<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Archiving and Interchange DTD v2.3 20070202//EN" "archivearticle.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" article-type="systematic-review" dtd-version="2.3" xml:lang="EN">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Vet. Sci.</journal-id>
<journal-title>Frontiers in Veterinary Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Vet. Sci.</abbrev-journal-title>
<issn pub-type="epub">2297-1769</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fvets.2025.1534114</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Veterinary Science</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Prevalence of Japanese encephalitis in pigs in Mainland China during 2000&#x2013;2024: a systemic review and meta-analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Liu</surname> <given-names>Xue-Tong</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2609560/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Jiang</surname> <given-names>Li-Dong</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Lin</surname> <given-names>Yu-Ting</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhao</surname> <given-names>Ran</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Qi</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1580932/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Zhang</surname> <given-names>Shu-Ying</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Ata</surname> <given-names>Emad Beshir</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1944040/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Xin</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Yuan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Zi-Xuan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Xu</surname> <given-names>Cui</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Xiao</surname> <given-names>Ying</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Yi-Fan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Leng</surname> <given-names>Xue</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2785538/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Gong</surname> <given-names>Qing-Long</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1311313/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Du</surname> <given-names>Rui</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/949621/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>College of Veterinary Medicine, Jilin Agricultural University</institution>, <addr-line>Changchun</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Ginseng and Antler Products Testing Center of the Ministry of Agricultural PRC, Jilin Agricultural University</institution>, <addr-line>Changchun</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>College of Chinese Medicine Materials, Jilin Agricultural University</institution>, <addr-line>Changchun</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>Department of Parasitology and Animal Diseases, Veterinary Research Institute, National Research Centre</institution>, <addr-line>Giza</addr-line>, <country>Egypt</country></aff>
<aff id="aff5"><sup>5</sup><institution>Department of Veterinary Medicine, College of Agriculture, Yanbian University</institution>, <addr-line>Yanji</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0002">
<p>Edited by: Abdul Wahaab, The Pennsylvania State University (PSU), United States</p>
</fn>
<fn fn-type="edited-by" id="fn0003">
<p>Reviewed by: Sawar Khan, Central South University, China</p>
<p>Mohsin Nawaz, University of Poonch Rawalakot, Pakistan</p>
<p>Ankita Singh, Duke University, United States</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Shu-Ying Zhang, <email>zhangshuying1201@163.com</email>; Qing-Long Gong, <email>gongqinglong1001@163.com</email>; Rui Du, <email>durui197101@sina.com</email></corresp>
<fn fn-type="equal" id="fn0001"><p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>07</day>
<month>02</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1534114</elocation-id>
<history>
<date date-type="received">
<day>25</day>
<month>11</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>01</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Liu, Jiang, Lin, Zhao, Wang, Zhang, Ata, Liu, Wang, Liu, Xu, Xiao, Wang, Leng, Gong and Du.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Liu, Jiang, Lin, Zhao, Wang, Zhang, Ata, Liu, Wang, Liu, Xu, Xiao, Wang, Leng, Gong and Du</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>Japanese encephalitis (JE) is an acute viral disease transmitted mainly by mosquitoes, primarily affecting Southeast Asia, and the Western Pacific. This study aimed to analyze the factors contributing to JE occurrence in pigs across China.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>A systematic search was done using six databases for the published epidemiological studies on porcine JE, including the Chinese Web of Knowledge (CNKI), Wan Fang Database, ScienceDirect, Web of Science, VIP Chinese Journal Database, and PubMed.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>A meta-analysis of 31 studies from 2000 to 2024 found an overall prevalence of 35.2% (95% CI: 25.1&#x2013;46.1). The highest prevalence occurred between 2010 and 2015 at 53.4% (95% CI: 44.2&#x2013;80.6), from 2010 to 2015, increased precipitation and favorable annual temperatures led to the proliferation of mosquitoes, causing Japanese Encephalitis outbreaks among swine. While the lowest was 2.5% (95% CI: 0.2&#x2013;6.6) in temperate climates. Serum samples showed the highest prevalence 38.1% (95% CI: 27.9&#x2013;48.9), and ELISA testing had a higher detection rate 38.2% (95% CI: 24.5&#x2013;52.9). In the farming mode subgroup, the highest prevalence was observed in the large-scale farming mode at 40.9% (95% CI: 26.4&#x2013;66.3).</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>The study highlights the spread of JE across China and suggests that it may be underrecognized in some areas. Continuous monitoring and improvements in farming practices are essential for controlling the disease.</p>
</sec>
</abstract>
<kwd-group>
<kwd>Japanese encephalitis</kwd>
<kwd>prevalence</kwd>
<kwd>pigs</kwd>
<kwd>zoonosis</kwd>
<kwd>meta-analysis</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="5"/>
<equation-count count="2"/>
<ref-count count="86"/>
<page-count count="16"/>
<word-count count="10793"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Veterinary Epidemiology and Economics</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>The farm animals play an essential role in maintaining the global food security (<xref ref-type="bibr" rid="ref1">1</xref>, <xref ref-type="bibr" rid="ref2">2</xref>). They were subjected to different pathogens that affected their productivity (<xref ref-type="bibr" rid="ref3 ref4 ref5">3&#x2013;5</xref>), especially the swine sector is affected by different pathogens (<xref ref-type="bibr" rid="ref6 ref7 ref8 ref9">6&#x2013;9</xref>).</p>
<p>Japanese encephalitis (JE) also known as Epidemic encephalitis B (<xref ref-type="bibr" rid="ref10">10</xref>), is a naturally occurring epidemic caused by the insect-born <italic>Japanese encephalitis virus (JEV)</italic>; a member of the flavivirus group (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref12">12</xref>) which leads to neurological disorders by affecting the central nervous system of animals (<xref ref-type="bibr" rid="ref13">13</xref>, <xref ref-type="bibr" rid="ref14">14</xref>), and has been classified as a category II of animal diseases in China (<xref ref-type="bibr" rid="ref15">15</xref>). Because of the disease zoonotic potentiality, the World Health Organization (WHO) recommends human immunization as the most effective means to control the JE (<xref ref-type="bibr" rid="ref16">16</xref>). Though the disease can occur year-round (<xref ref-type="bibr" rid="ref17">17</xref>), it shows distinct seasonality, peaking in summer and fall (<xref ref-type="bibr" rid="ref18">18</xref>). Outbreaks can also be triggered by poor feeding management, unsanitary conditions, and abnormal climate changes (<xref ref-type="bibr" rid="ref19">19</xref>). The <italic>JEV</italic> is transmitted by mosquito vectors (<xref ref-type="bibr" rid="ref20">20</xref>), with birds and bats serving as the primary reservoir hosts. It has a broad host range, including various animal species and humans. Notably, pigs, horses, and humans exhibit observable clinical symptoms, while other infected animals generally do not show significant signs of infection (<xref ref-type="bibr" rid="ref21">21</xref>). The pigs play a crucial role mainly as amplification hosts during human outbreaks (<xref ref-type="bibr" rid="ref17">17</xref>, <xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref23">23</xref>). Pigs may exhibit prolonged viremia, lasting from weeks to months, and are susceptible to the disease at any age (<xref ref-type="bibr" rid="ref24">24</xref>). Infection of sows during gestation period might result in abortion, stillbirth, or give birth to mummified fetuses. While, in boars, infection causes swollen testes, reduced sperm quality, diminished libido, and eventual reproductive failure (<xref ref-type="bibr" rid="ref25">25</xref>). The main route of infection is through biting of mosquitoes vector; mainly the Culex tritaeniorhynchus, fed on diseased pigs. The virus can survive and replicate within mosquitoes, which then transmit it to other pigs and people through bites (<xref ref-type="bibr" rid="ref26">26</xref>). Pigs play a crucial role as amplifying hosts in the JE transmission cycle, alongside water birds (<xref ref-type="bibr" rid="ref27">27</xref>). They can develop viremia sufficient to sustain transmission and are frequently linked to epizootic spillover leading to human JE cases (<xref ref-type="bibr" rid="ref27">27</xref>). Recent studies have revealed that pigs can shed <italic>JEV</italic> through multiple routes and maintain persistent infections, suggesting a potential for vector-free transmission among pigs (<xref ref-type="bibr" rid="ref27">27</xref>, <xref ref-type="bibr" rid="ref28">28</xref>). Pigs are primary reservoirs for the <italic>JEV</italic>, which mosquitoes can transmit to humans. In Mainland China, with the improvement of living standards, the number of pigs is increasing gradually. According to government statistics, in 2014, the number of pigs in Mainland China was estimated as approximately 465,827,000, and pork is commonly consumed by the Chinese population (<xref ref-type="bibr" rid="ref29">29</xref>). Therefore, pigs are the most important potential source for Japanese encephalitis infection in humans. Surprisingly, the virus can overcome the vector mosquito route and spread between swine herds through highly contagious oro-nasal secretions (<xref ref-type="bibr" rid="ref30">30</xref>). The virus persists even during winter when mosquito populations are low (<xref ref-type="bibr" rid="ref31">31</xref>), which complicate the eradication efforts. Consequently, the disease poses a serious threat to the pig farming industry, causing significant economic losses and hindering industry growth in China and globally (<xref ref-type="bibr" rid="ref32">32</xref>).</p>
<p>The epidemiological situation of the disease varies between the countries but mainly found across East and Southeast Asia, including China, Japan, Korea, India, Thailand, and Vietnam (<xref ref-type="bibr" rid="ref33">33</xref>). The causative agent can infect multiple host species including equine and swine. The <italic>JEV</italic> P3 strain was first isolated in China in 1949 and remained endemic for the next 60&#x202F;years (<xref ref-type="bibr" rid="ref34">34</xref>). Mosquito species are the primary vectors of this virus, while pigs are the main reservoirs that promote the transmission of <italic>JEV</italic> from animals to humans (<xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref35">35</xref>). However, China has a vast hog farming industry. According to statistics, the number of pigs farrowed reached 735.1 million in 2014 (<xref ref-type="bibr" rid="ref36">36</xref>). In 2015, 624 human cases of JE were reported in China, 19 of which were fatal (<xref ref-type="bibr" rid="ref26">26</xref>). Furthermore, the <italic>JEV</italic> has become a major pathogen causing reproductive disorders in pigs, leading to severe economic losses (<xref ref-type="bibr" rid="ref32">32</xref>), making it also a potential threat to human health (<xref ref-type="bibr" rid="ref24">24</xref>).</p>
<p>To our knowledge, no comprehensive systematic analysis of the overall prevalence of this disease has been conducted in China. Thus, this systematic review and meta-analysis aimed to examine the prevalence of JE in Chinese swine herds and assess potential risk factors: including time of sampling, area of sample collection, testing method, and type of samples, in addition to the evaluation of raw data from the included studies, geographic factors such as longitude, latitude, elevation, rainfall, humidity, temperature, and climate conditions were examined to determine their relationship to the prevalence of the disease.</p>
</sec>
<sec sec-type="materials|methods" id="sec6">
<label>2</label>
<title>Materials and methods</title>
<sec id="sec7">
<label>2.1</label>
<title>Search strategy</title>
<p>This study followed the PRISMA guidelines (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>) (<xref ref-type="bibr" rid="ref37">37</xref>, <xref ref-type="bibr" rid="ref38">38</xref>). Literature related to porcine JE was retrieved from six databases, including PubMed, ScienceDirect, Web of Science, CNKI, Wan Fang Data Knowledge Service Platform, and Wipro Chinese Journal Database. We reviewed all national literature on porcine JE published between January 1, 2000, and May 8, 2024, with sampling dates from 1997 to 2021.</p>
<p>The following formulas and MeSH terms were used in PubMed &#x201C;Swine,&#x201D; &#x201C;Pig,&#x201D; &#x201C;Encephalitis, Japanese&#x201D; and &#x201C;China&#x201D; were used in PubMed. Boolean operators &#x201C;AND&#x201D; were used to connect MeSH terms and &#x201C;OR&#x201D; to connect the entry terms.</p>
<p>In ScienceDirect, we searched for &#x201C;Prevalence,&#x201D; &#x201C;Swine,&#x201D; &#x201C;Japanese B Encephalitis,&#x201D; and &#x201C;China.&#x201D; In Web of Science, &#x201C;Japanese B Encephalitis,&#x201D; &#x201C;Swine,&#x201D; and &#x201C;Prevalence&#x201D; were used as keywords. In three Chinese databases, &#x201C;liuxingxingyixingnaoyan (in Chinese)&#x201D; and &#x201C;zhu (in Chinese)&#x201D; or &#x201C;yixingnaoyan (in Chinese)&#x201D; and &#x201C;zhu (in Chinese)&#x201D; were used to search with fuzzy search and synonym expansion in advanced searches. Detailed search formulas were provided in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S2</xref>. Retrieved articles were sorted and screened with Endnote X21 (version 21.2.0.17387).</p>
<p>Studies were included if they met the following criteria: (1) Study subjects must be pigs; (2) The objective must be to assess the prevalence of JE infection; (3) Data must include the total number of pigs tested and those testing positive; (4) The study must be conducted in China; (5) The study design must be cross-sectional; (6) The study must be published in Chinese or English. (7) The pigs must be naturally infected. Studies not meeting these criteria were excluded. Duplicate studies and review articles (non-research papers) were also excluded.</p>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Data extraction and quality assessment</title>
<p>Four reviewers utilized a standardized data collection form to extract data for the meta-analysis (<xref ref-type="bibr" rid="ref39">39</xref>). Discrepancies between reviewers or uncertainties regarding study quality were resolved by the lead author. The extracted data included: first author, sampling year, publication year, sample type, geographic area, province, latitude and longitude, elevation, mean annual temperature, humidity, max/min temperature, max daily precipitation, climate, testing method, age, sex, season of collection, feeding method, mode of swine husbandry, total swine samples, and number of positive samples for JE.</p>
<p>The quality of the publications was assessed using a standardized scoring method (<xref ref-type="bibr" rid="ref40">40</xref>). Each study was evaluated on specific criteria (such as randomized sampling, assay clarity, detailed sampling methods, clear sampling timeframes, and inclusion of four or more relevant factors). Each study received a score from 0 to 5 on a standardized scale.</p>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>Data analysis</title>
<p>All calculations, including those related to the prevalence of porcine JE, were conducted using R software (version 4.0.2) using data from multiple studies. The double-arcsine transform (PFT) were selected for rate conversion based on these results and prior research findings (<xref ref-type="table" rid="tab1">Table 1</xref>) (<xref ref-type="bibr" rid="ref41">41</xref>).</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Normal distribution test for the normal rate and the different conversion of the normal rate.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Conversion form</th>
<th align="center" valign="top">
<italic>W</italic>
</th>
<th align="center" valign="top">
<italic>P</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">PRAW</td>
<td align="center" valign="top">0.942</td>
<td align="center" valign="top">0.093</td>
</tr>
<tr>
<td align="left" valign="top">PLN</td>
<td align="center" valign="top">0.901</td>
<td align="center" valign="top">0.008</td>
</tr>
<tr>
<td align="left" valign="top">PLOGIT</td>
<td align="center" valign="top">0.979</td>
<td align="center" valign="top">0.793</td>
</tr>
<tr>
<td align="left" valign="top">PAS</td>
<td align="center" valign="top">0.966</td>
<td align="center" valign="top">0.406</td>
</tr>
<tr>
<td align="left" valign="top">PFT</td>
<td align="center" valign="top">0.969</td>
<td align="center" valign="top">0.500</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x201C;PRAW&#x201D;: original rate; &#x201C;PLN&#x201D;: logarithmic conversion; &#x201C;PLOGIT&#x201D;: logit transformation; &#x201C;PAS&#x201D;: arcsine transformation; &#x201C;PFT&#x201D;: double-arcsine transformation; &#x201C;NaN&#x201D;: meaningless number; &#x201C;NA&#x201D;: missing data.</p>
</table-wrap-foot>
</table-wrap>
<p>The PFT formula is:<disp-formula id="E1">
<mml:math id="M1">
<mml:mtable columnalign="left">
<mml:mtr>
<mml:mtd>
<mml:mi mathvariant="normal">t</mml:mi>
<mml:mo>=</mml:mo>
<mml:mo>arcsin</mml:mo>
<mml:mfenced close="}" open="{">
<mml:mrow>
<mml:mi mathvariant="normal">sqrt</mml:mi>
<mml:mfenced close="]" open="[">
<mml:mtable columnalign="left">
<mml:mtr>
<mml:mtd>
<mml:mi mathvariant="normal">r</mml:mi>
<mml:mo stretchy="true">/</mml:mo>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi mathvariant="normal">n</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:mfenced>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mfenced>
</mml:mrow>
</mml:mfenced>
<mml:mo>+</mml:mo>
<mml:mo>arcsin</mml:mo>
<mml:mfenced close="}" open="{">
<mml:mrow>
<mml:mi mathvariant="normal">sqrt</mml:mi>
<mml:mfenced close="]" open="[">
<mml:mtable columnalign="left">
<mml:mtr>
<mml:mtd>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi mathvariant="normal">r</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:mfenced>
<mml:mo stretchy="true">/</mml:mo>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi mathvariant="normal">n</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:mfenced>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mfenced>
</mml:mrow>
</mml:mfenced>
<mml:mspace width="thickmathspace"/>
<mml:mi mathvariant="normal">s</mml:mi>
<mml:mi mathvariant="normal">e</mml:mi>
<mml:mfenced open="(" close=")">
<mml:mi mathvariant="normal">t</mml:mi>
</mml:mfenced>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mo>=</mml:mo>
<mml:mi mathvariant="normal">sqrt</mml:mi>
<mml:mfenced close="]" open="[">
<mml:mtable columnalign="left">
<mml:mtr>
<mml:mtd>
<mml:mn>1</mml:mn>
<mml:mo stretchy="true">/</mml:mo>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi mathvariant="normal">n</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>0.5</mml:mn>
</mml:mrow>
</mml:mfenced>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mfenced>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:math>
</disp-formula><disp-formula id="E2">
<mml:math id="M2">
<mml:mi mathvariant="normal">p</mml:mi>
<mml:mo>=</mml:mo>
<mml:msup>
<mml:mfenced open="[" close="]">
<mml:mrow>
<mml:mo>sin</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi mathvariant="normal">t</mml:mi>
<mml:mo stretchy="true">/</mml:mo>
<mml:mn>2</mml:mn>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
</mml:mfenced>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:math>
</disp-formula></p>
<p>Note: t: conversion prevalence; r&#x202F;=&#x202F;positive rate; n&#x202F;=&#x202F;sample size; se&#x202F;=&#x202F;standard deviation.</p>
<p>Forest plots were employed to visualize the results and assess heterogeneity between studies. Heterogeneity was calculated using Cochran&#x2019;s Q-test and the <italic>I</italic><sup>2</sup> statistic, with 50% as the critical value for <italic>I</italic><sup>2</sup>. The <italic>&#x03C7;</italic><sup>2</sup> test (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) was also applied. <italic>I</italic><sup>2</sup>&#x202F;&#x003C;&#x202F;50%indicates low heterogeneity, suggesting that the differences in study results were primarily due to random errors. <italic>I</italic><sup>2</sup>&#x202F;&#x2265;&#x202F;50% indicated high heterogeneity and significant inconsistency between study results, suggesting that other factors may contribute to the observed variations. In such cases, potential factors contributing to heterogeneity require further investigation. These methods were applied to assess the statistical significance of heterogeneity in the selected studies. When heterogeneity was evident, a random-effects model was employed for meta-analysis (<xref ref-type="bibr" rid="ref42">42</xref>). Publication bias was evaluated with funnel plots, the trim-and-fill method, and Egger&#x2019;s test. Studies suggested that different subgroups may produce varying funnel plots due to changes in prevalence over time (<xref ref-type="bibr" rid="ref36">36</xref>). Thus, each subgroup was further evaluated through funnel plots and forest plots. Sensitivity analyses were conducted to determine if any single study significantly impacted the overall estimates (<xref ref-type="bibr" rid="ref43">43</xref>).</p>
<p>Heterogeneity is a critical metric in meta-analyses; thus, accurate assessing is essential to identifying key factors for preventing JE infection in pigs nationwide. To explore potential sources of heterogeneity, subgroup analyses and univariate regression were employed to identify its predictors. The factors assessed included; geographic region (Northeast vs. other regions), sampling period (post&#x2013;2015 vs. pre&#x2013;2010 and 2010&#x2013;2015), assay method (PCR vs. ELISA, RT-RAA, LAT), season (autumn vs. spring, summer, winter), sex (boars vs. sows), age classification (nursery pigs vs. Weaned piglets and fattening pigs), sample type (serum vs. organization, brain tissue, blood), feeding system (large-scale vs. free-range), and study quality (high-quality vs. medium-quality studies). To further explore other potential sources of heterogeneity, we further assessed their geographic factors, in groups, which included longitude, latitude, elevation, rainfall, humidity, and climate.</p>
<p>This meta-analysis adhered to the PRISMA guidelines (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>) (<xref ref-type="bibr" rid="ref37">37</xref>, <xref ref-type="bibr" rid="ref38">38</xref>, <xref ref-type="bibr" rid="ref44">44</xref>). Correlations were analyzed for each subgroup based on testing method and region to identify heterogeneity sources. Heterogeneity in covariates was quantified using the R<sup>2</sup> statistic. This meta-analysis lacked a review protocol and was not registered with the Cochrane Database. The R codes for this meta-analysis are available in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S3</xref>.</p>
</sec>
</sec>
<sec sec-type="results" id="sec10">
<label>3</label>
<title>Results</title>
<p>A total of 481 studies were identified from six databases. A meta-analysis was performed on 31 studies that met the inclusion and exclusion criteria (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Among the included studies, five had quality scores between 4 and 5, 26 scored between 2 and 3, and none scored between 0 and 1.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Flow diagram of eligible studies for searching and selecting.</p>
</caption>
<graphic xlink:href="fvets-12-1534114-g001.tif"/>
</fig>
<sec id="sec11">
<label>3.1</label>
<title>Publishing biased results</title>
<p>We assumed a random-effects model because there was apparent heterogeneity in the studies (<italic>I</italic><sup>2</sup> =&#x202F;100%, <italic>p</italic> =&#x202F;0). The extent of publication bias was assessed and illustrated by a funnel plot (<xref ref-type="fig" rid="fig2">Figure 2</xref>). The Egger&#x2019;s test (<italic>p</italic> &#x003C;&#x202F;0.05) revealed that, there was publication bias (<italic>p</italic> =&#x202F;0.8732, <xref ref-type="fig" rid="fig3">Figure 3</xref>). The heterogeneity results were shown by the forest plot (<xref ref-type="fig" rid="fig4">Figure 4</xref>). The result of the trim and filled analysis showed that, no trimming was performed, and no data was changed, which meant there may be no significant publication bias. Therefore, our pooled estimates were relatively robust (<italic>p</italic> =&#x202F;0, <xref ref-type="fig" rid="fig5">Figure 5</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables S3, S4</xref>). The publication bias should be interpreted with caution because of the inconsistency in the results.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Funnel plot with pseudo 95% confidence interval limits for the examination of publication bias.</p>
</caption>
<graphic xlink:href="fvets-12-1534114-g002.tif"/>
</fig>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Egger&#x2019;s test for publication bias.</p>
</caption>
<graphic xlink:href="fvets-12-1534114-g003.tif"/>
</fig>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Forest plot of prevalence of epidemic encephalitis B in pig amongst studies conducted in China.</p>
</caption>
<graphic xlink:href="fvets-12-1534114-g004.tif"/>
</fig>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Cut-and-fill method for publication bias.</p>
</caption>
<graphic xlink:href="fvets-12-1534114-g005.tif"/>
</fig>
</sec>
<sec id="sec12">
<label>3.2</label>
<title>Sensitivity analysis results</title>
<p>Sensitivity analyses showed that, excluding any single study did not change the overall results, which remained consistent with prior analyses (<xref ref-type="fig" rid="fig6">Figure 6</xref>). Therefore, the findings of this review and meta-analysis were robust and reliable.</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Sensitivity analysis.</p>
</caption>
<graphic xlink:href="fvets-12-1534114-g006.tif"/>
</fig>
</sec>
<sec id="sec13">
<label>3.3</label>
<title>A meta-analysis of Japanese encephalitis in pigs in China</title>
<p>In China, all provinces showed a high prevalence of JE, except for Qinghai, Tibet, and Xinjiang, which were unaffected regions (<xref ref-type="bibr" rid="ref45">45</xref>). Our meta-analysis covered seven geographic subregions: East China, South China, North China, Central China, Southwest China, Northwest China, and Northeast China. The overall prevalence of JE in the national swine population was 35.2% (95% CI: 25.1&#x2013;46.1; <xref ref-type="table" rid="tab2">Table 2</xref>). South China had the highest prevalence among regions at 43.8% (95% CI: 21.6&#x2013;67.4; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref>). Jiangxi Province had the highest prevalence at 86.0% (95% CI: 24.8&#x2013;100.0; <xref ref-type="table" rid="tab3">Table 3</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S10</xref>), followed by Chongqing Municipality at 77.4% (95% CI: 71.1&#x2013;83.2; <xref ref-type="table" rid="tab3">Table 3</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S10</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Pooled prevalence of Japanese encephalitis of swine in Mainland China.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="2"/>
<th align="center" valign="top" rowspan="2">No. studies</th>
<th align="center" valign="top" rowspan="2">No. tested</th>
<th align="center" valign="top" rowspan="2">No. positive</th>
<th align="center" valign="top" rowspan="2">% (95% CI&#x002A;)</th>
<th align="center" valign="top" colspan="3">Heterogeneity</th>
<th align="center" valign="top" colspan="2">Univariate meta-regression</th>
</tr>
<tr>
<th align="center" valign="top">
<italic>&#x03C7;</italic>
<sup>2</sup>
</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top"><italic>I</italic><sup>2</sup> (%)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">Coefficient (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="10">Region&#x002A;</td>
</tr>
<tr>
<td align="left" valign="top">Central China</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">6,663</td>
<td align="center" valign="top">2,687</td>
<td align="center" valign="top">38.6% (16.0&#x2013;64.2)</td>
<td align="center" valign="top">1,190.86</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Eastern China</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">1,683</td>
<td align="center" valign="top">423</td>
<td align="center" valign="top">31.4% (5.1&#x2013;66.9)</td>
<td align="center" valign="top">744.48</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Northeastern China</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">4,149</td>
<td align="center" valign="top">709</td>
<td align="center" valign="top">7.4% (0.3&#x2013;21.9)</td>
<td align="center" valign="top">476.92</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td align="center" valign="top">0.0402</td>
<td align="center" valign="top">&#x2212;0.3149 (&#x2212;0.6156 to &#x2212;0.0141)</td>
</tr>
<tr>
<td align="left" valign="top">Northern China</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">625</td>
<td align="center" valign="top">59</td>
<td align="center" valign="top">9.3% (7.1&#x2013;11.8)</td>
<td align="center" valign="top">1.69</td>
<td align="center" valign="top">0.43</td>
<td align="center" valign="top">0.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Northwestern China</td>
<td align="center" valign="top">4</td>
<td align="center" valign="top">2,896</td>
<td align="center" valign="top">1,404</td>
<td align="center" valign="top">38.2% (6.0&#x2013;78.1)</td>
<td align="center" valign="top">2,327.27</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.9%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Southern China</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">9,837</td>
<td align="center" valign="top">5,348</td>
<td align="center" valign="top">43.8% (21.6&#x2013;67.4)</td>
<td align="center" valign="top">1,173.96</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Southwestern China</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">12,822</td>
<td align="center" valign="top">4,873</td>
<td align="center" valign="top">26.7% (17.4&#x2013;37.2)</td>
<td align="center" valign="top">1,969.00</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Sampling years</td>
</tr>
<tr>
<td align="left" valign="top">2010 ago</td>
<td align="center" valign="top">25</td>
<td align="center" valign="top">10,582</td>
<td align="center" valign="top">4,280</td>
<td align="center" valign="top">36.2% (27.1&#x2013;45.9)</td>
<td align="center" valign="top">1,740.87</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">98.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">2010&#x2013;2015</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">25,567</td>
<td align="center" valign="top">11,236</td>
<td align="center" valign="top">63.4% (44.2&#x2013;80.6)</td>
<td align="center" valign="top">2,187.10</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.7%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">2015 late</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">3,839</td>
<td align="center" valign="top">125</td>
<td align="center" valign="top">7.8% (3.4&#x2013;13.5)</td>
<td align="center" valign="top">75.71</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">93.4%</td>
<td align="center" valign="top">0.0003</td>
<td align="center" valign="top">&#x2212;0.4193 (&#x2212;0.6484 to &#x2212;0.1902)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Sample</td>
</tr>
<tr>
<td align="left" valign="top">Organization</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">4.4% (0.0&#x2013;17.7)</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">&#x2013;</td>
<td align="center" valign="top">&#x2013;</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Brain tissue</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">1,120</td>
<td align="center" valign="top">78</td>
<td align="center" valign="top">11.0% (1.7&#x2013;26.5)</td>
<td align="center" valign="top">16.61</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">94.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Serum</td>
<td align="center" valign="top">27</td>
<td align="center" valign="top">51,783</td>
<td align="center" valign="top">20,153</td>
<td align="center" valign="top">38.1% (27.9&#x2013;48.9)</td>
<td align="center" valign="top">8,032.47</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.7%</td>
<td align="center" valign="top">0.0148</td>
<td align="center" valign="top">0.3637 (0.0713&#x2013;0.6562)</td>
</tr>
<tr>
<td align="left" valign="top">Blood</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">167</td>
<td align="center" valign="top">11</td>
<td align="center" valign="top">6.6% (3.3&#x2013;10.9)</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">&#x2013;</td>
<td align="center" valign="top">&#x2013;</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Detection method&#x002A;</td>
</tr>
<tr>
<td align="left" valign="top">ELISA</td>
<td align="center" valign="top">16</td>
<td align="center" valign="top">15,152</td>
<td align="center" valign="top">6,435</td>
<td align="center" valign="top">38.2% (24.5&#x2013;52.9)</td>
<td align="center" valign="top">3,897.70</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">PCR</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">6,725</td>
<td align="center" valign="top">1,072</td>
<td align="center" valign="top">8.5% (0.6&#x2013;23.2)</td>
<td align="center" valign="top">2,405.11</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.8%</td>
<td align="center" valign="top">0.0056</td>
<td align="center" valign="top">&#x2212;0.3277 (&#x2212;0.5595 to &#x2212;0.0959)</td>
</tr>
<tr>
<td align="left" valign="top">RT-RAA</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">185</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">6.5% (3.3&#x2013;10.5)</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">&#x2013;</td>
<td align="center" valign="top">&#x2013;</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">LAT</td>
<td align="center" valign="top">9</td>
<td align="center" valign="top">7,403</td>
<td align="center" valign="top">2,909</td>
<td align="center" valign="top">32.4% (19.8&#x2013;46.5)</td>
<td align="center" valign="top">805.92</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Breeding mode</td>
</tr>
<tr>
<td align="left" valign="top">Farm</td>
<td align="center" valign="top">18</td>
<td align="center" valign="top">43,333</td>
<td align="center" valign="top">16,971</td>
<td align="center" valign="top">40.9% (26.4&#x2013;56.3)</td>
<td align="center" valign="top">7,751.66</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.8%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Free range</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">5,328</td>
<td align="center" valign="top">2,736</td>
<td align="center" valign="top">35.8% (14.9&#x2013;59.7)</td>
<td align="center" valign="top">1,517.22</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td align="center" valign="top">0.7430</td>
<td align="center" valign="top">&#x2212;0.0451 (&#x2212;0.3145 to 0.2243)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Season&#x002A;</td>
</tr>
<tr>
<td align="left" valign="top">Spring</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">1,230</td>
<td align="center" valign="top">258</td>
<td align="center" valign="top">27.5% (10.8&#x2013;48.1)</td>
<td align="center" valign="top">180.84</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">97.2%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Winter</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">251</td>
<td align="center" valign="top">131</td>
<td align="center" valign="top">51.3% (13.6&#x2013;88.2)</td>
<td align="center" valign="top">50.26</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">96.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Autumn</td>
<td align="center" valign="top">6</td>
<td align="center" valign="top">1,564</td>
<td align="center" valign="top">565</td>
<td align="center" valign="top">23.8% (5.4&#x2013;49.3)</td>
<td align="center" valign="top">1,011.42</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.5%</td>
<td align="center" valign="top">0.4227</td>
<td align="center" valign="top">&#x2212;0.1292 (&#x2212;0.4450 to 0.1866)</td>
</tr>
<tr>
<td align="left" valign="top">Summer</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">3,084</td>
<td align="center" valign="top">1,464</td>
<td align="center" valign="top">36.6% (15.3&#x2013;60.9)</td>
<td align="center" valign="top">1,342.69</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.3%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Gender</td>
</tr>
<tr>
<td align="left" valign="top">Female</td>
<td align="center" valign="top">9</td>
<td align="center" valign="top">4,680</td>
<td align="center" valign="top">2,753</td>
<td align="center" valign="top">50.0% (26.8&#x2013;73.3)</td>
<td align="center" valign="top">1,451.80</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Male</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">804</td>
<td align="center" valign="top">303</td>
<td align="center" valign="top">40.6% (19.4&#x2013;63.7)</td>
<td align="center" valign="top">365.72</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.1%</td>
<td align="center" valign="top">0.5847</td>
<td align="center" valign="top">&#x2212;0.0925 (&#x2212;0.4243 to 0.2393)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Age</td>
</tr>
<tr>
<td align="left" valign="top">Nursery pigs</td>
<td align="center" valign="top">9</td>
<td align="center" valign="top">3,219</td>
<td align="center" valign="top">1,078</td>
<td align="center" valign="top">31.2% (14.6&#x2013;50.8)</td>
<td align="center" valign="top">1,140.24</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.3%</td>
<td align="center" valign="top">0.1938</td>
<td align="center" valign="top">&#x2212;0.1826 (&#x2212;0.4581 to 0.0929)</td>
</tr>
<tr>
<td align="left" valign="top">Weaned piglets</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">1,530</td>
<td align="center" valign="top">360</td>
<td align="center" valign="top">48.4% (14.3&#x2013;83.4)</td>
<td align="center" valign="top">361.13</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.9%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Fattening pigs</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">5,953</td>
<td align="center" valign="top">2,783</td>
<td align="center" valign="top">49.7% (29.8&#x2013;69.7)</td>
<td align="center" valign="top">1,522.45</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Quality level</td>
</tr>
<tr>
<td align="left" valign="top">0&#x2013;2</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">27,735</td>
<td align="center" valign="top">11,342</td>
<td align="center" valign="top">29.3% (11.4&#x2013;51.2)</td>
<td align="center" valign="top">1,652.05</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">3&#x2013;4</td>
<td align="center" valign="top">24</td>
<td align="center" valign="top">25,523</td>
<td align="center" valign="top">9,636</td>
<td align="center" valign="top">35.1% (24.2&#x2013;46.9)</td>
<td align="center" valign="top">7,212.33</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.7%</td>
<td align="center" valign="top">0.6245</td>
<td align="center" valign="top">0.0628 (&#x2212;0.1887 to 0.3144)</td>
</tr>
<tr>
<td align="left" valign="top">Total</td>
<td align="center" valign="top">31</td>
<td align="center" valign="top">53,258</td>
<td align="center" valign="top">20,978</td>
<td align="center" valign="top">35.2% (25.1&#x2013;46.1)</td>
<td align="center" valign="top">10,151.33</td>
<td align="center" valign="top">0.000</td>
<td align="center" valign="top">99.7%</td>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>CI&#x002A;: Confidence interval.</p>
<p>Region&#x002A;: Central China: Hubei; Eastern China: Zhejiang; Northeastern China: Heilongjiang, Jilin, Liaoning; Northern China: Inner Mongolia; Northwestern China: Ningxia, Qinghai, Xinjiang.</p>
<p>Method&#x002A;: ELISA: Enzyme linked immunosorbent assay; PCR: Polymerase Chain Reaction; RT-RAA: Reverse Transcription Recombinase Aided Amplification; LAT: Latex agglutination test.</p>
<p>Season&#x002A;: Spring: Mar to May; Summer: Jun to Aug.; Autumn: Sep to Nov; Winter: Dec to Feb.</p>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Estimated pooled seroprevalence of Japanese encephalitis by provincial regions in China.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Province</th>
<th align="center" valign="top">No. Studies</th>
<th align="left" valign="top">Region</th>
<th align="center" valign="top">No. tested</th>
<th align="center" valign="top">No. positive</th>
<th align="center" valign="top">% Prevalence</th>
<th align="center" valign="top">% (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Beijing</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">North China</td>
<td align="center" valign="top">172</td>
<td align="center" valign="top">13</td>
<td align="center" valign="top">7.5%</td>
<td align="center" valign="top">4.0&#x2013;12.0</td>
</tr>
<tr>
<td align="left" valign="top">Fujian</td>
<td align="center" valign="top">2</td>
<td align="left" valign="bottom">East China</td>
<td align="center" valign="top">284</td>
<td align="center" valign="top">134</td>
<td align="center" valign="top">48.0%</td>
<td align="center" valign="top">11.5&#x2013;85.8</td>
</tr>
<tr>
<td align="left" valign="top">Gansu</td>
<td align="center" valign="top">2</td>
<td align="left" valign="bottom">Northwest China</td>
<td align="center" valign="top">1,756</td>
<td align="center" valign="top">1,331</td>
<td align="center" valign="top">68.4%</td>
<td align="center" valign="top">45.3&#x2013;87.5</td>
</tr>
<tr>
<td align="left" valign="top">Guangdong</td>
<td align="center" valign="top">3</td>
<td align="left" valign="bottom">Southern China</td>
<td align="center" valign="top">4,603</td>
<td align="center" valign="top">2,424</td>
<td align="center" valign="top">62.1%</td>
<td align="center" valign="top">35.6&#x2013;85.2</td>
</tr>
<tr>
<td align="left" valign="top">Guangxi</td>
<td align="center" valign="top">4</td>
<td align="left" valign="bottom">Southern China</td>
<td align="center" valign="top">7,148</td>
<td align="center" valign="top">4,081</td>
<td align="center" valign="top">41.5%</td>
<td align="center" valign="top">12.2&#x2013;74.6</td>
</tr>
<tr>
<td align="left" valign="top">Guizhou</td>
<td align="center" valign="top">2</td>
<td align="left" valign="bottom">Southwest China</td>
<td align="center" valign="top">3,498</td>
<td align="center" valign="top">1,594</td>
<td align="center" valign="top">51.2%</td>
<td align="center" valign="top">34.4&#x2013;67.9</td>
</tr>
<tr>
<td align="left" valign="top">Hainan</td>
<td align="center" valign="top">2</td>
<td align="left" valign="top">Southern China</td>
<td align="center" valign="top">348</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">67.0%</td>
<td align="center" valign="top">0.0&#x2013;100.0</td>
</tr>
<tr>
<td align="left" valign="top">Hebei</td>
<td align="center" valign="top">1</td>
<td align="left" valign="top">North China</td>
<td align="center" valign="top">365</td>
<td align="center" valign="top">35</td>
<td align="center" valign="top">9.6%</td>
<td align="center" valign="top">6.8&#x2013;12.8</td>
</tr>
<tr>
<td align="left" valign="top">Henan</td>
<td align="center" valign="top">3</td>
<td align="left" valign="bottom">Central China</td>
<td align="center" valign="top">824</td>
<td align="center" valign="top">385</td>
<td align="center" valign="top">23.9%</td>
<td align="center" valign="top">0.0&#x2013;73.3</td>
</tr>
<tr>
<td align="left" valign="top">Heilongjiang</td>
<td align="center" valign="top">3</td>
<td align="left" valign="bottom">Northeast China</td>
<td align="center" valign="top">1,286</td>
<td align="center" valign="top">110</td>
<td align="center" valign="top">7.7%</td>
<td align="center" valign="top">3.4&#x2013;13.3</td>
</tr>
<tr>
<td align="left" valign="top">Hubei</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">Central China</td>
<td align="center" valign="top">30</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0.0%</td>
<td align="center" valign="top">0.0&#x2013;100.0</td>
</tr>
<tr>
<td align="left" valign="top">Hunan</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">Central China</td>
<td align="center" valign="top">3,026</td>
<td align="center" valign="top">583</td>
<td align="center" valign="top">19.3%</td>
<td align="center" valign="top">17.9&#x2013;20.7</td>
</tr>
<tr>
<td align="left" valign="top">Jilin</td>
<td align="center" valign="top">3</td>
<td align="left" valign="bottom">Northeast China</td>
<td align="center" valign="top">2,251</td>
<td align="center" valign="top">487</td>
<td align="center" valign="top">7.0%</td>
<td align="center" valign="top">0.0&#x2013;30.9</td>
</tr>
<tr>
<td align="left" valign="top">Jiangsu</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">East China</td>
<td align="center" valign="top">363</td>
<td align="center" valign="top">170</td>
<td align="center" valign="top">47.8%</td>
<td align="center" valign="top">41.7&#x2013;52.0</td>
</tr>
<tr>
<td align="left" valign="top">Jiangxi</td>
<td align="center" valign="top">2</td>
<td align="left" valign="bottom">Southern China</td>
<td align="center" valign="top">301</td>
<td align="center" valign="top">213</td>
<td align="center" valign="top">86.0%</td>
<td align="center" valign="top">24.8&#x2013;100.0</td>
</tr>
<tr>
<td align="left" valign="top">Liaoning</td>
<td align="center" valign="top">2</td>
<td align="left" valign="bottom">Northeast China</td>
<td align="center" valign="top">363</td>
<td align="center" valign="top">82</td>
<td align="center" valign="top">9.1%</td>
<td align="center" valign="top">0.0&#x2013;52.0</td>
</tr>
<tr>
<td align="left" valign="top">Inner Mongolia</td>
<td align="center" valign="top">3</td>
<td align="left" valign="bottom">Northwest China</td>
<td align="center" valign="top">1,289</td>
<td align="center" valign="top">50</td>
<td align="center" valign="top">34.0%</td>
<td align="center" valign="top">27.4&#x2013;100.0</td>
</tr>
<tr>
<td align="left" valign="top">Shandong</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">East China</td>
<td align="center" valign="top">832</td>
<td align="center" valign="top">14</td>
<td align="center" valign="top">1.7%</td>
<td align="center" valign="top">0.9&#x2013;2.6</td>
</tr>
<tr>
<td align="left" valign="top">Shaanxi</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">Northwest China</td>
<td align="center" valign="top">188</td>
<td align="center" valign="top">64</td>
<td align="center" valign="top">34.0%</td>
<td align="center" valign="top">27.4&#x2013;41.0</td>
</tr>
<tr>
<td align="left" valign="top">Shanghai</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">East China</td>
<td align="center" valign="top">152</td>
<td align="center" valign="top">33</td>
<td align="center" valign="top">21.7%</td>
<td align="center" valign="top">15.5&#x2013;28.6</td>
</tr>
<tr>
<td align="left" valign="top">Sichuan</td>
<td align="center" valign="top">3</td>
<td align="left" valign="bottom">Southwest China</td>
<td align="center" valign="top">1,263</td>
<td align="center" valign="top">330</td>
<td align="center" valign="top">20.4%</td>
<td align="center" valign="top">6.7&#x2013;38.9</td>
</tr>
<tr>
<td align="left" valign="top">Xizang</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">Southwest China</td>
<td align="center" valign="top">454</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">5.1%</td>
<td align="center" valign="top">3.2&#x2013;7.3</td>
</tr>
<tr>
<td align="left" valign="top">Yunnan</td>
<td align="center" valign="top">5</td>
<td align="left" valign="bottom">Southwest China</td>
<td align="center" valign="top">2,895</td>
<td align="center" valign="top">1,225</td>
<td align="center" valign="top">26.9%</td>
<td align="center" valign="top">10.7&#x2013;47.1</td>
</tr>
<tr>
<td align="left" valign="top">Chongqing</td>
<td align="center" valign="top">1</td>
<td align="left" valign="bottom">Southwest China</td>
<td align="center" valign="top">186</td>
<td align="center" valign="top">144</td>
<td align="center" valign="top">77.4%</td>
<td align="center" valign="top">71.1&#x2013;83.2</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>In this study, subgroup analyses were conducted based on sampling time, region, season, testing method, age, province, sex, breeding mode, sample type, and quality score. Sampling time, region, testing method, and sample type were identified as significant risk factors for <italic>JEV</italic> infection in pigs (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05, <xref ref-type="table" rid="tab2">Table 2</xref>). The prevalence of JE was 63.4% (95% CI: 44.2&#x2013;80.6; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref>) with studies conducted between 2010 and 2015 were higher than other periods. The infection rate in South China was 43.8% (95% CI: 21.6&#x2013;67.4; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref>), which was higher than the other regions. While the lowest rate in the northeast was recorded in 7.4%, (95%CI: 0.3&#x2013;21.9; <xref ref-type="table" rid="tab2">Table 2</xref>). In the climate subgroup, the prevalence in temperate monsoon climates was 12.7% (95% CI: 5.7&#x2013;21.9; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S19</xref>) compared to 5.1% (95% CI: 3.2&#x2013;7.3; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S19</xref>) in highland alpine regions. Within the testing method subgroup, the prevalence using ELISA was 38.2% (95% CI: 24.5&#x2013;52.9; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S4</xref>), while RT-RAA had the lowest prevalence rate in 6.5% (95%CI: 3.3&#x2013;10.5; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S4</xref>). The prevalence among samples tested as serum was 38.1% (95% CI: 27.9&#x2013;48.9; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S3</xref>). The prevalence of porcine JE in the assay method subgroups ranged from 38.2% (95% CI: 24.5&#x2013;52.9; <xref ref-type="table" rid="tab2">Table 2</xref>) to 6.5% (95% CI: 3.3&#x2013;10.5). Among all sample types, serological testing samples had the highest prevalence of 38.1% (95% CI: 27.9&#x2013;48.9; <xref ref-type="table" rid="tab2">Table 2</xref>), whereas tissue samples had the lowest prevalence (4.4, 95% CI: 0.0&#x2013;17.7; <xref ref-type="table" rid="tab2">Table 2</xref>). In the seasonal subgroups, winter had the highest prevalence of 51.3% (95% CI: 13.6&#x2013;88.2; <xref ref-type="table" rid="tab2">Table 2</xref>) and autumn had the lowest prevalence of 23.8% (95% CI: 5.4&#x2013;49.3; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S6</xref>). Among the age subgroups, fattening pigs were more affected, with a prevalence of 49.7% (95% CI: 29.8&#x2013;69.7; <xref ref-type="table" rid="tab2">Table 2</xref>), meanwhile nursery pigs had the lowest prevalence of 31.2% (95% CI: 14.6&#x2013;50.8) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S8</xref>). Among the sex subgroups, the prevalence was higher in saws (50, 95%CI: 26.8&#x2013;73.3; <xref ref-type="table" rid="tab2">Table 2</xref>) than in boars (40.6, 95%CI: 19.4&#x2013;63.7; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S7</xref>). Among the different farming modes, the positive detection rate was significantly higher in mass culture (41.0, 95% CI: 26.4&#x2013;56.3; <xref ref-type="table" rid="tab2">Table 2</xref>) than in free-range mode (35.8, 95% CI: 14.9&#x2013;59.7; <xref ref-type="table" rid="tab2">Table 2</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S5</xref>). In the quality score subgroup, the prevalence of score 3&#x2013;4 (35.1, 95% CI: 24.2&#x2013;46.9; <xref ref-type="table" rid="tab2">Table 2</xref>) was higher than 0&#x2013;2 (29.3, 95% CI: 11.4&#x2013;51.2) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S9</xref>).</p>
<p>In addition, geographic factors were analyzed to further investigate the risk factors for the prevalence of porcine JE, such as latitude, longitude, rainfall, altitude, climate, and temperature variation. In the northern latitude subgroup, the highest prevalence was found at 20&#x2013;30 degrees north latitude (44.8, 95% CI: 32.4&#x2013;57.4; <xref ref-type="table" rid="tab4">Table 4</xref>), whereas the lowest prevalence was found at 40&#x2013;50 degrees north latitude (10.9, 95% CI: 10.1&#x2013;11.7; <xref ref-type="table" rid="tab4">Table 4</xref>). In the east longitude subgroup, the prevalence was higher in the 90&#x2013;110 degree longitude range compared to the other two groups (49.5, 95% CI: 48.7&#x2013;50.4; <xref ref-type="table" rid="tab4">Table 4</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S12</xref>). In the altitude subgroup, the prevalence of positive detections was higher in the altitude range 0&#x2013;1,000 (47.1, 95% CI: 25.8&#x2013;68.9; <xref ref-type="table" rid="tab4">Table 4</xref>) than in the range 4,000&#x2013;15,000 (21.7, 95% CI: 6.2&#x2013;43.1; <xref ref-type="table" rid="tab4">Table 4</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S13</xref>). The highest positive detection rate was observed at rainfall levels of 150&#x2013;200 (63.7, 95% CI: 17.1&#x2013;98.1; <xref ref-type="table" rid="tab4">Table 4</xref>) compared to 0&#x2013;50 (24.9, 95% CI: 10.4&#x2013;43.1; <xref ref-type="table" rid="tab4">Table 4</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S14</xref>), and the highest prevalence rate was observed in the humidity subgroups of 75&#x2013;85% at 46.6% (95% CI: 45.9&#x2013;47.3; <xref ref-type="table" rid="tab4">Table 4</xref>), while the lowest prevalence was observed at 40&#x2013;65% (12.4, 95% CI: 4.5&#x2013;23.2; <xref ref-type="table" rid="tab4">Table 4</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S15</xref>). In the temperature subgroup, the highest prevalence of 53.7% (95% CI: 34.7&#x2013;72.2; <xref ref-type="table" rid="tab4">Table 4</xref>) was observed when the temperature reached 20&#x2013;25&#x00B0;C, while the lowest prevalence of 14.8% (95% CI: 5.7&#x2013;27.2; <xref ref-type="table" rid="tab4">Table 4</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figures S16&#x2013;118</xref>) was observed when the temperature was ranged from 0 to 10&#x00B0;C. The prevalence was highest when the temperature reached 20&#x2013;25&#x00B0;C, while the lowest prevalence was observed when the temperature was 0&#x2013;10&#x00B0;C (95% CI: 5.7&#x2013;27.2; <xref ref-type="table" rid="tab4">Table 4</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figures S16&#x2013;118</xref>).</p>
<p>Heterogeneity across subgroups was explained by the assay method (covariate) (range 0&#x2013;79.25%; R<sup>2</sup>-method) and geographic region (covariate) (range 60.97&#x2013;97.04%; R<sup>2</sup>-country).</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Pooled prevalence of Japanese encephalitis of swine in Mainland China.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="2"/>
<th align="center" valign="top" rowspan="2">No. studies</th>
<th align="center" valign="top" rowspan="2">No. tested</th>
<th align="center" valign="top" rowspan="2">No. positive</th>
<th align="center" valign="top" rowspan="2">% (95% CI&#x002A;)</th>
<th align="center" valign="top" colspan="3">Heterogeneity</th>
<th align="center" valign="top" colspan="2">Univariate meta-regression</th>
</tr>
<tr>
<th align="center" valign="top">
<italic>&#x03C7;</italic>
<sup>2</sup>
</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top"><italic>I</italic><sup>2</sup> (%)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">Coefficient (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="10">Latitude&#x002A;</td>
</tr>
<tr>
<td align="left" valign="top">20&#x2013;30</td>
<td align="center" valign="top">27</td>
<td align="center" valign="top">21,555</td>
<td align="center" valign="top">9,994</td>
<td align="center" valign="top">44.8% (32.4&#x2013;57.7)</td>
<td align="center" valign="top">4,135.20</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">30&#x2013;40</td>
<td align="center" valign="top">17</td>
<td align="center" valign="top">5,581</td>
<td align="center" valign="top">2,472</td>
<td align="center" valign="top">30.9% (17.8&#x2013;45.8)</td>
<td align="center" valign="top">2,613.83</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">40&#x2013;50</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">5,554</td>
<td align="center" valign="top">764</td>
<td align="center" valign="top">10.9% (10.1&#x2013;11.7)</td>
<td align="center" valign="top">808.15</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.6%</td>
<td align="center" valign="top">0.0001</td>
<td align="center" valign="top">&#x2212;0.3923 (&#x2212;0.5901 to &#x2212;0.1945)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Longitude</td>
</tr>
<tr>
<td align="left" valign="top">90&#x2013;110</td>
<td align="center" valign="top">26</td>
<td align="center" valign="top">14,525</td>
<td align="center" valign="top">7,318</td>
<td align="center" valign="top">37.8% (27.6&#x2013;48.6)</td>
<td align="center" valign="top">3,126.16</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.2%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">110&#x2013;120</td>
<td align="center" valign="top">21</td>
<td align="center" valign="top">14,113</td>
<td align="center" valign="top">5,200</td>
<td align="center" valign="top">34.8% (19.0&#x2013;52.5)</td>
<td align="center" valign="top">4,811.60</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">120&#x2013;130</td>
<td align="center" valign="top">9</td>
<td align="center" valign="top">4,052</td>
<td align="center" valign="top">712</td>
<td align="center" valign="top">9.2% (2.9&#x2013;18.3)</td>
<td align="center" valign="top">538.56</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.5%</td>
<td align="center" valign="top">0.0044</td>
<td align="center" valign="top">&#x2212;0.3394 (&#x2212;0.5728 to &#x2212;0.1061)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Altitude</td>
</tr>
<tr>
<td align="left" valign="top">0&#x2013;1,000</td>
<td align="center" valign="top">14</td>
<td align="center" valign="top">9,463</td>
<td align="center" valign="top">3,867</td>
<td align="center" valign="top">47.1% (25.8&#x2013;68.9)</td>
<td align="center" valign="top">2,254.03</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">1,000&#x2013;4,000</td>
<td align="center" valign="top">22</td>
<td align="center" valign="top">14,504</td>
<td align="center" valign="top">5,639</td>
<td align="center" valign="top">22.8% (12.7&#x2013;34.7)</td>
<td align="center" valign="top">4,314.25</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.5%</td>
<td align="center" valign="top">0.0915</td>
<td align="center" valign="top">&#x2212;0.1580 (&#x2212;0.3416 to 0.0255)</td>
</tr>
<tr>
<td align="left" valign="top">4,000&#x2013;15,000</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2,441</td>
<td align="center" valign="top">607</td>
<td align="center" valign="top">21.7% (6.2&#x2013;43.1)</td>
<td align="center" valign="top">1,122.04</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.5%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">15,000&#x2013;20,000</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">5,156</td>
<td align="center" valign="top">2,826</td>
<td align="center" valign="top">36.6% (21.5&#x2013;53.1)</td>
<td align="center" valign="top">1,192.30</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.2%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">20,000&#x2013;40,000</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">1,126</td>
<td align="center" valign="top">291</td>
<td align="center" valign="top">32.8% (1.4&#x2013;79.1)</td>
<td align="center" valign="top">380.70</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.5%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Rainfall</td>
</tr>
<tr>
<td align="left" valign="top">0&#x2013;50</td>
<td align="center" valign="top">9</td>
<td align="center" valign="top">3,139</td>
<td align="center" valign="top">1,519</td>
<td align="center" valign="top">24.9% (10.4&#x2013;43.1)</td>
<td align="center" valign="top">1,680.95</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.5%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">50&#x2013;100</td>
<td align="center" valign="top">32</td>
<td align="center" valign="top">15,097</td>
<td align="center" valign="top">4,825</td>
<td align="center" valign="top">28.9% (18.9&#x2013;40.1)</td>
<td align="center" valign="top">4,944.07</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.4%</td>
<td align="center" valign="top">0.5177</td>
<td align="center" valign="top">&#x2212;0.0611 (&#x2212;0.2462 to 0.1240)</td>
</tr>
<tr>
<td align="left" valign="top">100&#x2013;150</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">7,757</td>
<td align="center" valign="top">3,306</td>
<td align="center" valign="top">28.5% (11.9&#x2013;48.9)</td>
<td align="center" valign="top">1,633.49</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">150&#x2013;200</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">4,762</td>
<td align="center" valign="top">2,596</td>
<td align="center" valign="top">63.7% (17.1&#x2013;98.1)</td>
<td align="center" valign="top">657.45</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.4%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">200&#x2013;350</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">1,935</td>
<td align="center" valign="top">984</td>
<td align="center" valign="top">33.2% (13.8&#x2013;56.1)</td>
<td align="center" valign="top">100.46</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Humidity</td>
</tr>
<tr>
<td align="left" valign="top">40&#x2013;65</td>
<td align="center" valign="top">17</td>
<td align="center" valign="top">7,861</td>
<td align="center" valign="top">2,025</td>
<td align="center" valign="top">12.4% (4.5&#x2013;23.2)</td>
<td align="center" valign="top">4,376.41</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">65&#x2013;70</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">25,885</td>
<td align="center" valign="top">760</td>
<td align="center" valign="top">23.6% (12.3&#x2013;37.2)</td>
<td align="center" valign="top">242.76</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">97.5%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">70&#x2013;85</td>
<td align="center" valign="top">32</td>
<td align="center" valign="top">22,244</td>
<td align="center" valign="top">10,445</td>
<td align="center" valign="top">45.1% (33.9&#x2013;56.6)</td>
<td align="center" valign="top">3,785.25</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.2%</td>
<td align="center" valign="top">&#x003C;0.0001</td>
<td align="center" valign="top">0.3318 (0.1685&#x2013;0.4952)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Minimum annual temperature</td>
</tr>
<tr>
<td align="left" valign="top">&#x2212;10 to 0</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">958</td>
<td align="center" valign="top">98</td>
<td align="center" valign="top">10.1% (8.2&#x2013;12.1)</td>
<td align="center" valign="top">0.1</td>
<td align="center" valign="top">0.75</td>
<td align="center" valign="top">0.0%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">0&#x2013;10</td>
<td align="center" valign="top">15</td>
<td align="center" valign="top">7,166</td>
<td align="center" valign="top">2,097</td>
<td align="center" valign="top">14.4% (5.4&#x2013;26.6)</td>
<td align="center" valign="top">3,680.14</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td align="center" valign="top">0.0047</td>
<td align="center" valign="top">&#x2212;0.2791 (&#x2212;0.4727 to &#x2212;0.0855)</td>
</tr>
<tr>
<td align="left" valign="top">10&#x2013;20</td>
<td align="center" valign="top">31</td>
<td align="center" valign="top">17,406</td>
<td align="center" valign="top">7,328</td>
<td align="center" valign="top">39.3% (28.6&#x2013;50.5)</td>
<td align="center" valign="top">4,278.96</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.3%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">20&#x2013;30</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">7,160</td>
<td align="center" valign="top">2,876</td>
<td align="center" valign="top">43.5% (16.9&#x2013;72.2)</td>
<td align="center" valign="top">809.32</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.1%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Maximum annual temperature</td>
</tr>
<tr>
<td align="left" valign="top">0&#x2013;10</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">1,622</td>
<td align="center" valign="top">480</td>
<td align="center" valign="top">20.4% (5.0&#x2013;42.5)</td>
<td align="center" valign="top">20.94</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">95.2%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">10&#x2013;20</td>
<td align="center" valign="top">22</td>
<td align="center" valign="top">12,530</td>
<td align="center" valign="top">4,533</td>
<td align="center" valign="top">20.0% (10.2&#x2013;32.0)</td>
<td align="center" valign="top">5,056.62</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">20&#x2013;30</td>
<td align="center" valign="top">32</td>
<td align="center" valign="top">18,538</td>
<td align="center" valign="top">8,217</td>
<td align="center" valign="top">40.7% (29.2&#x2013;52.6)</td>
<td align="center" valign="top">4,967.92</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.4%</td>
<td align="center" valign="top">0.0116</td>
<td align="center" valign="top">0.2264 (0.0506&#x2013;0.4022)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Average annual temperature</td>
</tr>
<tr>
<td align="left" valign="top">0&#x2013;10</td>
<td align="center" valign="top">14</td>
<td align="center" valign="top">7,691</td>
<td align="center" valign="top">2,118</td>
<td align="center" valign="top">14.8% (5.7&#x2013;27.2)</td>
<td align="center" valign="top">3,701.81</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.6%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">10&#x2013;15</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">3,931</td>
<td align="center" valign="top">1,671</td>
<td align="center" valign="top">24.1% (4.6&#x2013;52.3)</td>
<td align="center" valign="top">328.44</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.8%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">15&#x2013;20</td>
<td align="center" valign="top">25</td>
<td align="center" valign="top">10,361</td>
<td align="center" valign="top">3,469</td>
<td align="center" valign="top">32.9% (21.3&#x2013;45.7)</td>
<td align="center" valign="top">2,721.66</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.1%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">20&#x2013;25</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">10,707</td>
<td align="center" valign="top">5,972</td>
<td align="center" valign="top">53.7% (34.7&#x2013;72.2)</td>
<td align="center" valign="top">1,261.55</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.1%</td>
<td align="center" valign="top">0.0068</td>
<td align="center" valign="top">0.2897 (0.0797&#x2013;0.4998)</td>
</tr>
<tr>
<td align="left" valign="top" colspan="10">Climate</td>
</tr>
<tr>
<td align="left" valign="top">Oceanic subtropical monsoon climate</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">7,133</td>
<td align="center" valign="top">3,648</td>
<td align="center" valign="top">43.7% (21.7&#x2013;67.0)</td>
<td align="center" valign="top">404.63</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.3%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Plateau alpine climate</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">454</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">5.1% (3.2&#x2013;7.3)</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">&#x2013;</td>
<td align="center" valign="top">&#x2013;</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Subtropical mild monsoon climate</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">3,207</td>
<td align="center" valign="top">1,452</td>
<td align="center" valign="top">73.2% (25.9&#x2013;99.9)</td>
<td align="center" valign="top">263.54</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.2%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Subtropical monsoon climate</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">12,222</td>
<td align="center" valign="top">5,280</td>
<td align="center" valign="top">36.2% (26.1&#x2013;46.9)</td>
<td align="center" valign="top">2,770.30</td>
<td align="center" valign="top">0.00</td>
<td align="center" valign="top">99.2%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Temperate continental climate</td>
<td align="center" valign="top">3</td>
<td align="center" valign="top">1,944</td>
<td align="center" valign="top">1,395</td>
<td align="center" valign="top">57.2% (31.1&#x2013;81.3)</td>
<td align="center" valign="top">175.54</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.9%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Temperate continental monsoon climate</td>
<td align="center" valign="top">5</td>
<td align="center" valign="top">2,273</td>
<td align="center" valign="top">46</td>
<td align="center" valign="top">2.5% (0.2&#x2013;6.6)</td>
<td align="center" valign="top">30.50</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">86.9%</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Temperate monsoon climate</td>
<td align="center" valign="top">11</td>
<td align="center" valign="top">5,109</td>
<td align="center" valign="top">1,130</td>
<td align="center" valign="top">12.7% (5.7&#x2013;21.9)</td>
<td align="center" valign="top">818.47</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">98.8%</td>
<td align="center" valign="top">0.0110</td>
<td align="center" valign="top">&#x2212;0.2843 (&#x2212;0.5035 to &#x2212;0.0652)</td>
</tr>
<tr>
<td align="left" valign="top">Tropical monsoon Marine climate</td>
<td align="center" valign="top">2</td>
<td align="center" valign="top">348</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">66.9% (0.0&#x2013;100.0)</td>
<td align="center" valign="top">317.14</td>
<td align="center" valign="top">&#x003C;0.01</td>
<td align="center" valign="top">99.7%</td>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>CI&#x002A;: Confidence interval.</p>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="sec14">
<label>4</label>
<title>Discussion</title>
<p>Porcine JE is a zoonotic infectious disease, that affects both humans and animals. Geographically, it is endemic in regions in the Far East, South, and Southeast Asian countries (<xref ref-type="bibr" rid="ref46">46</xref>, <xref ref-type="bibr" rid="ref47">47</xref>) including South Korea, Thailand, Java (Indonesia), and the Primrosy region of Siberia (Russia), and in Kerala, and Haryana, India (<xref ref-type="bibr" rid="ref48">48</xref>, <xref ref-type="bibr" rid="ref49">49</xref>). Recently, cases of JE have also been reported in mainland Australia, Guam, and USA (<xref ref-type="bibr" rid="ref50">50</xref>). Surprisingly, the morbidity and mortality rates due to infection with JE have increased in China, except in Northern, Northeast China, Qinghai, Xinjiang, and Tibet. Meanwhile, the prevalence of <italic>JEV</italic> is rising globally in endemic areas, posing a serious threat to public health and the livestock industry (<xref ref-type="bibr" rid="ref51">51</xref>). Pigs are intermediate hosts for the <italic>JEV</italic>, whereas humans are the final hosts, and the infected carrier pigs are the primary source of transmission. Clinically, the disease leads to abortion, stillbirth, mummified fetuses in sows, and testicular inflammation in boars (<xref ref-type="bibr" rid="ref25">25</xref>). This is clearly reflecting the expanding range of the disease&#x2019;s endemicity, and posing a growing public health concern (<xref ref-type="bibr" rid="ref32">32</xref>).</p>
<p>To our knowledge, this is the first meta-analysis on the prevalence of porcine JE in China. The findings of this study could inform actionable control measures to improve animal husbandry practices. The analysis of the obtained results revealed, significant variations in the prevalence of JE in pigs across regions, sampling periods, and breeding practices (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). The national swine population showed an overall prevalence rate of 35.2% for JE (<xref ref-type="table" rid="tab2">Table 2</xref>). At the regional level, the South China showed a high significant (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) prevalence (43.8, 95% CI: 21.6&#x2013;67.4; <xref ref-type="table" rid="tab2">Table 2</xref>) compared to the other regions (<xref ref-type="table" rid="tab2">Table 2</xref>). Also, Jiangxi Province had the highest prevalence, followed by Chongqing Municipality (<xref ref-type="table" rid="tab2">Table 2</xref>). Both provinces are located within the subtropical monsoon climate zone, and characterized by hot summers, mild winters, four distinct seasons, and a well-developed monsoon pattern, all of which are likely to influence the spreading of the disease. Numerous analyses have indicated that the incidence of <italic>JEV</italic> infection has a seasonal pattern and closely related to geographical distribution, and climate (<xref ref-type="bibr" rid="ref19">19</xref>). Study in southwest China found significant associations between JE incidence and agricultural and climatic variables, including monthly precipitation and monthly mean minimum and maximum temperatures (<xref ref-type="bibr" rid="ref52">52</xref>). This climate provides favorable conditions for its spread. The region&#x2019;s average annual temperature ranges from 20&#x00B0;C to 25&#x00B0;C. This warm climate promotes the reproduction and transmission of vector organisms, such as mosquitoes. Consequently, swine populations in the subtropical region face a higher risk of infection, leading to elevated prevalence rates. Furthermore, the higher elevations, cold and arid climate, and low annual precipitation in the western region are unfavorable conditions for mosquito survival and reproduction, leading to weaker transmission of JE. Meanwhile, the low elevation, abundant plains, high precipitation, and vegetation of South China create optimal conditions for mosquito proliferation, thereby facilitating the local spreading of <italic>JEV</italic> (<xref ref-type="bibr" rid="ref53 ref54 ref55">53&#x2013;55</xref>).</p>
<p>The prevalence of JE between 2010 and 2015 was 63.4%, that was higher than in other periods. A total of 858 pig serum samples from both large-scale and rural free-range farms in Longyan City, Fujian Province, were tested for <italic>JEV</italic> antibody levels between 2011 and 2014. The elevated JE prevalence from 2010 to 2015 was influenced by several factors. A substantial research has consistently demonstrated a significant positive correlation between increasing temperatures and both the proliferation of mosquito populations and elevated incidence of mosquito-borne diseases (<xref ref-type="bibr" rid="ref56">56</xref>). Average annual precipitation of 100&#x2013;150 millimeters and temperatures between 15 and 20&#x00B0;C fostered mosquito proliferation, correlated positively with JE incidence and leading to a rise in in infected cases. Distinct climatic subtypes within temperate regions showed varying JE prevalence patterns. In Gansu Province, China, the cases appeared in a temperate arid climate, indicating a possible spread to new areas (<xref ref-type="bibr" rid="ref57">57</xref>). In temperate zones, the disease transmission is typically epidemic and seasonal, with most cases occurring during summer months (<xref ref-type="bibr" rid="ref58">58</xref>). This contrasts with subtropical and tropical regions where transmission can occur year-round, peaking during the rainy season (<xref ref-type="bibr" rid="ref58">58</xref>). The seasonal nature of JE in temperate areas limits the overall prevalence compared to regions with continuous transmission (<xref ref-type="bibr" rid="ref59">59</xref>). Serological testing revealed that, the prevalence of <italic>JEV</italic> in immunized pigs from large-scale and free-range farms were 72.17 and 57.72%, respectively. In comparison, the seropositivity rate in immunized pigs was 69.71%, slightly higher than the 68.89% in unimmunized pigs (<xref ref-type="bibr" rid="ref60">60</xref>). Significant differences were observed between the two cases, and due to the divergent objectives of the studies, investigations involving immunized pigs were excluded from our analysis, while only studies utilizing non-immunized pigs were included. The JE remains a serious concern in Fujian Province and requires continued attention. One of the included articles showed that, 78 porcine <italic>JEV</italic> nucleic acids were detected in 263 samples collected from 14 different swine farms in the south from 2011 to 2018, with a positivity rate of 29.7% (<xref ref-type="bibr" rid="ref61">61</xref>). The emergence of this cause may be due to the location in the tropics and subtropics, where the warm and humid climate, the high density of mosquitoes, and the large number of domestic pigs provide the natural conditions for the spread and reproduction of <italic>JEV</italic> (<xref ref-type="bibr" rid="ref22">22</xref>).</p>
<p>Various methods have been used in epidemiological studies of <italic>JEV</italic>, including virus isolation, RT-PCR, RT-qPCR, and microdroplet digital PCR (ddPCR) (<xref ref-type="bibr" rid="ref13">13</xref>). Virus isolation is a time-consuming, labor-intensive process that often taking over a week to complete, this limits its use in large-scale epidemiologic investigations. The serum neutralization test (SNT) is the standard method for serological detection of <italic>JEV</italic>, but cross-reactivity between the different <italic>flaviviruses</italic> within the same genus was recorded using this tool which reflects the inaccurate results (<xref ref-type="bibr" rid="ref62">62</xref>). On the other side, the previously mentioned molecular techniques usually take 2&#x2013;3&#x202F;h for completion (<xref ref-type="bibr" rid="ref63 ref64 ref65">63&#x2013;65</xref>). False positivity varies depending on the used tools and could affect the accurate estimation of the disease prevalence. Accordingly, four major detection methods for JE were usually applied including; ELISA, PCR, RT-RAA, and LAT. ELISA is a fundamental technique in immunology and molecular biology, utilizing antigen&#x2013;antibody binding with enzymatic and colorimetric assays for quantitative analysis of target molecules. It detects and quantifies specific proteins, peptides, antibodies, or antigens in biological samples, making it essential in research and diagnostics (<xref ref-type="bibr" rid="ref66">66</xref>). This technique is extensively used to detect antibodies and antigens for diagnosing and <italic>JEV</italic> monitoring but is prone to cross-reactivity with other flaviviruses like <italic>yellow fever virus</italic>, which can lead to false results and affect prevalence estimates. To address this issue more effectively, it is suggested to develop more specific detection methods for antigen, including secondary screening alongside PCR assays or alternative immunological detection techniques in future studies to mitigate the impact of cross-reactivity. PCR utilizes the semi-conservative replication of DNA for <italic>in vitro</italic> enzymatic synthesis and amplification of specific nucleic acid sequences. The specificity of this technique is achieved through the utilization of oligonucleotide primers complementary to the flanking regions of the target sequence (<xref ref-type="bibr" rid="ref67">67</xref>). RT-PCR involves the conversion of mRNA into cDNA utilizing reverse transcriptase, which subsequently serves as the template for amplifying the target fragment. The RNA template employed in this procedure may comprise total RNA, mRNA, or in vitro transcribed RNA (<xref ref-type="bibr" rid="ref68">68</xref>). LAT is an indirect agglutination assay using latex particles as carriers. Soluble antigens are adsorbed on these particles, allowing specific antibodies to bind and promote agglutination (<xref ref-type="bibr" rid="ref69">69</xref>). It was found that, ELISA was significantly (<italic>p</italic> =&#x202F;0.0056, <xref ref-type="table" rid="tab5">Table 5</xref>) the commonly used tool. It offers several advantages, including rapidity, high efficiency, low cost, specificity, high sensitivity, simplicity, and no need for high aseptic procedures. Also, it enables the simultaneous testing of multiple serum samples (<xref ref-type="bibr" rid="ref70">70</xref>). Given the large pig population, rapid turnover, and high infection rates of <italic>JEV</italic> in the country (<xref ref-type="bibr" rid="ref71">71</xref>), the specificity, reproducibility, and operational simplicity of ELISA render it an optimal method for the detection of porcine JE antibodies due to infection adding to the evaluation of antibody titers following immunization (<xref ref-type="bibr" rid="ref70">70</xref>). It is noteworthy that, some studies did not explain whether the pigs had been immunized with swine JE vaccine or not. So, false-positive results contribute to heterogeneity in the results (<xref ref-type="bibr" rid="ref72">72</xref>).</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Included studies of Japanese encephalitis of swine in Mainland China.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Reference ID</th>
<th align="center" valign="top">Sampling time</th>
<th align="left" valign="top">Detection method</th>
<th align="center" valign="top">No. tested</th>
<th align="center" valign="top">No. positive</th>
<th align="center" valign="top">Prevalence</th>
<th align="left" valign="top">Study design</th>
<th align="center" valign="top">Score</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="8">Central China</td>
</tr>
<tr>
<td align="left" valign="top">Tang et al. (2022)</td>
<td align="center" valign="bottom">2019&#x2013;2021</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">3,026</td>
<td align="center" valign="top">583</td>
<td align="center" valign="top">0.192664</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Cui (2009)</td>
<td align="center" valign="bottom">2008&#x2013;2009</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">801</td>
<td align="center" valign="top">384</td>
<td align="center" valign="top">0.4794</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Chai et al. (2018)</td>
<td align="center" valign="bottom">2006&#x2013;2012</td>
<td align="left" valign="bottom">UN</td>
<td align="center" valign="top">2,597</td>
<td align="center" valign="top">1,575</td>
<td align="center" valign="top">0.606469</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">2</td>
</tr>
<tr>
<td align="left" valign="top">Chen and Wei (2010)</td>
<td align="center" valign="bottom">2007.6&#x2013;2008.9</td>
<td align="left" valign="bottom">RT-PCR</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">0.043478261</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">4</td>
</tr>
<tr>
<td align="left" valign="top">Jiang et al. (2010)</td>
<td align="center" valign="bottom">2008&#x2013;2009</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">216</td>
<td align="center" valign="top">144</td>
<td align="center" valign="top">0.6666667</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top" colspan="8">East China</td>
</tr>
<tr>
<td align="left" valign="top">Fan et al. (2014)</td>
<td align="center" valign="bottom">2014</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">564</td>
<td align="center" valign="top">283</td>
<td align="center" valign="top">0.501773</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Zhao et al. (2023)</td>
<td align="center" valign="bottom">2016&#x2013;2020</td>
<td align="left" valign="bottom">PCR</td>
<td align="center" valign="top">832</td>
<td align="center" valign="top">14</td>
<td align="center" valign="top">0.016827</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Li et al. (2018)</td>
<td align="center" valign="bottom">2011&#x2013;2014</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">135</td>
<td align="center" valign="top">93</td>
<td align="center" valign="top">0.6888889</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Li et al. (2009)</td>
<td align="center" valign="bottom">2006&#x2013;2007</td>
<td align="left" valign="bottom">Other</td>
<td align="center" valign="top">152</td>
<td align="center" valign="top">33</td>
<td align="center" valign="top">0.217105</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top" colspan="8">North China</td>
</tr>
<tr>
<td align="left" valign="top">Jin et al. (2008)</td>
<td align="center" valign="top">2006.7</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">172</td>
<td align="center" valign="top">13</td>
<td align="center" valign="top">0.075581395</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Guo et al. (2019)</td>
<td align="center" valign="bottom">2015&#x2013;2016</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">88</td>
<td align="center" valign="top">11</td>
<td align="center" valign="top">0.065868263</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Chai et al. (2018)</td>
<td align="center" valign="bottom">2006&#x2013;2012</td>
<td align="left" valign="bottom">UN</td>
<td align="center" valign="top">365</td>
<td align="center" valign="top">35</td>
<td align="center" valign="top">0.09589</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">2</td>
</tr>
<tr>
<td align="left" valign="top" colspan="8">Northeast China</td>
</tr>
<tr>
<td align="left" valign="top">Zhao et al. (2023)</td>
<td align="center" valign="bottom">2016&#x2013;2020</td>
<td align="left" valign="bottom">PCR</td>
<td align="center" valign="top">1,043</td>
<td align="center" valign="top">29</td>
<td align="center" valign="top">0.027804</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Sun et al. (2012)</td>
<td align="center" valign="bottom">1997&#x2013;2000</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">866</td>
<td align="center" valign="top">88</td>
<td align="center" valign="top">0.101616628</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">4</td>
</tr>
<tr>
<td align="left" valign="top">Guo et al. (2019)</td>
<td align="center" valign="bottom">2015&#x2013;2016</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">79</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Zhang and Lu (2011)</td>
<td align="center" valign="bottom">2006&#x2013;2009</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">2,161</td>
<td align="center" valign="top">592</td>
<td align="center" valign="top">0.273947247</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top" colspan="8">Northwest China</td>
</tr>
<tr>
<td align="left" valign="top">Fan et al. (2014)</td>
<td align="center" valign="bottom">2014</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">188</td>
<td align="center" valign="top">64</td>
<td align="center" valign="top">0.340425532</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Yao et al. (2022)</td>
<td align="center" valign="top">UN</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">1,523</td>
<td align="center" valign="top">1,199</td>
<td align="center" valign="top">0.787261983</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">2</td>
</tr>
<tr>
<td align="left" valign="top">Zhao et al. (2023)</td>
<td align="center" valign="bottom">2016&#x2013;2020</td>
<td align="left" valign="bottom">PCR</td>
<td align="center" valign="top">952</td>
<td align="center" valign="top">9</td>
<td align="center" valign="top">0.009453782</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Jiang and Liu (2007)</td>
<td align="center" valign="top">2006</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">233</td>
<td align="center" valign="top">132</td>
<td align="center" valign="top">0.566523605</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">4</td>
</tr>
<tr>
<td align="left" valign="top" colspan="8">Southern China</td>
</tr>
<tr>
<td align="left" valign="top">Fan et al. (2014)</td>
<td align="center" valign="bottom">2014</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">304</td>
<td align="center" valign="top">108</td>
<td align="center" valign="top">0.355263158</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Huang et al. (2012)</td>
<td align="center" valign="top">2009&#x2013;2011</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">4,282</td>
<td align="center" valign="top">2,227</td>
<td align="center" valign="top">0.520084073</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Ma et al. (2020)</td>
<td align="center" valign="top">2013</td>
<td align="left" valign="bottom">ELISA</td>
<td align="center" valign="top">465</td>
<td align="center" valign="top">445</td>
<td align="center" valign="top">0.956989247</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Zhao et al. (2023)</td>
<td align="center" valign="bottom">2016&#x2013;2020</td>
<td align="left" valign="bottom">PCR</td>
<td align="center" valign="top">278</td>
<td align="center" valign="top">8</td>
<td align="center" valign="top">0.028776978</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Liu et al. (2006)</td>
<td align="center" valign="top">2002&#x2013;2003</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">86</td>
<td align="center" valign="top">21</td>
<td align="center" valign="top">0.244186047</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">2</td>
</tr>
<tr>
<td align="left" valign="top">Chen et al. (2000)</td>
<td align="center" valign="top">2000</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">149</td>
<td align="center" valign="top">41</td>
<td align="center" valign="top">0.275167785</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">2</td>
</tr>
<tr>
<td align="left" valign="top">Qin and He (2011)</td>
<td align="center" valign="top">2008&#x2013;2010</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">2,597</td>
<td align="center" valign="top">1,575</td>
<td align="center" valign="top">0.606469003</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Li et al. (2010)</td>
<td align="center" valign="top">2008&#x2013;2009</td>
<td align="left" valign="bottom">RT-PCR</td>
<td align="center" valign="top">1,676</td>
<td align="center" valign="top">923</td>
<td align="center" valign="top">0.55071599</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">4</td>
</tr>
<tr>
<td align="left" valign="top" colspan="8">Southwest China</td>
</tr>
<tr>
<td align="left" valign="top">Hua and Li (2012)</td>
<td align="center" valign="top">UN</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">2,906</td>
<td align="center" valign="top">1,239</td>
<td align="center" valign="top">0.426359257</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">2</td>
</tr>
<tr>
<td align="left" valign="top">Yang et al. (2013)</td>
<td align="center" valign="top">2010&#x2013;2012</td>
<td align="left" valign="bottom">LAT</td>
<td align="center" valign="top">135</td>
<td align="center" valign="top">67</td>
<td align="center" valign="top">0.496296296</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="bottom">3</td>
</tr>
<tr>
<td align="left" valign="top">Zhou (2011)</td>
<td align="center" valign="top">UN</td>
<td align="left" valign="top">LAT</td>
<td align="center" valign="top">274</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">0.04379562</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">2</td>
</tr>
<tr>
<td align="left" valign="top">Liu et al. (2007)</td>
<td align="center" valign="top">2002&#x2013;2006</td>
<td align="left" valign="top">ELISA</td>
<td align="center" valign="top">592</td>
<td align="center" valign="top">194</td>
<td align="center" valign="top">0.327702703</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">3</td>
</tr>
<tr>
<td align="left" valign="top">Yang et al. (2008)</td>
<td align="center" valign="top">2005&#x2013;2007</td>
<td align="left" valign="top">LAT</td>
<td align="center" valign="top">2,292</td>
<td align="center" valign="top">1,105</td>
<td align="center" valign="top">0.482111693</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">3</td>
</tr>
<tr>
<td align="left" valign="top">Zhang et al. (2017)</td>
<td align="center" valign="top">UN</td>
<td align="left" valign="top">ELISA</td>
<td align="center" valign="top">454</td>
<td align="center" valign="top">23</td>
<td align="center" valign="top">0.050660793</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">2</td>
</tr>
<tr>
<td align="left" valign="top">Nie et al. (2022)</td>
<td align="center" valign="top">2020&#x2013;2021</td>
<td align="left" valign="top">RT-RAA</td>
<td align="center" valign="top">185</td>
<td align="center" valign="top">12</td>
<td align="center" valign="top">0.064864865</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">3</td>
</tr>
<tr>
<td align="left" valign="top">Liu et al. (2013)</td>
<td align="center" valign="top">2009&#x2013;2010</td>
<td align="left" valign="top">RT-PCR</td>
<td align="center" valign="top">108</td>
<td align="center" valign="top">20</td>
<td align="center" valign="top">0.185185185</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">3</td>
</tr>
<tr>
<td align="left" valign="top">Ceng and Chen (2011)</td>
<td align="center" valign="top">2010</td>
<td align="left" valign="top">ELISA</td>
<td align="center" valign="top">592</td>
<td align="center" valign="top">355</td>
<td align="center" valign="top">0.599662162</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">3</td>
</tr>
<tr>
<td align="left" valign="top">Wu et al. (2024)</td>
<td align="center" valign="top">2007&#x2013;2008</td>
<td align="left" valign="top">ELISA</td>
<td align="center" valign="top">486</td>
<td align="center" valign="top">124</td>
<td align="center" valign="top">0.255144033</td>
<td align="left" valign="top">Cross sectional</td>
<td align="center" valign="top">4</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>UN&#x002A;: unclear.</p>
<p>LAT&#x002A;: Latex agglutination test.</p>
<p>RT-PCR&#x002A;: Reverse Transcription-Polymerase Chain Reaction.</p>
<p>RT-RAA&#x002A;: Reverse Transcription Recombinase Aided Amplification.</p>
<p>PCR&#x002A;: Polymerase Chain Reaction.</p>
<p>ELISA&#x002A;: Enzyme linked immunosorbent assay.</p>
</table-wrap-foot>
</table-wrap>
<p>It was recorded that; Pigs are one of the main hosts of <italic>JEV</italic> (<xref ref-type="bibr" rid="ref73">73</xref>, <xref ref-type="bibr" rid="ref74">74</xref>). The prolonged viremia in the blood of pigs infected with the <italic>JEV</italic>, characterized by high viral loads and infectiousness, which could be the main source of human infection (<xref ref-type="bibr" rid="ref35">35</xref>). Once the virus enters the host, it rapidly invades the bloodstream and replicates in internal organs such as (heart, liver, spleen, kidneys), causing brief viremia that lasts 3&#x2013;7&#x202F;days. The virus can cross the blood&#x2013;brain barrier, invade the central nervous system, and replicate in brain tissue, causing lesions and neurological symptoms (<xref ref-type="bibr" rid="ref75">75</xref>, <xref ref-type="bibr" rid="ref76">76</xref>). In the present study, our analysis of various sample types showed that serum had a higher detected prevalence compared to other tissues. Analysis of <italic>JEV</italic> serum data from Chinese swine herds showed that the prevalence and distribution of <italic>JEV</italic> in pigs also exhibited seasonal and geographic variation; <italic>JEV</italic> infections appeared 1&#x2013;2&#x202F;months earlier in southern China than in northern parts (<xref ref-type="bibr" rid="ref26">26</xref>). These characteristics not only allow pigs to play an important role in the <italic>JEV</italic> transmission chain, but also provide a warning to the public health community that pigs are potential reservoirs of viruses that may directly or indirectly infect humans, especially if they have high viral loads in their blood with the ability to cross the blood&#x2013;brain barrier, enter the central nervous system and replicate in brain tissue (<xref ref-type="bibr" rid="ref77">77</xref>), causing neurological lesions that lead to clinical manifestations such as neurological symptoms, meningitis, encephalitis, and other serious diseases (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref78">78</xref>).</p>
<p>Immunization greatly affects disease incidence in pig populations. Significant emphasis was placed on rigorous screening of unvaccinated pig herds, excluding articles that did not specify immunized populations and antibody protection rates. All included studies came from large-scale farms and free-range herds with unvaccinated pigs. According to the World Health Organization, the vaccine currently used for JE is the SA14-14-2 strain (<xref ref-type="bibr" rid="ref79">79</xref>), and studies have shown vaccine efficacy to be between 80 and 99% after a single dose and 98% or higher after two doses (<xref ref-type="bibr" rid="ref80">80</xref>). Therefore, for studies that did not explicitly state whether the subjects had been vaccinated, when the seropositive rate of pigs exceeded 90%, we considered the herd to be immune. For studies that did not explicitly state whether subjects had been immunized, we assumed that the seropositivity rate among pigs exceeded 90%, as vaccinated pigs generate antibodies, resulting in a higher antibody positivity rate. Through rigorous screening, we minimized immune factor confounding to accurately analyze the JE prevalence.</p>
<p>Surprisingly, the infection rate was higher in winter than in other seasons, though the difference was not statistically significant (<xref ref-type="table" rid="tab2">Table 2</xref>). The incidence and prevalence of the disease show clear seasonality, typically peaking from July to September, then sharply declining after October. The disease is usually sporadic but can also become endemic (<xref ref-type="bibr" rid="ref14">14</xref>). In our study, the phenomenon of higher prevalence in winter may be related to the regions included in the study. Especially in Hainan, Guangdong, and Yunnan provinces, which have warmer climates with insignificant seasonal variations, mosquitoes are active throughout the year. Therefore, even in winter, the mosquito population remains high, leading to higher infection rates in that season, which in turn may have influenced the bias of the study results. This disease peaks in prevalence during China&#x2019;s rainy summer and autumn. Epidemic peaks occur from June to July in southern regions, from July to August in northern regions, and from August to September in northeastern regions. For instance, irrigated rice fields provide ideal breeding grounds for Culex tritaeniorhynchus, the primary vector for <italic>JEV</italic> transmission (<xref ref-type="bibr" rid="ref81">81</xref>). Variations in environmental conditions and temperatures affect mosquito activity, leading to distinct disease transmission patterns across different areas (<xref ref-type="bibr" rid="ref82">82</xref>). The increased precipitation during the summer and fall seasons creates more favorable breeding conditions for mosquitoes, resulting in a substantial increase in both of their population density and activity levels (<xref ref-type="bibr" rid="ref57">57</xref>). As a consequence, this exacerbates the transmission of <italic>JEV</italic>. In areas with intensive rice farming and pig production, JE transmission is likely to increase due to the creation of suitable environments for vector mosquitoes and amplifying hosts (<xref ref-type="bibr" rid="ref19">19</xref>). Studies indicate that tropical regions lack seasonality, allowing the disease to occur year-round (<xref ref-type="bibr" rid="ref83">83</xref>). Interestingly, the same observation of high incidence rate was recorded in winter compared to the other seasons but with a different insect-born pathogen (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref11">11</xref>).</p>
<p>The epidemiology of porcine JE is mainly driven by mosquito as the primary virus vector (<xref ref-type="bibr" rid="ref84">84</xref>). It has a well-defined transmission route, mainly through mosquito bites, so mosquito control is a key measure to prevent disease transmission. In areas where the climate is more stable and mosquitoes are active throughout the year, especially in tropical and subtropical areas, prevention and control strategies for epidemics should focus on strengthening herd management and immunization (<xref ref-type="bibr" rid="ref15">15</xref>). However, swine JE lacks specific antiviral treatments, so management relies on supportive care and immune enhancement. Prevention involves immunization, vector control, and managing pig populations (<xref ref-type="bibr" rid="ref85">85</xref>). Live <italic>JEV</italic> vaccines are recommended in endemic or high-risk regions. Since JE transmission is linked to blood-feeding arthropods like mosquitoes, controlling these vectors by the different tools is crucial for prevention (<xref ref-type="bibr" rid="ref86">86</xref>).</p>
<p>Our meta-analysis included five studies with quality scores of 4 or 5, 26 studies with scores of 2 or 3, and none with scores of 0 or 1. Our review for the moderate-quality studies revealed that several detailed descriptions of seasons, random sampling methods, and sampling procedures were lacked. Neglecting of seasonal factors may lead to seasonal bias in epidemiologic results, especially for those diseases that are strongly influenced by climatic and environmental changes, and the lack of seasonal descriptions will limit the accuracy and extrapolation of results. Lack of random sampling or poor description may then lead to sample selection bias, making the results of the study unable to truly reflect the characteristics of the target group, thus affecting the reliability and scientific value of the results. In addition, unclear details of the sampling method may lead to reduced comparability across studies, thus affecting the accuracy of meta-analyses. Therefore, it is recommended that, future researchers in the future should cover these shortages to improve the reliability of their findings. This study used regression analysis to investigate factors affecting JE spreading, identifying a significant correlation between sample size and JE prevalence. However, the analyses did not account for all potential confounding variables. Future research should include more covariates to improve generalizability and establish stronger causal relationships.</p>
<p>This meta-analysis has several strengths, including a broad temporal range, extensive geographic coverage, and well-defined analytical methods, but also some limitations were present. Firstly, the selected articles were limited to Chinese or English, potentially excluding relevant studies in other languages. Secondly, the articles were sourced from six databases only, which may have excluded relevant studies from other sources. Lastly, the study concentrates on specific Chinese provinces, underrepresenting regions like Qinghai, Tibet, and Xinjiang. This limited representation may impact findings and compromise external validity and robustness. Future studies should adopt a more comprehensive sampling approach, especially in underrepresented western provinces, to better assess national prevalence.</p>
</sec>
<sec sec-type="conclusions" id="sec15">
<label>5</label>
<title>Conclusion</title>
<p>The current meta-analysis showed that the prevalence of JE infection in swine is widely distributed across China. Additionally, the disease is more prevalent in regions with consistently hot and humid climates. Thus, we recommend continuous surveillance of swine populations and implementing isolation measures to reduce mosquito contact with herds. Furthermore, awareness of JE should be raised in regions where the disease receives less attention, and epidemiological investigations should be promptly conducted to ensure timely control of its spread. The high prevalence of this disease swine can cause significant economic losses for farmers and herdsmen adding to increasing the risk of infection. Therefore, attention to animal welfare and application of all precaution measures to limit the spread of JE is crucial for intensive pig farming. This study lays a foundation for future research on strategies to control JE.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec16">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors without undue reservation.</p>
</sec>
<sec sec-type="author-contributions" id="sec17">
<title>Author contributions</title>
<p>X-TL: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing, Software, Visualization. L-DJ: Data curation, Writing &#x2013; review &#x0026; editing, Formal analysis. Y-TL: Data curation, Writing &#x2013; review &#x0026; editing, Formal analysis. RZ: Formal analysis, Writing &#x2013; review &#x0026; editing. QW: Methodology, Writing &#x2013; review &#x0026; editing, Visualization. S-YZ: Conceptualization, Funding acquisition, Writing &#x2013; review &#x0026; editing. EA: Writing &#x2013; review &#x0026; editing, Investigation. XiL: Investigation, Writing &#x2013; review &#x0026; editing. YW: Investigation, Writing &#x2013; review &#x0026; editing. Z-XL: Investigation, Writing &#x2013; review &#x0026; editing. CX: Investigation, Writing &#x2013; review &#x0026; editing. YX: Investigation, Writing &#x2013; review &#x0026; editing. Y-FW: Investigation, Writing &#x2013; review &#x0026; editing. XuL: Writing &#x2013; review &#x0026; editing, Investigation, Supervision. Q-LG: Conceptualization, Writing &#x2013; review &#x0026; editing, Methodology, Software. RD: Conceptualization, Funding acquisition, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec18">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was financially supported by Jilin Province Science and Technology Development Project (20240304190SF).</p>
</sec>
<sec sec-type="COI-statement" id="sec19">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec20">
<title>Generative AI statement</title>
<p>The authors declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="sec21">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec22">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fvets.2025.1534114/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fvets.2025.1534114/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Supplementary_file_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<ref-list>
<title>References</title>
<ref id="ref1"><label>1.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Niu</surname> <given-names>TM</given-names></name> <name><surname>Yu</surname> <given-names>LJ</given-names></name> <name><surname>Zhao</surname> <given-names>JH</given-names></name> <name><surname>Zhang</surname> <given-names>RR</given-names></name> <name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Wang</surname> <given-names>N</given-names></name> <etal/></person-group>. <article-title>Characterization and pathogenicity of the porcine epidemic diarrhea virus isolated in China</article-title>. <source>Microb Pathog</source>. (<year>2023</year>) <volume>174</volume>:<fpage>105924</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.micpath.2022.105924</pub-id>, PMID: <pub-id pub-id-type="pmid">36473667</pub-id></citation></ref>
<ref id="ref2"><label>2.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Abdel-Aziz</surname> <given-names>TH</given-names></name> <name><surname>Abdel-Ghany</surname> <given-names>HSM</given-names></name> <name><surname>Elsawy</surname> <given-names>BSM</given-names></name> <name><surname>Abdullah</surname> <given-names>H</given-names></name> <name><surname>Abouelsoued</surname> <given-names>D</given-names></name> <etal/></person-group>. <article-title>Molecular and serological diagnosis of the circulating Trypanosoma evansi in Egyptian livestock with risk factors assessment</article-title>. <source>Microb Pathog</source>. (<year>2024</year>) <volume>197</volume>:<fpage>107073</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.micpath.2024.107073</pub-id></citation></ref>
<ref id="ref3"><label>3.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Kasem</surname> <given-names>S</given-names></name> <name><surname>Yu</surname> <given-names>MHH</given-names></name> <name><surname>Alkhalefa</surname> <given-names>N</given-names></name> <name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Nayel</surname> <given-names>M</given-names></name> <name><surname>Abdo</surname> <given-names>W</given-names></name> <etal/></person-group>. <article-title>Impact of equine herpesvirus-1 ORF15 (Eul45) on viral replication and neurovirulence</article-title>. <source>Vet Microbiol</source>. (<year>2024</year>) <volume>298</volume>:<fpage>110234</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.vetmic.2024.110234</pub-id>, PMID: <pub-id pub-id-type="pmid">39180797</pub-id></citation></ref>
<ref id="ref4"><label>4.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ibrahim</surname> <given-names>HS</given-names></name> <name><surname>Alsenosy</surname> <given-names>AA</given-names></name> <name><surname>El-Ktany</surname> <given-names>EM</given-names></name> <name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Abas</surname> <given-names>OM</given-names></name></person-group>. <article-title>Anthelmintic efficacy and pharmacodynamic effects of levamisole-oxyclozanide combination as (Levanide&#x00AE;) in fattening calves</article-title>. <source>Egypt J Vet Sci</source>. (<year>2023</year>) <volume>54</volume>:<fpage>1245</fpage>&#x2013;<lpage>54</lpage>. doi: <pub-id pub-id-type="doi">10.21608/ejvs.2023.219811.1532</pub-id></citation></ref>
<ref id="ref5"><label>5.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shalaby</surname> <given-names>H</given-names></name> <name><surname>Kandil</surname> <given-names>O</given-names></name> <name><surname>Hendawy</surname> <given-names>S</given-names></name> <name><surname>Elsawy</surname> <given-names>BS</given-names></name> <name><surname>Ashry</surname> <given-names>HM</given-names></name> <name><surname>El-Namaky</surname> <given-names>A</given-names></name> <etal/></person-group>. <article-title>Dynamics of Haemonchus contortus coproantigen appearance in feces of experimentally infected sheep</article-title>. <source>Egypt J Vet Sci</source>. (<year>2024</year>) <volume>55</volume>:<fpage>1307</fpage>&#x2013;<lpage>14</lpage>. doi: <pub-id pub-id-type="doi">10.21608/ejvs.2024.251684.1693</pub-id></citation></ref>
<ref id="ref6"><label>6.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Li</surname> <given-names>ZJ</given-names></name> <name><surname>Shi</surname> <given-names>CW</given-names></name> <name><surname>Yang</surname> <given-names>GL</given-names></name> <name><surname>Yang</surname> <given-names>WT</given-names></name> <name><surname>Wang</surname> <given-names>CF</given-names></name></person-group>. <article-title>African swine fever virus: a raised global upsurge and a continuous threaten to pig husbandry</article-title>. <source>Microbe Pathog</source>. (<year>2022</year>) <volume>167</volume>:<fpage>105561</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.micpath.2022.105561</pub-id>, PMID: <pub-id pub-id-type="pmid">35526679</pub-id></citation></ref>
<ref id="ref7"><label>7.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hu</surname> <given-names>TY</given-names></name> <name><surname>Lian</surname> <given-names>YB</given-names></name> <name><surname>Qian</surname> <given-names>JH</given-names></name> <name><surname>Yang</surname> <given-names>YL</given-names></name> <name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Zhang</surname> <given-names>RR</given-names></name> <etal/></person-group>. <article-title>Immunogenicity of engineered probiotics expressing conserved antigens of influenza virus and FLIC flagellin against H9N2 AI infection in mice</article-title>. <source>Res Vet Sci</source>. (<year>2022</year>) <volume>153</volume>:<fpage>115</fpage>&#x2013;<lpage>26</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.rvsc.2022.10.024</pub-id>, PMID: <pub-id pub-id-type="pmid">36351352</pub-id></citation></ref>
<ref id="ref8"><label>8.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sha</surname> <given-names>W</given-names></name> <name><surname>Beshir Ata</surname> <given-names>E</given-names></name> <name><surname>Yan</surname> <given-names>M</given-names></name> <name><surname>Zhang</surname> <given-names>Z</given-names></name> <name><surname>Fan</surname> <given-names>H</given-names></name></person-group>. <article-title>Swine colibacillosis: analysis of the gut bacterial microbiome</article-title>. <source>Microorganisms</source>. (<year>2024</year>) <volume>12</volume>:<fpage>1233</fpage>. doi: <pub-id pub-id-type="doi">10.3390/microorganisms12061233</pub-id>, PMID: <pub-id pub-id-type="pmid">38930615</pub-id></citation></ref>
<ref id="ref9"><label>9.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Yang</surname> <given-names>W-T</given-names></name> <name><surname>Yang</surname> <given-names>W</given-names></name> <name><surname>Jin</surname> <given-names>Y-B</given-names></name> <name><surname>Ata</surname> <given-names>EB</given-names></name> <name><surname>Zhang</surname> <given-names>R-R</given-names></name> <name><surname>Huang</surname> <given-names>HB</given-names></name> <etal/></person-group>. <article-title>Synthesized swine influenza NS1 antigen provides a protective immunity in a mice model</article-title>. <source>J Vet Sci</source>. (<year>2020</year>) <volume>21</volume>:<fpage>e66</fpage>. doi: <pub-id pub-id-type="doi">10.4142/jvs.2020.21.e66</pub-id></citation></ref>
<ref id="ref10"><label>10.</label> <citation citation-type="book"><person-group person-group-type="author"><name><surname>Hao</surname> <given-names>Y</given-names></name> <name><surname>Sheng</surname> <given-names>K</given-names></name> <name><surname>Ruan</surname> <given-names>WK</given-names></name></person-group>. <source>Expression of non-structural proteins in Japanese encephalitis virus and their interaction with host hnRNP K in Chinese</source>. <publisher-name>College of Animal Science and Technology, Beijing University of Agriculture</publisher-name> (<year>2024</year>), <volume>39</volume>, <fpage>37</fpage>&#x2013;<lpage>42</lpage>. doi: <pub-id pub-id-type="doi">10.13473/j.cnki.issn.1002-3186.2024.0108</pub-id></citation></ref>
<ref id="ref11"><label>11.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ashraf</surname> <given-names>U</given-names></name> <name><surname>Ding</surname> <given-names>Z</given-names></name> <name><surname>Deng</surname> <given-names>S</given-names></name> <name><surname>Ye</surname> <given-names>J</given-names></name> <name><surname>Cao</surname> <given-names>S</given-names></name> <name><surname>Chen</surname> <given-names>Z</given-names></name></person-group>. <article-title>Pathogenicity and virulence of Japanese encephalitis virus: neuroinflammation and neuronal cell damage</article-title>. <source>Virulence</source>. (<year>2021</year>) <volume>12</volume>:<fpage>968</fpage>&#x2013;<lpage>80</lpage>. doi: <pub-id pub-id-type="doi">10.1080/21505594.2021.1899674</pub-id>, PMID: <pub-id pub-id-type="pmid">33724154</pub-id></citation></ref>
<ref id="ref12"><label>12.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname> <given-names>LP</given-names></name> <name><surname>Yuan</surname> <given-names>Y</given-names></name> <name><surname>Liu</surname> <given-names>YL</given-names></name> <name><surname>Lu</surname> <given-names>QB</given-names></name> <name><surname>Shi</surname> <given-names>LS</given-names></name> <name><surname>Ren</surname> <given-names>X</given-names></name> <etal/></person-group>. <article-title>Etiological and epidemiological features of acute meningitis or encephalitis in China: a nationwide active surveillance study</article-title>. <source>Lancet Reg Health West Pac</source>. (<year>2022</year>) <volume>20</volume>:<fpage>100361</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.lanwpc.2021.100361</pub-id>, PMID: <pub-id pub-id-type="pmid">35036977</pub-id></citation></ref>
<ref id="ref13"><label>13.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Nie</surname> <given-names>M</given-names></name> <name><surname>Zhou</surname> <given-names>Y</given-names></name> <name><surname>Li</surname> <given-names>F</given-names></name> <name><surname>Deng</surname> <given-names>H</given-names></name> <name><surname>Zhao</surname> <given-names>M</given-names></name> <name><surname>Huang</surname> <given-names>Y</given-names></name> <etal/></person-group>. <article-title>Epidemiological investigation of swine Japanese encephalitis virus based on RT-RAA detection method</article-title>. <source>Sci Rep</source>. (<year>2022</year>) <volume>12</volume>:<fpage>9392</fpage>. doi: <pub-id pub-id-type="doi">10.1038/s41598-022-13604-4</pub-id>, PMID: <pub-id pub-id-type="pmid">35672440</pub-id></citation></ref>
<ref id="ref14"><label>14.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>F</given-names></name> <name><surname>Li</surname> <given-names>H</given-names></name> <name><surname>Yang</surname> <given-names>L</given-names></name> <name><surname>Wang</surname> <given-names>L</given-names></name> <name><surname>Gu</surname> <given-names>L</given-names></name> <name><surname>Zhong</surname> <given-names>G</given-names></name> <etal/></person-group>. <article-title>The spatial-temporal pattern of Japanese encephalitis and its influencing factors in Guangxi, China</article-title>. <source>Infect Genet Evol</source>. (<year>2023</year>) <volume>111</volume>:<fpage>105433</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.meegid.2023.105433</pub-id>, PMID: <pub-id pub-id-type="pmid">37037290</pub-id></citation></ref>
<ref id="ref15"><label>15.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname> <given-names>Q</given-names></name> <name><surname>Yang</surname> <given-names>S</given-names></name> <name><surname>Yang</surname> <given-names>K</given-names></name> <name><surname>Li</surname> <given-names>X</given-names></name> <name><surname>Dai</surname> <given-names>Y</given-names></name> <name><surname>Zheng</surname> <given-names>Y</given-names></name> <etal/></person-group>. <article-title>CD4 is an important host factor for Japanese encephalitis virus entry and replication in PK-15 cells</article-title>. <source>Vet Microbiol</source>. (<year>2023</year>) <volume>287</volume>:<fpage>109913</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.vetmic.2023.109913</pub-id>, PMID: <pub-id pub-id-type="pmid">38006719</pub-id></citation></ref>
<ref id="ref16"><label>16.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Paul</surname> <given-names>KK</given-names></name> <name><surname>Sazzad</surname> <given-names>HMS</given-names></name> <name><surname>Rahman</surname> <given-names>M</given-names></name> <name><surname>Sultana</surname> <given-names>S</given-names></name> <name><surname>Hossain</surname> <given-names>MJ</given-names></name> <name><surname>Ledermann</surname> <given-names>JP</given-names></name> <etal/></person-group>. <article-title>Hospital-based surveillance for Japanese encephalitis in Bangladesh, 2007&#x2013;2016: implications for introduction of immunization</article-title>. <source>Int J Infect Dis</source>. (<year>2020</year>) <volume>99</volume>:<fpage>69</fpage>&#x2013;<lpage>74</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.ijid.2020.07.026</pub-id>, PMID: <pub-id pub-id-type="pmid">32721530</pub-id></citation></ref>
<ref id="ref17"><label>17.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Impoinvil</surname> <given-names>DE</given-names></name> <name><surname>Baylis</surname> <given-names>M</given-names></name> <name><surname>Solomon</surname> <given-names>T</given-names></name></person-group>. <article-title>Japanese encephalitis: on the one health agenda</article-title>. <source>Curr Top Microbiol Immunol</source>. (<year>2013</year>) <volume>365</volume>:<fpage>205</fpage>&#x2013;<lpage>47</lpage>. doi: <pub-id pub-id-type="doi">10.1007/82_2012_243</pub-id>, PMID: <pub-id pub-id-type="pmid">22886540</pub-id></citation></ref>
<ref id="ref18"><label>18.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>De</surname> <given-names>Y</given-names></name> <name><surname>Zou</surname> <given-names>WZ</given-names></name> <name><surname>Liu</surname> <given-names>H</given-names></name></person-group>. <article-title>Overview of porcine epidemic encephalitis B and its prevention and treatment in pigs</article-title>. <source>Chinese Livestock Poultry Breed Chinese</source>. (<year>2022</year>) <volume>18</volume>:<fpage>138</fpage>&#x2013;<lpage>40</lpage>.</citation></ref>
<ref id="ref19"><label>19.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Erlanger</surname> <given-names>TE</given-names></name> <name><surname>Weiss</surname> <given-names>S</given-names></name> <name><surname>Keiser</surname> <given-names>J</given-names></name> <name><surname>Utzinger</surname> <given-names>J</given-names></name> <name><surname>Wiedenmayer</surname> <given-names>K</given-names></name></person-group>. <article-title>Past, present, and future of Japanese encephalitis</article-title>. <source>Emerg Infect Dis</source>. (<year>2009</year>) <volume>15</volume>:<fpage>1</fpage>&#x2013;<lpage>7</lpage>. doi: <pub-id pub-id-type="doi">10.3201/eid1501.080311</pub-id>, PMID: <pub-id pub-id-type="pmid">19116041</pub-id></citation></ref>
<ref id="ref20"><label>20.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ricklin</surname> <given-names>ME</given-names></name> <name><surname>Garc&#x00ED;a-Nicol&#x00E1;s</surname> <given-names>O</given-names></name> <name><surname>Brechb&#x00FC;hl</surname> <given-names>D</given-names></name> <name><surname>Python</surname> <given-names>S</given-names></name> <name><surname>Zumkehr</surname> <given-names>B</given-names></name> <name><surname>Nougairede</surname> <given-names>A</given-names></name> <etal/></person-group>. <article-title>Vector-free transmission and persistence of Japanese encephalitis virus in pigs</article-title>. <source>Nat Commun</source>. (<year>2016</year>) <volume>7</volume>:<fpage>10832</fpage>. doi: <pub-id pub-id-type="doi">10.1038/ncomms10832</pub-id>, PMID: <pub-id pub-id-type="pmid">26902924</pub-id></citation></ref>
<ref id="ref21"><label>21.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Liu</surname> <given-names>QL</given-names></name> <name><surname>Jian</surname> <given-names>WX</given-names></name> <name><surname>Shi</surname> <given-names>CQ</given-names></name> <name><surname>Xia</surname> <given-names>ZH</given-names></name> <name><surname>Yang</surname> <given-names>GY</given-names></name> <name><surname>Hong</surname> <given-names>J</given-names></name> <etal/></person-group>. <article-title>Monitoring immune antibodies against Japanese encephalitis in pigs from a large-scale farm in Yuping County, Guizhou Province from 2020 to 2022 (in Chinese)</article-title>. <source>Animals Breed Feed</source>. (<year>2024</year>) <volume>23</volume>:<fpage>75</fpage>&#x2013;<lpage>8</lpage>. doi: <pub-id pub-id-type="doi">10.13300/j.cnki.cn42-1648/s.2024.11.016</pub-id></citation></ref>
<ref id="ref22"><label>22.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Van den Hurk</surname> <given-names>AF</given-names></name> <name><surname>Ritchie</surname> <given-names>SA</given-names></name> <name><surname>Mackenzie</surname> <given-names>JS</given-names></name></person-group>. <article-title>Ecology and geographical expansion of Japanese encephalitis virus</article-title>. <source>Annu Rev Entomol</source>. (<year>2009</year>) <volume>54</volume>:<fpage>17</fpage>&#x2013;<lpage>35</lpage>. doi: <pub-id pub-id-type="doi">10.1146/annurev.ento.54.110807.090510</pub-id>, PMID: <pub-id pub-id-type="pmid">19067628</pub-id></citation></ref>
<ref id="ref23"><label>23.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Simpson</surname> <given-names>DI</given-names></name> <name><surname>Smith</surname> <given-names>CE</given-names></name> <name><surname>Marshall</surname> <given-names>TF</given-names></name> <name><surname>Platt</surname> <given-names>GS</given-names></name> <name><surname>Way</surname> <given-names>HJ</given-names></name> <name><surname>Bowen</surname> <given-names>ETW</given-names></name> <etal/></person-group>. <article-title>Arbovirus infections in Sarawak: the role of the domestic pig</article-title>. <source>Trans R Soc Trop Med Hyg</source>. (<year>1976</year>) <volume>70</volume>:<fpage>66</fpage>&#x2013;<lpage>72</lpage>. doi: <pub-id pub-id-type="doi">10.1016/0035-9203(76)90010-9</pub-id>, PMID: <pub-id pub-id-type="pmid">1265821</pub-id></citation></ref>
<ref id="ref24"><label>24.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname> <given-names>H</given-names></name> <name><surname>Li</surname> <given-names>Y</given-names></name> <name><surname>Liang</surname> <given-names>X</given-names></name> <name><surname>Liang</surname> <given-names>G</given-names></name></person-group>. <article-title>Japanese encephalitis in Mainland China</article-title>. <source>Jpn J Infect Dis</source>. (<year>2009</year>) <volume>62</volume>:<fpage>331</fpage>&#x2013;<lpage>6</lpage>. PMID: <pub-id pub-id-type="pmid">19762980</pub-id></citation></ref>
<ref id="ref25"><label>25.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mansfield</surname> <given-names>KL</given-names></name> <name><surname>Hern&#x00E1;ndez-Triana</surname> <given-names>LM</given-names></name> <name><surname>Banyard</surname> <given-names>AC</given-names></name> <name><surname>Fooks</surname> <given-names>AR</given-names></name> <name><surname>Johnson</surname> <given-names>N</given-names></name></person-group>. <article-title>Japanese encephalitis virus infection, diagnosis and control in domestic animals</article-title>. <source>Vet Microbiol</source>. (<year>2017</year>) <volume>201</volume>:<fpage>85</fpage>&#x2013;<lpage>92</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.vetmic.2017.01.014</pub-id>, PMID: <pub-id pub-id-type="pmid">28284628</pub-id></citation></ref>
<ref id="ref26"><label>26.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Chai</surname> <given-names>C</given-names></name> <name><surname>Wang</surname> <given-names>Q</given-names></name> <name><surname>Cao</surname> <given-names>S</given-names></name> <name><surname>Zhao</surname> <given-names>Q</given-names></name> <name><surname>Wen</surname> <given-names>Y</given-names></name> <name><surname>Huang</surname> <given-names>X</given-names></name> <etal/></person-group>. <article-title>Serological and molecular epidemiology of Japanese encephalitis virus infections in swine herds in China, 2006&#x2013;2012</article-title>. <source>J Vet Sci</source>. (<year>2018</year>) <volume>19</volume>:<fpage>151</fpage>&#x2013;<lpage>5</lpage>. doi: <pub-id pub-id-type="doi">10.4142/jvs.2018.19.1.151</pub-id>, PMID: <pub-id pub-id-type="pmid">28693301</pub-id></citation></ref>
<ref id="ref27"><label>27.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Park</surname> <given-names>SL</given-names></name> <name><surname>Huang</surname> <given-names>YS</given-names></name> <name><surname>Vanlandingham</surname> <given-names>DL</given-names></name></person-group>. <article-title>Re-examining the importance of pigs in the transmission of Japanese encephalitis virus</article-title>. <source>Pathogens</source>. (<year>2022</year>) <volume>11</volume>:<fpage>575</fpage>. doi: <pub-id pub-id-type="doi">10.3390/pathogens11050575</pub-id>, PMID: <pub-id pub-id-type="pmid">35631096</pub-id></citation></ref>
<ref id="ref28"><label>28.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Lyons</surname> <given-names>AC</given-names></name> <name><surname>Huang</surname> <given-names>YS</given-names></name> <name><surname>Park</surname> <given-names>SL</given-names></name> <name><surname>Ayers</surname> <given-names>VB</given-names></name> <name><surname>Hettenbach</surname> <given-names>SM</given-names></name> <name><surname>Higgs</surname> <given-names>S</given-names></name> <etal/></person-group>. <article-title>Shedding of Japanese encephalitis virus in oral fluid of infected swine</article-title>. <source>Vector Borne Zoonotic Dis</source>. (<year>2018</year>) <volume>18</volume>:<fpage>469</fpage>&#x2013;<lpage>74</lpage>. doi: <pub-id pub-id-type="doi">10.1089/vbz.2018.2283</pub-id>, PMID: <pub-id pub-id-type="pmid">29742002</pub-id></citation></ref>
<ref id="ref29"><label>29.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname> <given-names>XX</given-names></name> <name><surname>Ren</surname> <given-names>WX</given-names></name> <name><surname>Tan</surname> <given-names>QD</given-names></name> <name><surname>Hou</surname> <given-names>GY</given-names></name> <name><surname>Fei</surname> <given-names>YC</given-names></name> <name><surname>Zhao</surname> <given-names>LJ</given-names></name> <etal/></person-group>. <article-title>Meta-analysis of toxoplasma gondii in pigs intended for human consumption in Mainland China</article-title>. <source>Acta Trop</source>. (<year>2019</year>) <volume>198</volume>:<fpage>105081</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.actatropica.2019.105081</pub-id>, PMID: <pub-id pub-id-type="pmid">31299285</pub-id></citation></ref>
<ref id="ref30"><label>30.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Banerjee</surname> <given-names>S</given-names></name> <name><surname>Sen Gupta</surname> <given-names>PS</given-names></name> <name><surname>Bandyopadhyay</surname> <given-names>AK</given-names></name></person-group>. <article-title>Insight into SNPs and epitopes of E protein of newly emerged genotype-I isolates of JEV from Midnapur, West Bengal, India</article-title>. <source>BMC Immunol</source>. (<year>2017</year>) <volume>18</volume>:<fpage>13</fpage>. doi: <pub-id pub-id-type="doi">10.1186/s12865-017-0197-9</pub-id>, PMID: <pub-id pub-id-type="pmid">28264652</pub-id></citation></ref>
<ref id="ref31"><label>31.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ning-Qing</surname> <given-names>C</given-names></name></person-group>. <article-title>Control of arboviral encephalitis in China (Author's Transl)</article-title>. <source>Med Trop (Mars)</source>. (<year>1980</year>) <volume>40</volume>:<fpage>555</fpage>&#x2013;<lpage>9</lpage>.</citation></ref>
<ref id="ref32"><label>32.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Yuan</surname> <given-names>L</given-names></name> <name><surname>Wu</surname> <given-names>R</given-names></name> <name><surname>Liu</surname> <given-names>H</given-names></name> <name><surname>Wen</surname> <given-names>X</given-names></name> <name><surname>Huang</surname> <given-names>X</given-names></name> <name><surname>Wen</surname> <given-names>Y</given-names></name> <etal/></person-group>. <article-title>Tissue tropism and molecular characterization of a Japanese encephalitis virus strain isolated from pigs in Southwest China</article-title>. <source>Virus Res</source>. (<year>2016</year>) <volume>215</volume>:<fpage>55</fpage>&#x2013;<lpage>64</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.virusres.2016.02.001</pub-id>, PMID: <pub-id pub-id-type="pmid">26851509</pub-id></citation></ref>
<ref id="ref33"><label>33.</label> <citation citation-type="journal"><person-group person-group-type="author"><collab id="coll1">WHO</collab></person-group>. <article-title>Japanese encephalitis vaccines: who position paper, February 2015&#x2013;recommendations</article-title>. <source>Vaccine</source>. (<year>2016</year>) <volume>34</volume>:<fpage>302</fpage>&#x2013;<lpage>3</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.vaccine.2015.07.057</pub-id>, PMID: <pub-id pub-id-type="pmid">26232543</pub-id></citation></ref>
<ref id="ref34"><label>34.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>YX</given-names></name> <name><surname>Li</surname> <given-names>MH</given-names></name> <name><surname>Fu</surname> <given-names>SH</given-names></name> <name><surname>Chen</surname> <given-names>WX</given-names></name> <name><surname>Liu</surname> <given-names>QY</given-names></name> <name><surname>Zhang</surname> <given-names>HL</given-names></name> <etal/></person-group>. <article-title>Japanese encephalitis, Tibet, China</article-title>. <source>Emerg Infect Dis</source>. (<year>2011</year>) <volume>17</volume>:<fpage>934</fpage>&#x2013;<lpage>6</lpage>. doi: <pub-id pub-id-type="doi">10.3201/eid1705.101417</pub-id>, PMID: <pub-id pub-id-type="pmid">21529419</pub-id></citation></ref>
<ref id="ref35"><label>35.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Weaver</surname> <given-names>SC</given-names></name> <name><surname>Barrett</surname> <given-names>AD</given-names></name></person-group>. <article-title>Transmission cycles, host range, evolution and emergence of arboviral disease</article-title>. <source>Nat Rev Microbiol</source>. (<year>2004</year>) <volume>2</volume>:<fpage>789</fpage>&#x2013;<lpage>801</lpage>. doi: <pub-id pub-id-type="doi">10.1038/nrmicro1006</pub-id>, PMID: <pub-id pub-id-type="pmid">15378043</pub-id></citation></ref>
<ref id="ref36"><label>36.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ni</surname> <given-names>HB</given-names></name> <name><surname>Gong</surname> <given-names>QL</given-names></name> <name><surname>Zhao</surname> <given-names>Q</given-names></name> <name><surname>Li</surname> <given-names>XY</given-names></name> <name><surname>Zhang</surname> <given-names>XX</given-names></name></person-group>. <article-title>Prevalence of Haemophiles parasuis "Glaesserella Parasuis" in pigs in China: a systematic review and meta-analysis</article-title>. <source>Prev Vet Med</source>. (<year>2020</year>) <volume>182</volume>:<fpage>105083</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.prevetmed.2020.105083</pub-id>, PMID: <pub-id pub-id-type="pmid">32652336</pub-id></citation></ref>
<ref id="ref37"><label>37.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Moher</surname> <given-names>D</given-names></name> <name><surname>Liberati</surname> <given-names>A</given-names></name> <name><surname>Tetzlaff</surname> <given-names>J</given-names></name> <name><surname>Altman</surname> <given-names>DG</given-names></name></person-group>. <article-title>Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement</article-title>. <source>Ann Intern Med</source>. (<year>2009</year>) <volume>6</volume>:<fpage>e1000097</fpage>. doi: <pub-id pub-id-type="doi">10.1371/journal.pmed.1000097</pub-id>, PMID: <pub-id pub-id-type="pmid">19621072</pub-id></citation></ref>
<ref id="ref38"><label>38.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Moher</surname> <given-names>D</given-names></name> <name><surname>Shamseer</surname> <given-names>L</given-names></name> <name><surname>Clarke</surname> <given-names>M</given-names></name> <name><surname>Ghersi</surname> <given-names>D</given-names></name> <name><surname>Liberati</surname> <given-names>A</given-names></name> <name><surname>Petticrew</surname> <given-names>M</given-names></name> <etal/></person-group>. <article-title>Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement</article-title>. <source>Syst Rev</source>. (<year>2015</year>) <volume>4</volume>:<fpage>1</fpage>. doi: <pub-id pub-id-type="doi">10.1186/2046-4053-4-1</pub-id>, PMID: <pub-id pub-id-type="pmid">25554246</pub-id></citation></ref>
<ref id="ref39"><label>39.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname> <given-names>W</given-names></name> <name><surname>Gong</surname> <given-names>QL</given-names></name> <name><surname>Zeng</surname> <given-names>A</given-names></name> <name><surname>Li</surname> <given-names>MH</given-names></name> <name><surname>Zhao</surname> <given-names>Q</given-names></name> <name><surname>Ni</surname> <given-names>HB</given-names></name></person-group>. <article-title>Prevalence of cryptosporidium in pigs in China: a systematic review and meta-analysis</article-title>. <source><italic>Trans bound Emerg</italic> Dis</source>. (<year>2021</year>) <volume>68</volume>:<fpage>1400</fpage>&#x2013;<lpage>13</lpage>. doi: <pub-id pub-id-type="doi">10.1111/tbed.13806</pub-id></citation></ref>
<ref id="ref40"><label>40.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ran</surname> <given-names>X</given-names></name> <name><surname>Cheng</surname> <given-names>J</given-names></name> <name><surname>Wang</surname> <given-names>M</given-names></name> <name><surname>Chen</surname> <given-names>X</given-names></name> <name><surname>Wang</surname> <given-names>H</given-names></name> <name><surname>Ge</surname> <given-names>Y</given-names></name> <etal/></person-group>. <article-title>Brucellosis seroprevalence in dairy cattle in China during 2008-2018: a systematic review and meta-analysis</article-title>. <source>Acta Trop</source>. (<year>2019</year>) <volume>189</volume>:<fpage>117</fpage>&#x2013;<lpage>23</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.actatropica.2018.10.002</pub-id>, PMID: <pub-id pub-id-type="pmid">30308207</pub-id></citation></ref>
<ref id="ref41"><label>41.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Barendregt</surname> <given-names>JJ</given-names></name> <name><surname>Doi</surname> <given-names>SA</given-names></name> <name><surname>Lee</surname> <given-names>YY</given-names></name> <name><surname>Norman</surname> <given-names>RE</given-names></name> <name><surname>Vos</surname> <given-names>T</given-names></name></person-group>. <article-title>Meta-analysis of prevalence</article-title>. <source>J Epidemiol Community Health</source>. (<year>2013</year>) <volume>67</volume>:<fpage>974</fpage>&#x2013;<lpage>8</lpage>. doi: <pub-id pub-id-type="doi">10.1136/jech-2013-203104</pub-id>, PMID: <pub-id pub-id-type="pmid">23963506</pub-id></citation></ref>
<ref id="ref42"><label>42.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Assefa</surname> <given-names>A</given-names></name> <name><surname>Bihon</surname> <given-names>A</given-names></name></person-group>. <article-title>Bovine cysticercosis in Ethiopia: a systematic review and meta-analysis of prevalence from abattoir-based surveys</article-title>. <source>Prev Vet Med</source>. (<year>2019</year>) <volume>169</volume>:<fpage>104707</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.prevetmed.2019.104707</pub-id>, PMID: <pub-id pub-id-type="pmid">31311641</pub-id></citation></ref>
<ref id="ref43"><label>43.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Gong</surname> <given-names>QL</given-names></name> <name><surname>Li</surname> <given-names>D</given-names></name> <name><surname>Diao</surname> <given-names>NC</given-names></name> <name><surname>Liu</surname> <given-names>Y</given-names></name> <name><surname>Li</surname> <given-names>BY</given-names></name> <name><surname>Tian</surname> <given-names>T</given-names></name> <etal/></person-group>. <article-title>Mink Aleutian disease seroprevalence in China during 1981&#x2013;2017: a systematic review and meta-analysis</article-title>. <source>Microb Pathog</source>. (<year>2020</year>) <volume>139</volume>:<fpage>103908</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.micpath.2019.103908</pub-id>, PMID: <pub-id pub-id-type="pmid">31830583</pub-id></citation></ref>
<ref id="ref44"><label>44.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shamseer</surname> <given-names>L</given-names></name> <name><surname>Moher</surname> <given-names>D</given-names></name> <name><surname>Clarke</surname> <given-names>M</given-names></name> <name><surname>Ghersi</surname> <given-names>D</given-names></name> <name><surname>Liberati</surname> <given-names>A</given-names></name> <name><surname>Petticrew</surname> <given-names>M</given-names></name> <etal/></person-group>. <article-title>Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation</article-title>. <source>BMJ</source>. (<year>2015</year>) <volume>349</volume>:<fpage>g7647</fpage>. doi: <pub-id pub-id-type="doi">10.1136/bmj.g7647</pub-id>, PMID: <pub-id pub-id-type="pmid">25555855</pub-id></citation></ref>
<ref id="ref45"><label>45.</label> <citation citation-type="journal"><article-title>Japanese encephalitis surveillance and immunization--Asia and the Western Pacific, 2012</article-title>. <source><italic>MMWR Morb Mortal Wkly</italic> Rep</source>. (<year>2013</year>) <volume>62</volume>:<fpage>658</fpage>&#x2013;<lpage>62</lpage>. PMID: <pub-id pub-id-type="pmid">23965828</pub-id></citation></ref>
<ref id="ref46"><label>46.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Dhanda</surname> <given-names>V</given-names></name> <name><surname>Thenmozhi</surname> <given-names>V</given-names></name> <name><surname>Kumar</surname> <given-names>NP</given-names></name> <name><surname>Hiriyan</surname> <given-names>J</given-names></name> <name><surname>Arunachalam</surname> <given-names>N</given-names></name> <name><surname>Balasubramanian</surname> <given-names>A</given-names></name> <etal/></person-group>. <article-title>Virus isolation from wild-caught mosquitoes during a Japanese encephalitis outbreak in Kerala in 1996</article-title>. <source>Indian J Med Res</source>. (<year>1997</year>) <volume>106</volume>:<fpage>4</fpage>&#x2013;<lpage>6</lpage>. PMID: <pub-id pub-id-type="pmid">9248207</pub-id></citation></ref>
<ref id="ref47"><label>47.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Schuh</surname> <given-names>AJ</given-names></name> <name><surname>Li</surname> <given-names>L</given-names></name> <name><surname>Tesh</surname> <given-names>RB</given-names></name> <name><surname>Innis</surname> <given-names>BL</given-names></name> <name><surname>Barrett</surname> <given-names>AD</given-names></name></person-group>. <article-title>Genetic characterization of early isolates of Japanese encephalitis virus: genotype II has been circulating since at least 1951</article-title>. <source>J Gen Virol</source>. (<year>2010</year>) <volume>91</volume>:<fpage>95</fpage>&#x2013;<lpage>102</lpage>. doi: <pub-id pub-id-type="doi">10.1099/vir.0.013631-0</pub-id>, PMID: <pub-id pub-id-type="pmid">19776238</pub-id></citation></ref>
<ref id="ref48"><label>48.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Williams</surname> <given-names>DT</given-names></name> <name><surname>Wang</surname> <given-names>LF</given-names></name> <name><surname>Daniels</surname> <given-names>PW</given-names></name> <name><surname>Mackenzie</surname> <given-names>JS</given-names></name></person-group>. <article-title>Molecular characterization of the first Australian isolate of Japanese encephalitis virus, the Fu strain</article-title>. <source>J Gen Virol</source>. (<year>2000</year>) <volume>81</volume>:<fpage>2471</fpage>&#x2013;<lpage>80</lpage>. doi: <pub-id pub-id-type="doi">10.1099/0022-1317-81-10-2471</pub-id>, PMID: <pub-id pub-id-type="pmid">10993935</pub-id></citation></ref>
<ref id="ref49"><label>49.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Nabeshima</surname> <given-names>T</given-names></name> <name><surname>Loan</surname> <given-names>HTK</given-names></name> <name><surname>Inoue</surname> <given-names>S</given-names></name> <name><surname>Sumiyoshi</surname> <given-names>M</given-names></name> <name><surname>Haruta</surname> <given-names>Y</given-names></name> <name><surname>Nga</surname> <given-names>PT</given-names></name> <etal/></person-group>. <article-title>Evidence of frequent introductions of Japanese encephalitis virus from South-East Asia and continental East Asia to Japan</article-title>. <source>J Gen Virol</source>. (<year>2009</year>) <volume>90</volume>:<fpage>827</fpage>&#x2013;<lpage>32</lpage>. doi: <pub-id pub-id-type="doi">10.1099/vir.0.007617-0</pub-id>, PMID: <pub-id pub-id-type="pmid">19264633</pub-id></citation></ref>
<ref id="ref50"><label>50.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sikazwe</surname> <given-names>C</given-names></name> <name><surname>Neave</surname> <given-names>MJ</given-names></name> <name><surname>Michie</surname> <given-names>A</given-names></name> <name><surname>Mileto</surname> <given-names>P</given-names></name> <name><surname>Wang</surname> <given-names>J</given-names></name> <name><surname>Cooper</surname> <given-names>N</given-names></name> <etal/></person-group>. <article-title>Molecular detection and characterization of the first Japanese encephalitis virus belonging to genotype IV acquired in Australia</article-title>. <source>PLoS Negl Trop Dis</source>. (<year>2022</year>) <volume>16</volume>:<fpage>e0010754</fpage>. doi: <pub-id pub-id-type="doi">10.1371/journal.pntd.0010754</pub-id>, PMID: <pub-id pub-id-type="pmid">36409739</pub-id></citation></ref>
<ref id="ref51"><label>51.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sewgobind</surname> <given-names>S</given-names></name> <name><surname>Johnson</surname> <given-names>N</given-names></name> <name><surname>Mansfield</surname> <given-names>KL</given-names></name></person-group>. <article-title>Jmm profile: Japanese encephalitis virus: an emerging threat</article-title>. <source>J Med Microbiol</source>. (<year>2022</year>) <volume>71</volume>. doi: <pub-id pub-id-type="doi">10.1099/jmm.0.001620</pub-id>, PMID: <pub-id pub-id-type="pmid">36748429</pub-id></citation></ref>
<ref id="ref52"><label>52.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhao</surname> <given-names>X</given-names></name> <name><surname>Cao</surname> <given-names>MQ</given-names></name> <name><surname>Feng</surname> <given-names>HH</given-names></name> <name><surname>Fan</surname> <given-names>H</given-names></name> <name><surname>Chen</surname> <given-names>F</given-names></name> <name><surname>Feng</surname> <given-names>Z</given-names></name> <etal/></person-group>. <article-title>Japanese encephalitis risk and contextual risk factors in Southwest China: a Bayesian hierarchical spatial and spatiotemporal analysis</article-title>. <source>Int J Environ Res Public Health</source>. (<year>2014</year>) <volume>11</volume>:<fpage>4201</fpage>&#x2013;<lpage>17</lpage>. doi: <pub-id pub-id-type="doi">10.3390/ijerph110404201</pub-id>, PMID: <pub-id pub-id-type="pmid">24739769</pub-id></citation></ref>
<ref id="ref53"><label>53.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>X</given-names></name> <name><surname>Gao</surname> <given-names>X</given-names></name> <name><surname>Ren</surname> <given-names>Z</given-names></name> <name><surname>Cao</surname> <given-names>Y</given-names></name> <name><surname>Wang</surname> <given-names>J</given-names></name> <name><surname>Liang</surname> <given-names>G</given-names></name></person-group>. <article-title>A spatial and temporal analysis of Japanese encephalitis in Mainland China, 1963&#x2013;1975: a period without Japanese encephalitis vaccination</article-title>. <source>PLoS One</source>. (<year>2014</year>) <volume>9</volume>:<fpage>e99183</fpage>. doi: <pub-id pub-id-type="doi">10.1371/journal.pone.0099183</pub-id>, PMID: <pub-id pub-id-type="pmid">24911168</pub-id></citation></ref>
<ref id="ref54"><label>54.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zheng</surname> <given-names>Y</given-names></name> <name><surname>Li</surname> <given-names>M</given-names></name> <name><surname>Wang</surname> <given-names>H</given-names></name> <name><surname>Liang</surname> <given-names>G</given-names></name></person-group>. <article-title>Japanese encephalitis and Japanese encephalitis virus in Mainland China</article-title>. <source>Rev Med Virol</source>. (<year>2012</year>) <volume>22</volume>:<fpage>301</fpage>&#x2013;<lpage>22</lpage>. doi: <pub-id pub-id-type="doi">10.1002/rmv.1710</pub-id>, PMID: <pub-id pub-id-type="pmid">22407526</pub-id></citation></ref>
<ref id="ref55"><label>55.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Liang</surname> <given-names>G</given-names></name> <name><surname>Li</surname> <given-names>X</given-names></name> <name><surname>Gao</surname> <given-names>X</given-names></name> <name><surname>Fu</surname> <given-names>S</given-names></name> <name><surname>Wang</surname> <given-names>H</given-names></name> <name><surname>Li</surname> <given-names>M</given-names></name> <etal/></person-group>. <article-title>Arboviruses and their related infections in China: a comprehensive field and laboratory investigation over the last 3 decades</article-title>. <source>Rev Med Virol</source>. (<year>2018</year>) <volume>28</volume>:<fpage>1</fpage>&#x2013;<lpage>21</lpage>. doi: <pub-id pub-id-type="doi">10.1002/rmv.1959</pub-id>, PMID: <pub-id pub-id-type="pmid">29210509</pub-id></citation></ref>
<ref id="ref56"><label>56.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname> <given-names>J</given-names></name> <name><surname>Ogden</surname> <given-names>NH</given-names></name> <name><surname>Zhu</surname> <given-names>H</given-names></name></person-group>. <article-title>The impact of weather conditions on Culex pipiens and <italic>Culex restuans</italic> (Diptera: Culicidae) abundance: a case study in Peel region</article-title>. <source>J Med Entomol</source>. (<year>2011</year>) <volume>48</volume>:<fpage>468</fpage>&#x2013;<lpage>75</lpage>. doi: <pub-id pub-id-type="doi">10.1603/me10117</pub-id>, PMID: <pub-id pub-id-type="pmid">21485391</pub-id></citation></ref>
<ref id="ref57"><label>57.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname> <given-names>L</given-names></name> <name><surname>Hu</surname> <given-names>W</given-names></name> <name><surname>Soares Magalhaes</surname> <given-names>RJ</given-names></name> <name><surname>Bi</surname> <given-names>P</given-names></name> <name><surname>Ding</surname> <given-names>F</given-names></name> <name><surname>Sun</surname> <given-names>H</given-names></name> <etal/></person-group>. <article-title>The role of environmental factors in the spatial distribution of Japanese encephalitis in Mainland China</article-title>. <source>Environ Int</source>. (<year>2014</year>) <volume>73</volume>:<fpage>1</fpage>&#x2013;<lpage>9</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.envint.2014.07.004</pub-id>, PMID: <pub-id pub-id-type="pmid">25072160</pub-id></citation></ref>
<ref id="ref58"><label>58.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Aditi</surname> <given-names>S</given-names></name> <name><surname>Shailendra</surname> <given-names>K</given-names></name> <name><surname>Saxena</surname></name> <name><surname>Srivastava</surname> <given-names>AK</given-names></name> <name><surname>Asha</surname> <given-names>M</given-names></name></person-group>. <article-title>Japanese encephalitis: a persistent threat</article-title>. <source>Proc Natl Acad Sci India Sect B Biol Sci</source>. (<year>2012</year>) <volume>82</volume>:<fpage>55</fpage>&#x2013;<lpage>68</lpage>.</citation></ref>
<ref id="ref59"><label>59.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>RF</given-names></name> <name><surname>Zhao</surname> <given-names>XH</given-names></name> <name><surname>Tian</surname> <given-names>Y</given-names></name> <name><surname>Shi</surname> <given-names>YJ</given-names></name> <name><surname>Gu</surname> <given-names>XY</given-names></name> <name><surname>Wang</surname> <given-names>S</given-names></name></person-group>. <article-title>Different responses of Japanese encephalitis to weather variables among eight climate subtypes in Gansu, China, 2005-2019</article-title>. <source>BMC Infect Dis</source>. (<year>2023</year>) <volume>23</volume>:<fpage>114</fpage>. doi: <pub-id pub-id-type="doi">10.1186/s12879-023-08074-6</pub-id>, PMID: <pub-id pub-id-type="pmid">36823521</pub-id></citation></ref>
<ref id="ref60"><label>60.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>XH</given-names></name> <name><surname>Wei</surname> <given-names>CH</given-names></name> <name><surname>Dai</surname> <given-names>AL</given-names></name> <name><surname>Chen</surname> <given-names>SY</given-names></name> <name><surname>Yang</surname> <given-names>XY</given-names></name></person-group>. <article-title>Epidemiological investigation of epidemic encephalitis B in pigs in Longyan city, China in Chinese</article-title>. <source>Heilongjiang Animal Sci Vet Med</source>. (<year>2017</year>) <volume>2</volume>:<fpage>119</fpage>&#x2013;<lpage>22</lpage>. doi: <pub-id pub-id-type="doi">10.13881/j.cnki.hljxmsy.2017.0316</pub-id></citation></ref>
<ref id="ref61"><label>61.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sun</surname> <given-names>Y</given-names></name> <name><surname>Ding</surname> <given-names>H</given-names></name> <name><surname>Zhao</surname> <given-names>F</given-names></name> <name><surname>Yan</surname> <given-names>Q</given-names></name> <name><surname>Li</surname> <given-names>Y</given-names></name> <name><surname>Niu</surname> <given-names>X</given-names></name> <etal/></person-group>. <article-title>Genomic characteristics and E protein bioinformatics analysis of JEV isolates from South China from 2011 to 2018</article-title>. <source>Vaccines (Basel)</source>. <volume>10</volume>:<fpage>1303</fpage>. doi: <pub-id pub-id-type="doi">10.3390/vaccines10081303</pub-id>, PMID: <pub-id pub-id-type="pmid">36016192</pub-id></citation></ref>
<ref id="ref62"><label>62.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Beck</surname> <given-names>C</given-names></name> <name><surname>Lowenski</surname> <given-names>S</given-names></name> <name><surname>Durand</surname> <given-names>B</given-names></name> <name><surname>Bahuon</surname> <given-names>C</given-names></name> <name><surname>Zientara</surname> <given-names>S</given-names></name> <name><surname>Lecollinet</surname> <given-names>S</given-names></name></person-group>. <article-title>Improved reliability of serological tools for the diagnosis of West Nile fever in horses within Europe</article-title>. <source>PLoS Negl Trop Dis</source>. (<year>2017</year>) <volume>11</volume>:<fpage>e0005936</fpage>. doi: <pub-id pub-id-type="doi">10.1371/journal.pntd.0005936</pub-id>, PMID: <pub-id pub-id-type="pmid">28915240</pub-id></citation></ref>
<ref id="ref63"><label>63.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shao</surname> <given-names>N</given-names></name> <name><surname>Li</surname> <given-names>F</given-names></name> <name><surname>Nie</surname> <given-names>K</given-names></name> <name><surname>Fu</surname> <given-names>SH</given-names></name> <name><surname>Zhang</surname> <given-names>WJ</given-names></name> <etal/></person-group>. <article-title>TaqMan real-time RT-PCR assay for detecting and differentiating Japanese encephalitis virus</article-title>. <source>Biomed Environ Sci</source>. (<year>2018</year>) <volume>31</volume>:<fpage>208</fpage>&#x2013;<lpage>14</lpage>. doi: <pub-id pub-id-type="doi">10.3967/bes2018.026</pub-id></citation></ref>
<ref id="ref64"><label>64.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Santhosh</surname> <given-names>SR</given-names></name> <name><surname>Parida</surname> <given-names>MM</given-names></name> <name><surname>Dash</surname> <given-names>PK</given-names></name> <name><surname>Pateriya</surname> <given-names>A</given-names></name> <name><surname>Pattnaik</surname> <given-names>B</given-names></name> <name><surname>Pradhan</surname> <given-names>HK</given-names></name> <etal/></person-group>. <article-title>Development and evaluation of SYBR green I-based one-step real-time RT-PCR assay for detection and quantitation of Japanese encephalitis virus</article-title>. <source>J Virol Methods</source>. (<year>2007</year>) <volume>143</volume>:<fpage>73</fpage>&#x2013;<lpage>80</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jviromet.2007.02.011</pub-id>, PMID: <pub-id pub-id-type="pmid">17403544</pub-id></citation></ref>
<ref id="ref65"><label>65.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wu</surname> <given-names>X</given-names></name> <name><surname>Lin</surname> <given-names>H</given-names></name> <name><surname>Chen</surname> <given-names>S</given-names></name> <name><surname>Xiao</surname> <given-names>L</given-names></name> <name><surname>Yang</surname> <given-names>M</given-names></name> <name><surname>An</surname> <given-names>W</given-names></name> <etal/></person-group>. <article-title>Development and application of a reverse transcriptase droplet digital PCR (RT-ddPCR) for sensitive and rapid detection of Japanese encephalitis virus</article-title>. <source>J Virol Methods</source>. (<year>2017</year>) <volume>248</volume>:<fpage>166</fpage>&#x2013;<lpage>71</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jviromet.2017.06.015</pub-id>, PMID: <pub-id pub-id-type="pmid">28673857</pub-id></citation></ref>
<ref id="ref66"><label>66.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Cui</surname> <given-names>Y</given-names></name></person-group>. <article-title>Development of Nanobody and construction of immunoassay for staphylococcal enterotoxin (in Chinese)</article-title>. <source>Northwest A&#x0026;F Univ</source>. (<year>2024</year>). doi: <pub-id pub-id-type="doi">10.27409/d.cnki.gxbnu.2024.002195</pub-id></citation></ref>
<ref id="ref67"><label>67.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sun</surname> <given-names>SY</given-names></name> <name><surname>Wu</surname> <given-names>JJ</given-names></name> <name><surname>Yang</surname> <given-names>Z</given-names></name></person-group>. <article-title>Progress in serological detection of hepatitis B</article-title>. <source>Modern Med Health Res Electronic J</source>. (<year>2023</year>) <volume>7</volume>:<fpage>134</fpage>&#x2013;<lpage>7</lpage>.</citation></ref>
<ref id="ref68"><label>68.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Niu</surname> <given-names>YH</given-names></name> <name><surname>Yang</surname> <given-names>K</given-names></name> <name><surname>Wang</surname> <given-names>FM</given-names></name> <name><surname>Shen</surname> <given-names>HQ</given-names></name> <name><surname>Zhao</surname> <given-names>BH</given-names></name></person-group>. <article-title>Research advances and application of the polymerase chain reaction (PCR) in shrimp virus inspection</article-title>. <source>Hebei Fisheries</source>. (<year>2009</year>) <volume>1</volume>:<fpage>14</fpage>&#x2013;<lpage>24</lpage>.</citation></ref>
<ref id="ref69"><label>69.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Liu</surname> <given-names>ZL</given-names></name> <name><surname>Liu</surname> <given-names>ZY</given-names></name> <name><surname>Li</surname> <given-names>ZJ</given-names></name> <name><surname>Guo</surname> <given-names>L</given-names></name></person-group>. <article-title>Research progress of bovine rotavirus</article-title>. <source>Graziery Vet Sci</source>. (<year>2019</year>) <volume>20</volume>:<fpage>1</fpage>&#x2013;<lpage>3</lpage>.</citation></ref>
<ref id="ref70"><label>70.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mei</surname> <given-names>L</given-names></name> <name><surname>Wu</surname> <given-names>P</given-names></name> <name><surname>Ye</surname> <given-names>J</given-names></name> <name><surname>Gao</surname> <given-names>G</given-names></name> <name><surname>Shao</surname> <given-names>L</given-names></name> <name><surname>Huang</surname> <given-names>S</given-names></name> <etal/></person-group>. <article-title>Development and application of an antigen capture ELISA assay for diagnosis of Japanese encephalitis virus in swine, human and mosquito</article-title>. <source>Virol J</source>. (<year>2012</year>) <volume>9</volume>:<fpage>4</fpage>. doi: <pub-id pub-id-type="doi">10.1186/1743-422X-9-4</pub-id>, PMID: <pub-id pub-id-type="pmid">22221768</pub-id></citation></ref>
<ref id="ref71"><label>71.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>Y</given-names></name> <name><surname>Hou</surname> <given-names>L</given-names></name> <name><surname>Ye</surname> <given-names>J</given-names></name> <name><surname>Liu</surname> <given-names>X</given-names></name> <name><surname>Dan</surname> <given-names>H</given-names></name> <name><surname>Jin</surname> <given-names>M</given-names></name> <etal/></person-group>. <article-title>Development of a convenient immunochromatographic strip for the diagnosis of infection with Japanese encephalitis virus in swine</article-title>. <source>J Virol Methods</source>. (<year>2010</year>) <volume>168</volume>:<fpage>51</fpage>&#x2013;<lpage>6</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jviromet.2010.04.015</pub-id>, PMID: <pub-id pub-id-type="pmid">20433870</pub-id></citation></ref>
<ref id="ref72"><label>72.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Liu</surname> <given-names>Y</given-names></name> <name><surname>Gong</surname> <given-names>QL</given-names></name> <name><surname>Nie</surname> <given-names>LB</given-names></name> <name><surname>Wang</surname> <given-names>Q</given-names></name> <name><surname>Ge</surname> <given-names>GY</given-names></name> <name><surname>Li</surname> <given-names>DL</given-names></name> <etal/></person-group>. <article-title>Prevalence of porcine circovirus 2 throughout China in 2015&#x2013;2019: a systematic review and meta-analysis</article-title>. <source>Microb Pathog</source>. (<year>2020</year>) <volume>149</volume>:<fpage>104490</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.micpath.2020.104490</pub-id>, PMID: <pub-id pub-id-type="pmid">32956791</pub-id></citation></ref>
<ref id="ref73"><label>73.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zheng</surname> <given-names>B</given-names></name> <name><surname>Wang</surname> <given-names>X</given-names></name> <name><surname>Liu</surname> <given-names>Y</given-names></name> <name><surname>Li</surname> <given-names>Y</given-names></name> <name><surname>Long</surname> <given-names>S</given-names></name> <name><surname>Gu</surname> <given-names>C</given-names></name> <etal/></person-group>. <article-title>Japanese encephalitis virus infection induces inflammation of swine testis through RIG-I-NF-kB signaling pathway</article-title>. <source>Vet Microbiol</source>. (<year>2019</year>) <volume>238</volume>:<fpage>108430</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.vetmic.2019.108430</pub-id>, PMID: <pub-id pub-id-type="pmid">31648727</pub-id></citation></ref>
<ref id="ref74"><label>74.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Liu</surname> <given-names>H</given-names></name> <name><surname>Liu</surname> <given-names>ZJ</given-names></name> <name><surname>Jing</surname> <given-names>J</given-names></name> <name><surname>Ren</surname> <given-names>JQ</given-names></name> <name><surname>Liu</surname> <given-names>YY</given-names></name> <name><surname>Guo</surname> <given-names>HH</given-names></name> <etal/></person-group>. <article-title>Reverse transcription loop-mediated isothermal amplification for rapid detection of Japanese encephalitis virus in swine and mosquitoes</article-title>. <source>Vector Borne Zoonotic Dis</source>. (<year>2012</year>) <volume>12</volume>:<fpage>1042</fpage>&#x2013;<lpage>52</lpage>. doi: <pub-id pub-id-type="doi">10.1089/vbz.2012.0991</pub-id>, PMID: <pub-id pub-id-type="pmid">23176446</pub-id></citation></ref>
<ref id="ref75"><label>75.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zeng</surname> <given-names>Q</given-names></name> <name><surname>Liu</surname> <given-names>J</given-names></name> <name><surname>Li</surname> <given-names>Z</given-names></name> <name><surname>Zhang</surname> <given-names>Y</given-names></name> <name><surname>Zu</surname> <given-names>S</given-names></name> <name><surname>Ding</surname> <given-names>X</given-names></name> <etal/></person-group>. <article-title>Japanese encephalitis virus NS4B inhibits interferon beta production by targeting TLR3 and TRIF</article-title>. <source>Vet Microbiol</source>. (<year>2023</year>) <volume>284</volume>:<fpage>109849</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.vetmic.2023.109849</pub-id>, PMID: <pub-id pub-id-type="pmid">37597377</pub-id></citation></ref>
<ref id="ref76"><label>76.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Pierson</surname> <given-names>TC</given-names></name> <name><surname>Diamond</surname> <given-names>MS</given-names></name></person-group>. <article-title>The continued threat of emerging flaviviruses</article-title>. <source>Nat Microbiol</source>. (<year>2020</year>) <volume>5</volume>:<fpage>796</fpage>&#x2013;<lpage>812</lpage>. doi: <pub-id pub-id-type="doi">10.1038/s41564-020-0714-0</pub-id>, PMID: <pub-id pub-id-type="pmid">32367055</pub-id></citation></ref>
<ref id="ref77"><label>77.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>X</given-names></name> <name><surname>Li</surname> <given-names>J</given-names></name> <name><surname>Wu</surname> <given-names>G</given-names></name> <name><surname>Wang</surname> <given-names>M</given-names></name> <name><surname>Jing</surname> <given-names>Z</given-names></name></person-group>. <article-title>Detection of Japanese encephalitis by metagenomic next-generation sequencing of cerebrospinal fluid: a case report and literature review</article-title>. <source>Front Cell Neurosci</source>. (<year>2022</year>) <volume>16</volume>:<fpage>856512</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fncel.2022.856512</pub-id>, PMID: <pub-id pub-id-type="pmid">35250491</pub-id></citation></ref>
<ref id="ref78"><label>78.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sharma</surname> <given-names>KB</given-names></name> <name><surname>Vrati</surname> <given-names>S</given-names></name> <name><surname>Kalia</surname> <given-names>M</given-names></name></person-group>. <article-title>Pathobiology of Japanese encephalitis virus infection</article-title>. <source>Mol Asp Med</source>. (<year>2021</year>) <volume>81</volume>:<fpage>100994</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.mam.2021.100994</pub-id>, PMID: <pub-id pub-id-type="pmid">34274157</pub-id></citation></ref>
<ref id="ref79"><label>79.</label> <citation citation-type="journal"><person-group person-group-type="author"><collab id="coll2">National Health Commission of the people&#x2032;s republic of China</collab></person-group>. <article-title>Immunization schedules and instructions for vaccines of the national immunization program (2021 version)</article-title>. <source>Chinese J Viral Dis</source>. (<year>2021</year>) <volume>4</volume>:<fpage>241</fpage>&#x2013;<lpage>5</lpage>. doi: <pub-id pub-id-type="doi">10.16505/j.2095-0136.2021.0021</pub-id></citation></ref>
<ref id="ref80"><label>80.</label> <citation citation-type="journal"><article-title>Global Advisory Committee on vaccine safety, 9-10 June 2005</article-title>. <source>Wkly Epidemiol Rec</source>. (<year>2005</year>) <volume>80</volume>:<fpage>242</fpage>&#x2013;<lpage>7</lpage>. PMID: <pub-id pub-id-type="pmid">16047931</pub-id></citation></ref>
<ref id="ref81"><label>81.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Tu</surname> <given-names>T</given-names></name> <name><surname>Xu</surname> <given-names>KQ</given-names></name> <name><surname>Xu</surname> <given-names>L</given-names></name> <name><surname>Gao</surname> <given-names>Y</given-names></name> <name><surname>Zhou</surname> <given-names>Y</given-names></name> <name><surname>He</surname> <given-names>YM</given-names></name> <etal/></person-group>. <article-title>Association between meteorological factors and the prevalence dynamics of Japanese encephalitis</article-title>. <source>PLoS One</source>. (<year>2021</year>) <volume>16</volume>:<fpage>e0247980</fpage>. doi: <pub-id pub-id-type="doi">10.1371/journal.pone.0247980</pub-id>, PMID: <pub-id pub-id-type="pmid">33657174</pub-id></citation></ref>
<ref id="ref82"><label>82.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname> <given-names>LH</given-names></name> <name><surname>Li</surname> <given-names>Y</given-names></name> <name><surname>Bi</surname> <given-names>YH</given-names></name></person-group>. <article-title>Mosquito and pig with Japanese encephalitis (in Chinese)</article-title>. <source>Swine Ind Sci</source>. (<year>2008</year>) <volume>6</volume>:<fpage>34</fpage>&#x2013;<lpage>6</lpage>.</citation></ref>
<ref id="ref83"><label>83.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sakamoto</surname> <given-names>R</given-names></name> <name><surname>Tanimoto</surname> <given-names>T</given-names></name> <name><surname>Takahashi</surname> <given-names>K</given-names></name> <name><surname>Hamaki</surname> <given-names>T</given-names></name> <name><surname>Kusumi</surname> <given-names>E</given-names></name> <name><surname>Crump</surname> <given-names>A</given-names></name></person-group>. <article-title>Flourishing Japanese encephalitis, associated with global warming and urbanisation in Asia, demands widespread integrated vaccination programmes</article-title>. <source>Ann Glob Health</source>. (<year>2019</year>) <volume>85</volume>:<fpage>111</fpage>. doi: <pub-id pub-id-type="doi">10.5334/aogh.2580</pub-id>, PMID: <pub-id pub-id-type="pmid">31373473</pub-id></citation></ref>
<ref id="ref84"><label>84.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Walsh</surname> <given-names>MG</given-names></name> <name><surname>Pattanaik</surname> <given-names>A</given-names></name> <name><surname>Vyas</surname> <given-names>N</given-names></name> <name><surname>Saxena</surname> <given-names>D</given-names></name> <name><surname>Webb</surname> <given-names>C</given-names></name> <name><surname>Sawleshwarkar</surname> <given-names>S</given-names></name> <etal/></person-group>. <article-title>High-risk landscapes of Japanese encephalitis virus outbreaks in India converge on wetlands, rain-fed agriculture, wild Ardeidae, and domestic pigs and chickens</article-title>. <source>Int J Epidemiol</source>. (<year>2022</year>) <volume>51</volume>:<fpage>1408</fpage>&#x2013;<lpage>18</lpage>. doi: <pub-id pub-id-type="doi">10.1093/ije/dyac050</pub-id>, PMID: <pub-id pub-id-type="pmid">35355081</pub-id></citation></ref>
<ref id="ref85"><label>85.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ladreyt</surname> <given-names>H</given-names></name> <name><surname>Durand</surname> <given-names>B</given-names></name> <name><surname>Dussart</surname> <given-names>P</given-names></name> <name><surname>Chevalier</surname> <given-names>V</given-names></name></person-group>. <article-title>How central is the domestic pig in the epidemiological cycle of Japanese encephalitis virus? A review of scientific evidence and implications for disease control</article-title>. <source>Viruses</source>. (<year>2019</year>) <volume>11</volume>:<fpage>949</fpage>. doi: <pub-id pub-id-type="doi">10.3390/v11100949</pub-id>, PMID: <pub-id pub-id-type="pmid">31618959</pub-id></citation></ref>
<ref id="ref86"><label>86.</label> <citation citation-type="journal"><person-group person-group-type="author"><name><surname>Tang</surname> <given-names>Q</given-names></name> <name><surname>Deng</surname> <given-names>Z</given-names></name> <name><surname>Tan</surname> <given-names>S</given-names></name> <name><surname>Song</surname> <given-names>G</given-names></name> <name><surname>Zhang</surname> <given-names>H</given-names></name> <name><surname>Ge</surname> <given-names>L</given-names></name></person-group>. <article-title>Prevalence and genetic characteristics of Japanese encephalitis virus among mosquitoes and pigs in Hunan Province, China from 2019 to 2021</article-title>. <source>J Microbiol Biotechnol</source>. (<year>2022</year>) <volume>32</volume>:<fpage>1120</fpage>&#x2013;<lpage>5</lpage>. doi: <pub-id pub-id-type="doi">10.4014/jmb.2207.07068</pub-id>, PMID: <pub-id pub-id-type="pmid">36116917</pub-id></citation></ref>
</ref-list>
</back>
</article>