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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">1664-302X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fmicb.2025.1612124</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Time trend of measles burden on children and adolescents in BRICS-plus countries from 1990 to 2021 and prediction to 2032</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Yuan</surname> <given-names>Hongxia</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2757727/overview"/>
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</contrib>
<contrib contrib-type="author">
<name><surname>Yan</surname> <given-names>Bingju</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2752046/overview"/>
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</contrib>
<contrib contrib-type="author">
<name><surname>Chong</surname> <given-names>Yiran</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Le</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Jiang</surname> <given-names>Yong</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Division of Infectious Diseases, The First Affiliated Hospital of Jinzhou Medical University</institution>, <addr-line>Jinzhou</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Collaborative Innovation Center for Prevention and Control of Zoonoses of Jinzhou Medical University</institution>, <addr-line>Jinzhou</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Cardiology, The First Affiliated Hospital of Jinzhou Medical University</institution>, <addr-line>Jinzhou</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>Division of Hyperbaric Oxygen, The First Affiliated Hospital of Jinzhou Medical University</institution>, <addr-line>Jinzhou</addr-line>, <country>China</country></aff>
<aff id="aff5"><sup>5</sup><institution>Modern Industrial School of Health Management, Jinzhou Medical University</institution>, <addr-line>Jinzhou</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0003"><p>Edited by: Silvia Spoto, Fondazione Policlinico Universitario Campus Bio-Medico, Italy</p></fn>
<fn fn-type="edited-by" id="fn0004"><p>Reviewed by: Domenica Marika Lupoi, Campus Bio-Medico University Hospital, Italy</p><p>Andrea Di Bartolo, Campus Bio-Medico University Hospital, Italy</p><p>Yangyupei Yang, University of Michigan, United States</p></fn>
<corresp id="c001">&#x002A;Correspondence: Yong Jiang, <email>jiangyong@jzmu.edu.cn</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>24</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1612124</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>04</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>04</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Yuan, Yan, Chong, Wang and Jiang.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Yuan, Yan, Chong, Wang and Jiang</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>Measles remains a major disease burden on children and adolescents in BRICS-plus countries (Brazil, Russia, India, China, South Africa, and five others) despite vaccine efficacy. This study aims to clarify the temporal trend of measles burden and forecast the trend in 2032.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>Data from the Global Burden of Disease (GBD) 2021 were utilized to analyze the prevalence, incidence, mortality, and disability-adjusted life years (DALYs) of measles in BRICS-plus countries. In addition, the association between the social development index (SDI) and measles-related indicators of children and adolescents in BRICS-plus countries was analyzed. Joinpoint regression was performed to identify temporal trends, while the age-period-cohort model was used to assess demographic effects. The Bayesian Age-Period-Cohort (BAPC) and Autoregressive Integrated Moving Average (ARIMA) models were utilized to project indicators to 2032.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>From 1990 to 2021, the global prevalence of measles dropped by 92% (with an average annual decline of 6.80%), and the average annual decline rates for incidence, mortality, and DALYs were 6.80, 8.02, and 8.02%, respectively. Saudi Arabia had a 100% reduction in prevalence (with an average annual decrease of 15.20%), Ethiopia had the highest DALYs (124542.02), and Russia had the lowest DALYs (1.74). SDI was negatively linked to the measles prevalence (<italic>R</italic>&#x202F;=&#x202F;&#x2212;0.703, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001), and an increase in SDI significantly reduced the burden of measles. The prevalence of measles was highest among children under 5&#x202F;years old and slightly higher in males than in females. Joinpoint analysis indicated that the global burden of measles declined, but its mortality in China sharply increased from 2019 to 2021 (APC&#x202F;=&#x202F;191.88). The BAPC model predicted that by 2032, the global burden of measles will continue to decline, India will still have the highest prevalence (130.96), Russia may have no new cases, and Brazil and South Africa will have controllable local risks. ARIMA models showed similar trends.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>The declining burden of measles in BRICS-plus countries is correlated with SDI improvement, but low-income countries such as Ethiopia still face a high burden of measles. Children under 5&#x202F;years and regions with low vaccination rates require prioritized interventions. The burden of measles will continue to decrease in the next decade, and increasing vaccination coverage in high-burden countries will help achieve the goal of measles elimination.</p>
</sec>
</abstract>
<kwd-group>
<kwd>measles</kwd>
<kwd>BRICS-plus</kwd>
<kwd>joinpoint</kwd>
<kwd>age-period-cohort model</kwd>
<kwd>Bayesian age-period-cohort</kwd>
<kwd>ARIMA</kwd>
</kwd-group>
<contract-num rid="cn1">2024-MSLH-162</contract-num>
<contract-num rid="cn2">KYTD-2022004</contract-num>
<contract-sponsor id="cn1">Liaoning Province Science and Technology Plan Joint Initiative (Natural Science Fund-General Project)</contract-sponsor>
<contract-sponsor id="cn2">Scientific Research Fund of the First Affiliated Hospital of Jinzhou Medical University</contract-sponsor>
<counts>
<fig-count count="8"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="73"/>
<page-count count="16"/>
<word-count count="10980"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Infectious Agents and Disease</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>Measles is an acute respiratory infectious disease resulting from the measles virus. Its basic reproduction number (<italic>R</italic><sub>0</sub>) is as high as 12&#x2013;18, indicating extremely high infectivity (<xref ref-type="bibr" rid="ref45">Moss, 2017</xref>; <xref ref-type="bibr" rid="ref30">Guerra et al., 2017</xref>). From 2000 to 2018, the global incidence of measles greatly decreased from 145 cases per million people to 49 cases, with a reduction of 66% (<xref ref-type="bibr" rid="ref22">Gasta&#x00F1;aduy et al., 2021</xref>). However, in 2018, global measles cases sharply increased by 167% compared to 2016 (<xref ref-type="bibr" rid="ref51">Patel et al., 2019</xref>). In particular, the number of cases in Africa surged to nearly 290,000. According to the latest estimates by the World Health Organization (WHO) and the United States Centers for Disease Control and Prevention, there were approximately 10.3 million cases of measles worldwide in 2023, a 20% increase compared to 2022 (Measles).<xref ref-type="fn" rid="fn0001"><sup>1</sup></xref> The high infectivity makes measles a chief cause of death among children globally, especially in areas with low vaccination rates (<xref ref-type="bibr" rid="ref35">Lazar et al., 2019</xref>; <xref ref-type="bibr" rid="ref17">Do et al., 2021</xref>; <xref ref-type="bibr" rid="ref62">Stein-Zamir et al., 2024</xref>). In 2018, approximately 350,000 measles cases were reported globally, resulting in about 142,000 deaths, mostly in children under 5&#x202F;years old (<xref ref-type="bibr" rid="ref44">Misin et al., 2020</xref>). The Corona Virus Disease 2019 (COVID-19) pandemic severely disrupted global vaccination programs, leaving millions of children unvaccinated against measles (<xref ref-type="bibr" rid="ref16">Do et al., 2022</xref>), ultimately leading to local resurgences of measles (<xref ref-type="bibr" rid="ref64">Tariq et al., 2022</xref>; <xref ref-type="bibr" rid="ref28">George et al., 2024</xref>). Although measles is a vaccine-preventable disease, it remains a significant cause of death among children and adolescents in low- and middle-income countries (<xref ref-type="bibr" rid="ref65">Wang et al., 2021</xref>; <xref ref-type="bibr" rid="ref52">Portnoy et al., 2019</xref>). Therefore, measles remains a serious public health issue worldwide.</p>
<p>The BRICS has been established since 2009, and its initial members include Brazil, Russia, India, and China. In 2011, South Africa officially joined the organization. By January 1, 2024, Saudi Arabia, Egypt, the United Arab Emirates, Iran, and Ethiopia have also become full members of the BRICS, marking the expansion of the BRICS to BRICS-plus (<xref ref-type="bibr" rid="ref10">Cheng et al., 2025</xref>; <xref ref-type="bibr" rid="ref67">Wang et al., 2025</xref>), representing over half of the global population. They have a relatively high proportion of children and adolescents and face challenges in controlling measles, especially in areas with insufficient vaccination coverage (<xref ref-type="bibr" rid="ref71">Yousif et al., 2022</xref>; <xref ref-type="bibr" rid="ref13">Costa et al., 2020</xref>; <xref ref-type="bibr" rid="ref50">Panda et al., 2020</xref>). Brazil reported over 10,000 cases of measles between 2018 and 2019, mainly among unvaccinated people (<xref ref-type="bibr" rid="ref13">Costa et al., 2020</xref>). Russia and South Africa exhibited a relatively low incidence of measles but still experienced local outbreaks (<xref ref-type="bibr" rid="ref71">Yousif et al., 2022</xref>; <xref ref-type="bibr" rid="ref46">Muscat et al., 2024</xref>). India reported hundreds of thousands of cases each year. In 2017, 2.9 million children did not receive the first dose of measles-containing vaccine (MCV) on time, and the vaccination rate in 2018 was only 86%, far below the expected 95% (<xref ref-type="bibr" rid="ref53">Pustake et al., 2022</xref>). From October 2021 to September 2022, 172 measles outbreaks were reported, with a total of 12,589 cases (<xref ref-type="bibr" rid="ref34">Kumar et al., 2023</xref>). The incidence of measles in China dropped to 0.06 per 100,000 in 2023, no deaths were reported for many consecutive years, and measles is being eliminated in China (<xref ref-type="bibr" rid="ref41">Ma et al., 2019</xref>; <xref ref-type="bibr" rid="ref69">Wang H. et al., 2023</xref>; <xref ref-type="bibr" rid="ref19">Durrheim et al., 2023</xref>). However, local outbreaks remain (<xref ref-type="bibr" rid="ref72">Zhang et al., 2020</xref>; <xref ref-type="bibr" rid="ref38">Li et al., 2019</xref>). Due to vaccine hesitancy, Saudi Arabia, the United Arab Emirates, and Ethiopia are all threatened by measles to varying degrees (<xref ref-type="bibr" rid="ref2">Al-Abdullah, 2018</xref>; <xref ref-type="bibr" rid="ref3">Alamer et al., 2022</xref>; <xref ref-type="bibr" rid="ref6">Barqawi et al., 2024</xref>; <xref ref-type="bibr" rid="ref60">Shimelis et al., 2024</xref>). Reports confirm that Egypt and Iran eliminated measles between 2019 and 2022, but there have been no authoritative reports in recent years. WHO data show that the Middle East remains one of the hotspots for measles outbreaks. The measles epidemic in BRICS-plus countries has not been effectively controlled.</p>
<p>There is currently a lack of comprehensive research on the burden and development trend of measles in BRICS-plus countries. Therefore, this paper aims to analyze the temporal changes in measles burden among children and adolescents in BRICS-plus countries from 1990 to 2021, predict the disease trends to 2032, and strive to provide a scientific basis for decision-makers and public health workers to increase vaccination rates, reduce measles burden, and eradicate measles.</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>Data source and disease definition</title>
<p>The 2021 Global Burden of Disease (GBD) report produced by the Institute of Health Indicators and Evaluation (IHME) provides the burden data of 371 diseases and injuries in 204 countries and regions, including the prevalence, incidence, mortality, and risk factors (<xref ref-type="bibr" rid="ref25">GBD 2021 Demographics Collaborators, 2024</xref>; <xref ref-type="bibr" rid="ref27">GBD 2021 Risk Factors Collaborators, 2024</xref>; <xref ref-type="bibr" rid="ref24">GBD 2021 Causes of Death Collaborators, 2024</xref>; <xref ref-type="bibr" rid="ref26">GBD 2021 Diseases and Injuries Collaborators, 2024</xref>). All data were available to the public free of charge through the website,<xref ref-type="fn" rid="fn0002"><sup>2</sup></xref> including data available in previous reports, statistical modeling, and methodological information. According to GBD 2021, measles is highly contagious and mainly spreads through respiratory droplets. The typical clinical manifestations of measles include fever, cough, runny nose, conjunctivitis, oral mucosal spots, and systemic maculopapules. According to the tenth revision of the International Classification of Diseases, the code for measles is B05.</p>
<p>The GBD 2021 query tool was utilized to collect data on the prevalence, incidence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2021 in the global measles population and among children and adolescents in BRICS-plus countries. Given the data variability, the final estimate represents the average result of 500 calculations, and the boundary of uncertainty intervals was defined by the 2.5th and 97.5th percentiles, resulting in 95% uncertainty intervals (UIs) (<xref ref-type="bibr" rid="ref26">GBD 2021 Diseases and Injuries Collaborators, 2024</xref>). The detailed methodology and modeling process of GBD 2021 have been recorded in other related publications (<xref ref-type="bibr" rid="ref24">GBD 2021 Causes of Death Collaborators, 2024</xref>; <xref ref-type="bibr" rid="ref26">GBD 2021 Diseases and Injuries Collaborators, 2024</xref>). The data set used was anonymous and open to the public free of charge.</p>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Socio-demographic index</title>
<p>Socio-demographic index (SDI) is a composite marker of lag-distributed income per capita, average years of education, and fertility rates among females under 25&#x202F;years (<xref ref-type="bibr" rid="ref26">GBD 2021 Diseases and Injuries Collaborators, 2024</xref>). It ranged from 0 to 1, with 0 indicating the lowest development level and 1 indicating the highest level. According to the SDI value of GBD 2021, countries were divided into five SDI quintiles: low SDI, low-middle SDI, middle-SDI, high-middle SDI, and high-SDI regions.</p>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>DALYs</title>
<p>DALYs is a comprehensive index to quantify the impact of diseases, injuries, and risk factors on health. It comprehensively evaluates the disease burden from disability and mortality, including years of life lost (YLLs) and years lived with disability (YLDs). DALYs are widely used to evaluate the disease burden.</p>
</sec>
<sec id="sec10">
<label>2.4</label>
<title>Ethics approval</title>
<p>The data used were derived from the GBD study, which has been reviewed by the Institutional Review Board of the University of Washington and is available for public inquiry. The analysis of the GBD study followed the principles of accuracy and transparency and the guidelines for health estimation reports (<xref ref-type="bibr" rid="ref26">GBD 2021 Diseases and Injuries Collaborators, 2024</xref>).</p>
</sec>
<sec id="sec11">
<label>2.5</label>
<title>Statistical analysis</title>
<sec id="sec12">
<label>2.5.1</label>
<title>Estimated annual percentage changes and percentage change</title>
<p>From 1990 to 2021, estimated annual percentage changes (EAPCs) were calculated to reflect the fluctuating trend of measles burden among children and adolescents. The trends can be identified in a specific period using EAPCs and their 95% confidence intervals (CIs) (<xref ref-type="bibr" rid="ref8">Cen et al., 2024</xref>). When the upper limit of EAPC (95% CI) was lower than zero, it showed a statistically significant downward trend. On the contrary, when the lower limit of EAPC (95% CI) exceeded zero, it implied a statistically significant upward trend. If EAPC (95% CI) contained zero, it indicated no statistical significance. In addition, percentage changes were utilized to indicate the changes in prevalence, incidence, mortality, and DALYs in 2021 compared with 1990.</p>
</sec>
<sec id="sec13">
<label>2.5.2</label>
<title>Joinpoint regression program</title>
<p>Joinpoint regression analysis can be used to estimate disease trends using the least squares method, effectively avoiding the subjectivity of traditional linear trend analysis. This method aims to identify key turning points in disease burden trends and calculate annual percentage changes for each stage (<xref ref-type="bibr" rid="ref73">Zhang et al., 2022</xref>), which is widely used in epidemiological research to estimate the temporal trends of disease prevalence or mortality (<xref ref-type="bibr" rid="ref66">Wang and Miao, 2024</xref>). It can effectively identify and quantitatively describe the significant change in measles prevalence in the global and BRICS-plus countries. Through this model, the annual percentage change (APC) and its 95% CI were calculated to divide the fashion trends into different periods. To comprehensively appraise the trends, the average annual percentage change (AAPC) was calculated, which covered the comprehensive trend data from 1990 to 2021. APC or AAPC was compared with zero to determine whether the fluctuation trends in different regions were statistically significant. <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05 inferred statistical significance.</p>
</sec>
</sec>
<sec id="sec14">
<label>2.6</label>
<title>Age-period-cohort modeling analysis</title>
<p>Due to the linear relationship between age, period, and cohort, it is difficult to estimate the unique effect set for each age, period, and cohort. Therefore, the age-period-cohort model is used to analyze the temporal trends of different age groups, periods, and birth cohorts (<xref ref-type="bibr" rid="ref73">Zhang et al., 2022</xref>), aiming to study the temporal trend of incidence or mortality with age, period, and cohort (<xref ref-type="bibr" rid="ref20">Fan et al., 2023</xref>). The net drift reflects the percentage change in the population in 1&#x202F;year, while the local drift shows the APC in each age group. The longitudinal age curve shows the specific age rate fitted in the reference cohort, and the periodic deviation has been adjusted. Periodic relative risk (RR) was adjusted by age and nonlinear cohort effect in each period compared to the reference period. Cohort RR was adjusted by age and the nonlinear periodic effect in each cohort compared to the reference cohort. RR &#x003E;1 showed that this factor increased the risk of measles; RR &#x003C;1 showed that this factor reduced the risk of measles. To solve the identification problem caused by the linear relationship between age, period, and cohort, the internal estimator method associated with the age-period-cohort model was employed to overcome the unpredictability of model parameters.</p>
</sec>
<sec id="sec15">
<label>2.7</label>
<title>Bayesian age-period-cohort</title>
<p>The Bayesian age-period-cohort (BAPC) model considers the effects of age, period, and birth cohort on disease outcomes. It uses a second-order random walk (RW 2) model to combine prior information about unknown parameters with sample data to analyze and predict the effects of age, period, and cohort on a given event (such as mortality and disease incidence) in the population (<xref ref-type="bibr" rid="ref31">Ji et al., 2023</xref>). This model has higher accuracy in predicting the disease burden. Therefore, R-package BAPC and integrated nested Laplace approximation were leveraged to predict the burden of measles mortality and DALYs in the initial BRICS-plus countries from 2022 to 2032.</p>
</sec>
<sec id="sec16">
<label>2.8</label>
<title>ARIMA</title>
<p>Autoregressive Integrated Moving Average (ARIMA) model is a commonly used time series analysis method. We used this model to predict the prevalence, incidence, mortality, and DALYs of measles among children and adolescents in the BRICS-plus countries from 2022 to 2032. The model can effectively capture the trend and seasonal change characteristics in time series data by integrating three major elements: autoregression (AR), difference (I), and moving average (MA). The auto.arima function was used to select the optimal model based on the Akaike information criterion, and the Ljung&#x2013;Box test was used to verify whether the residual sequence was white noise.</p>
<p>Joinpoint and age-period-cohort analyses reveal trend characteristics, while the BAPC model clarifies the underlying drivers behind the trends. ARIMA models analyze time series data to eliminate trends and seasonal effects, revealing underlying long-term patterns while controlling for confounding factors.</p>
<p>In this study, the prevalence, incidence, mortality, and DALYs rates were all expressed as the predicted values per 100,000 population with a 95% UI. All analyses were performed in R software and Joinpoint Regression Program 5.3.0 (<xref ref-type="bibr" rid="ref47">National Institutes of Health, n.d.</xref>). <italic>p&#x202F;&#x003C;</italic> 0.05 (two-sided) inferred statistical significance.</p>
</sec>
</sec>
<sec sec-type="results" id="sec17">
<label>3</label>
<title>Results</title>
<sec id="sec18">
<label>3.1</label>
<title>Trends in measles burden in BRICS-plus countries and globally, 1990&#x2013;2021</title>
<p>The changes in measles-related burden to children and adolescents per 100,000 people in BRICS-plus countries and over the world (1990&#x2013;2021) are shown in <xref ref-type="table" rid="tab1">Table 1</xref>; <xref rid="SM1" ref-type="supplementary-material">Supplementary Table 1</xref> and <xref ref-type="fig" rid="fig1">Figures 1</xref>, <xref ref-type="fig" rid="fig2">2</xref>. Between 1990 and 2021, the global annual number of measles declined from 1701026.49 (95% UI: 600598.31 to 3702216.49) to 130392.93 (95% UI: 114767.08 to 147285.75), representing a reduction of 92%, with an average annual decrease of 6.80% (95% CI: &#x2212;7.74 to &#x2212;5.85). Moreover, from 1990 to 2021, the incidence, mortality, and DALYs of measles among children and adolescents were all decreased, and the EAPC was &#x2212;6.80 (95% CI: &#x2212;7.74 to &#x2212;5.85), &#x2212;8.02 (95% CI: &#x2212;8.58 to &#x2212;7.46), and &#x2212;8.02 (95% CI: &#x2212;8.58 to &#x2212;7.46), respectively. The overall measles burden in BRICS-plus countries showed a significant downward trend. The prevalence, incidence, mortality, and DALYs of measles were substantially reduced in Saudi Arabia. For instance, the prevalent cases decreased from 8320.57 (95% UI: 2961.13 to 18219.85) to 33.21 (95% UI: 7.34 to 68.26), representing a reduction of 100%, with an average annual decrease of 15.20% (95% CI: &#x2212;18.73 to &#x2212;11.53), followed by Iran and Egypt (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table 1</xref> and <xref ref-type="fig" rid="fig1">Figures 1</xref>, <xref ref-type="fig" rid="fig2">2</xref>). Brazil had a smaller decline from 1607.74 (95% UI: 1594.94 to 1619.91) to 19.05 (95% UI: 17.57 to 20.51) (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig1">Figures 1</xref>, <xref ref-type="fig" rid="fig2">2</xref>). In addition, Brazil had no significant changes in incidence and mortality, with EAPCs of &#x2212;4.55 (95% CI: &#x2212;16.5 to 9.13) and &#x2212;5.99 (95% CI: &#x2212;11.7 to 0.09), respectively.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Trends in the burden of measles between 1990 and 2021 across the BRICS.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Location</th>
<th align="center" valign="top">Num_1990 (95% UI)</th>
<th align="center" valign="top">Num_2021 (95% UI)</th>
<th align="center" valign="top">Percentage_change (100%)</th>
<th align="center" valign="top">Rate_1990 per 100,000 (95% UI)</th>
<th align="center" valign="top">Rate_2021 per 100,000 (95% UI)</th>
<th align="center" valign="top">EAPC (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="7">Prevalence</td>
</tr>
<tr>
<td align="left" valign="middle">Global</td>
<td align="center" valign="middle">1701026.49 (600598.31&#x2013;3702216.49)</td>
<td align="center" valign="middle">130392.93 (114767.08&#x2013;147285.75)</td>
<td align="center" valign="middle">&#x2212;0.92 (&#x2212;0.81 to &#x2212;0.96)</td>
<td align="center" valign="middle">7531.42 (2659.19&#x2013;16391.83)</td>
<td align="center" valign="middle">494.69 (435.41&#x2013;558.78)</td>
<td align="center" valign="middle">&#x2212;6.8 (&#x2212;7.74 to &#x2212;5.85)</td>
</tr>
<tr>
<td align="left" valign="middle">Brazil</td>
<td align="center" valign="middle">1607.74 (1594.94&#x2013;1619.91)</td>
<td align="center" valign="middle">19.05 (17.57&#x2013;20.51)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.99 to &#x2212;0.99)</td>
<td align="center" valign="middle">239.27 (237.37&#x2013;241.08)</td>
<td align="center" valign="middle">2.98 (2.75&#x2013;3.21)</td>
<td align="center" valign="middle">&#x2212;4.09 (&#x2212;13.46 to 6.29)</td>
</tr>
<tr>
<td align="left" valign="middle">Russian Federation</td>
<td align="center" valign="middle">493.54 (486.47&#x2013;500.79)</td>
<td align="center" valign="middle">0.02 (0&#x2013;0.07)</td>
<td align="center" valign="middle">&#x2212;1 (&#x2212;1 to &#x2212;1)</td>
<td align="center" valign="middle">109.23 (107.66&#x2013;110.83)</td>
<td align="center" valign="middle">0.01 (0&#x2013;0.02)</td>
<td align="center" valign="middle">&#x2212;13.01 (&#x2212;18.4 to &#x2212;7.27)</td>
</tr>
<tr>
<td align="left" valign="middle">India</td>
<td align="center" valign="middle">597505.81 (205169.4&#x2013;1295779.55)</td>
<td align="center" valign="middle">12431.4 (8325.82&#x2013;16471.2)</td>
<td align="center" valign="middle">&#x2212;0.98 (&#x2212;0.96 to &#x2212;0.99)</td>
<td align="center" valign="middle">14558.53 (4999.06&#x2013;31572.33)</td>
<td align="center" valign="middle">248.34 (166.33&#x2013;329.05)</td>
<td align="center" valign="middle">&#x2212;8.06 (&#x2212;10.16 to &#x2212;5.9)</td>
</tr>
<tr>
<td align="left" valign="middle">China</td>
<td align="center" valign="middle">2289.96 (2275.22&#x2013;2305.94)</td>
<td align="center" valign="middle">18.97 (17.44&#x2013;20.42)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.99 to &#x2212;0.99)</td>
<td align="center" valign="middle">51.45 (51.12&#x2013;51.81)</td>
<td align="center" valign="middle">0.57 (0.52&#x2013;0.61)</td>
<td align="center" valign="middle">&#x2212;9.85 (&#x2212;13.07 to &#x2212;6.5)</td>
</tr>
<tr>
<td align="left" valign="middle">South Africa</td>
<td align="center" valign="middle">20345.07 (7228.8&#x2013;44991.81)</td>
<td align="center" valign="middle">565.76 (374.86&#x2013;794.02)</td>
<td align="center" valign="middle">&#x2212;0.97 (&#x2212;0.95 to &#x2212;0.98)</td>
<td align="center" valign="middle">11545.46 (4102.21&#x2013;25532.04)</td>
<td align="center" valign="middle">284.05 (188.2&#x2013;398.64)</td>
<td align="center" valign="middle">&#x2212;6.05 (&#x2212;8.62 to &#x2212;3.41)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Incidence</td>
</tr>
<tr>
<td align="left" valign="middle">Global</td>
<td align="center" valign="middle">62087466.81 (21921838.14&#x2013;135130901.73)</td>
<td align="center" valign="middle">4759421.16 (4189082.17&#x2013;5376013.35)</td>
<td align="center" valign="middle">&#x2212;0.92 (&#x2212;0.81 to &#x2212;0.96)</td>
<td align="center" valign="middle">274896.67 (97060.5&#x2013;598301.67)</td>
<td align="center" valign="middle">18056.56 (15892.77&#x2013;20395.82)</td>
<td align="center" valign="middle">&#x2212;6.8 (&#x2212;7.74 to &#x2212;5.85)</td>
</tr>
<tr>
<td align="left" valign="middle">Brazil</td>
<td align="center" valign="middle">58682.64 (58215.15&#x2013;59126.74)</td>
<td align="center" valign="middle">695.34 (641.4&#x2013;748.54)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.99 to &#x2212;0.99)</td>
<td align="center" valign="middle">8733.5 (8663.92&#x2013;8799.59)</td>
<td align="center" valign="middle">108.79 (100.35&#x2013;117.11)</td>
<td align="center" valign="middle">&#x2212;4.55 (&#x2212;16.5 to 9.13)</td>
</tr>
<tr>
<td align="left" valign="middle">Russian Federation</td>
<td align="center" valign="middle">18014.09 (17756.01&#x2013;18278.68)</td>
<td align="center" valign="middle">0.83 (0&#x2013;2.55)</td>
<td align="center" valign="middle">&#x2212;1 (&#x2212;1 to &#x2212;1)</td>
<td align="center" valign="middle">3986.74 (3929.62&#x2013;4045.3)</td>
<td align="center" valign="middle">0.25 (0&#x2013;0.75)</td>
<td align="center" valign="middle">&#x2212;13.2 (&#x2212;18.69 to &#x2212;7.34)</td>
</tr>
<tr>
<td align="left" valign="middle">India</td>
<td align="center" valign="middle">21808962.03 (7488683.15&#x2013;47295953.57)</td>
<td align="center" valign="middle">453746.1 (303892.43&#x2013;601198.72)</td>
<td align="center" valign="middle">&#x2212;0.98 (&#x2212;0.96 to &#x2212;0.99)</td>
<td align="center" valign="middle">531386.41 (182465.56&#x2013;1152389.87)</td>
<td align="center" valign="middle">9064.55 (6070.9&#x2013;12010.23)</td>
<td align="center" valign="middle">&#x2212;8.06 (&#x2212;10.16 to &#x2212;5.9)</td>
</tr>
<tr>
<td align="left" valign="middle">China</td>
<td align="center" valign="middle">83583.39 (83045.52&#x2013;84166.68)</td>
<td align="center" valign="middle">692.45 (636.52&#x2013;745.15)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.99 to &#x2212;0.99)</td>
<td align="center" valign="middle">1878.1 (1866.02&#x2013;1891.21)</td>
<td align="center" valign="middle">20.71 (19.04&#x2013;22.29)</td>
<td align="center" valign="middle">&#x2212;9.85 (&#x2212;13.07 to &#x2212;6.5)</td>
</tr>
<tr>
<td align="left" valign="middle">South Africa</td>
<td align="center" valign="middle">742594.96 (263851.24&#x2013;1642201.03)</td>
<td align="center" valign="middle">20650.39 (13682.36&#x2013;28981.77)</td>
<td align="center" valign="middle">&#x2212;0.97 (&#x2212;0.95 to &#x2212;0.98)</td>
<td align="center" valign="middle">421409.18 (149730.8&#x2013;931919.32)</td>
<td align="center" valign="middle">10367.7 (6869.34&#x2013;14550.54)</td>
<td align="center" valign="middle">&#x2212;6.05 (&#x2212;8.62 to &#x2212;3.41)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Mortality</td>
</tr>
<tr>
<td align="left" valign="middle">Global</td>
<td align="center" valign="middle">670151.3 (249955.15&#x2013;1345889.86)</td>
<td align="center" valign="middle">55401.2 (31949.91&#x2013;85916.54)</td>
<td align="center" valign="middle">&#x2212;0.92 (&#x2212;0.87 to &#x2212;0.94)</td>
<td align="center" valign="middle">2967.14 (1106.69&#x2013;5959.02)</td>
<td align="center" valign="middle">210.18 (121.21&#x2013;325.95)</td>
<td align="center" valign="middle">&#x2212;8.02 (&#x2212;8.58 to &#x2212;7.46)</td>
</tr>
<tr>
<td align="left" valign="middle">Brazil</td>
<td align="center" valign="middle">276.83 (216.69&#x2013;333.2)</td>
<td align="center" valign="middle">0.37 (0.13&#x2013;0.77)</td>
<td align="center" valign="middle">&#x2212;1 (&#x2212;1 to &#x2212;1)</td>
<td align="center" valign="middle">41.2 (32.25&#x2013;49.59)</td>
<td align="center" valign="middle">0.06 (0.02&#x2013;0.12)</td>
<td align="center" valign="middle">&#x2212;5.99 (&#x2212;11.7 to 0.09)</td>
</tr>
<tr>
<td align="left" valign="middle">Russian Federation</td>
<td align="center" valign="middle">9.05 (5.97&#x2013;13.56)</td>
<td align="center" valign="middle">0.02 (0&#x2013;0.05)</td>
<td align="center" valign="middle">&#x2212;1 (&#x2212;1 to &#x2212;1)</td>
<td align="center" valign="middle">2 (1.32&#x2013;3)</td>
<td align="center" valign="middle">0.01 (0&#x2013;0.01)</td>
<td align="center" valign="middle">&#x2212;12.05 (&#x2212;14.97 to &#x2212;9.04)</td>
</tr>
<tr>
<td align="left" valign="middle">India</td>
<td align="center" valign="middle">160229.55 (58662.92&#x2013;317595.15)</td>
<td align="center" valign="middle">1106.66 (532.65&#x2013;2053.65)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.99 to &#x2212;0.99)</td>
<td align="center" valign="middle">3904.07 (1429.35&#x2013;7738.37)</td>
<td align="center" valign="middle">22.11 (10.64&#x2013;41.03)</td>
<td align="center" valign="middle">&#x2212;11.29 (&#x2212;13.33 to &#x2212;9.2)</td>
</tr>
<tr>
<td align="left" valign="middle">China</td>
<td align="center" valign="middle">291.35 (191.19&#x2013;408.59)</td>
<td align="center" valign="middle">13.34 (8.09&#x2013;20.88)</td>
<td align="center" valign="middle">&#x2212;0.95 (&#x2212;0.96 to &#x2212;0.95)</td>
<td align="center" valign="middle">6.55 (4.3&#x2013;9.18)</td>
<td align="center" valign="middle">0.4 (0.24&#x2013;0.62)</td>
<td align="center" valign="middle">&#x2212;12.23 (&#x2212;14.73 to &#x2212;9.66)</td>
</tr>
<tr>
<td align="left" valign="middle">South Africa</td>
<td align="center" valign="middle">2874.36 (999.4&#x2013;6210.42)</td>
<td align="center" valign="middle">38.46 (18.66&#x2013;76.19)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.98 to &#x2212;0.99)</td>
<td align="center" valign="middle">1631.15 (567.14&#x2013;3524.3)</td>
<td align="center" valign="middle">19.31 (9.37&#x2013;38.25)</td>
<td align="center" valign="middle">&#x2212;8.25 (&#x2212;10.8 to &#x2212;5.62)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">DALYs</td>
</tr>
<tr>
<td align="left" valign="middle">Global</td>
<td align="center" valign="middle">58581088.94 (21863110.63&#x2013;117684915.66)</td>
<td align="center" valign="middle">4839654.44 (2792705.27&#x2013;7500361.47)</td>
<td align="center" valign="middle">&#x2212;0.92 (&#x2212;0.87 to &#x2212;0.94)</td>
<td align="center" valign="middle">259371.93 (96800.48&#x2013;521058.32)</td>
<td align="center" valign="middle">18360.95 (10595.12&#x2013;28455.29)</td>
<td align="center" valign="middle">&#x2212;8.02 (&#x2212;8.58 to &#x2212;7.46)</td>
</tr>
<tr>
<td align="left" valign="middle">Brazil</td>
<td align="center" valign="middle">24427.27 (19172.82&#x2013;29377.2)</td>
<td align="center" valign="middle">33.67 (12.58&#x2013;69.32)</td>
<td align="center" valign="middle">&#x2212;1 (&#x2212;1 to &#x2212;1)</td>
<td align="center" valign="middle">3635.41 (2853.41&#x2013;4372.09)</td>
<td align="center" valign="middle">5.27 (1.97&#x2013;10.84)</td>
<td align="center" valign="middle">&#x2212;12.4 (&#x2212;21.85 to &#x2212;1.82)</td>
</tr>
<tr>
<td align="left" valign="middle">Russian Federation</td>
<td align="center" valign="middle">828.04 (559.07&#x2013;1218.13)</td>
<td align="center" valign="middle">1.74 (0.14&#x2013;4.41)</td>
<td align="center" valign="middle">&#x2212;1 (&#x2212;1 to &#x2212;1)</td>
<td align="center" valign="middle">183.25 (123.73&#x2013;269.59)</td>
<td align="center" valign="middle">0.51 (0.04&#x2013;1.31)</td>
<td align="center" valign="middle">&#x2212;12.22 (&#x2212;15.26 to &#x2212;9.07)</td>
</tr>
<tr>
<td align="left" valign="middle">India</td>
<td align="center" valign="middle">13987643.96 (5127269.6&#x2013;27707806.02)</td>
<td align="center" valign="middle">97011.63 (46424.37&#x2013;179433.74)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.99 to &#x2212;0.99)</td>
<td align="center" valign="middle">340816.03 (124928.52&#x2013;675114.73)</td>
<td align="center" valign="middle">1938.01 (927.43&#x2013;3584.57)</td>
<td align="center" valign="middle">&#x2212;11.27 (&#x2212;13.31 to &#x2212;9.19)</td>
</tr>
<tr>
<td align="left" valign="middle">China</td>
<td align="center" valign="middle">25541.6 (16818.05&#x2013;35827.67)</td>
<td align="center" valign="middle">1158.28 (701.83&#x2013;1814.5)</td>
<td align="center" valign="middle">&#x2212;0.95 (&#x2212;0.96 to &#x2212;0.95)</td>
<td align="center" valign="middle">573.91 (377.9&#x2013;805.04)</td>
<td align="center" valign="middle">34.65 (20.99&#x2013;54.28)</td>
<td align="center" valign="middle">&#x2212;12.19 (&#x2212;14.69 to &#x2212;9.61)</td>
</tr>
<tr>
<td align="left" valign="middle">South Africa</td>
<td align="center" valign="middle">252020.79 (87776.97&#x2013;543866)</td>
<td align="center" valign="middle">3339.01 (1616.75&#x2013;6574.21)</td>
<td align="center" valign="middle">&#x2212;0.99 (&#x2212;0.98 to &#x2212;0.99)</td>
<td align="center" valign="middle">143017.23 (49811.84&#x2013;308634.1)</td>
<td align="center" valign="middle">1676.38 (811.7&#x2013;3300.64)</td>
<td align="center" valign="middle">&#x2212;8.23 (&#x2212;10.79 to &#x2212;5.6)</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Temporal trend of disease burden of children and adolescents in global and BRICS-plus countries. <bold>(A)</bold> Percentage change in cases of prevalence, incidence, mortality, and DALYs in 1990 and 2021. <bold>(B)</bold> The EAPC of prevalence, incidence, mortality, and DALYs rates from 1990 to 2021. DALYs, disability-adjusted life years; EAPC, estimated annual percentage change.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g001.tif">
<alt-text content-type="machine-generated">Two bar charts labeled A and B compare global and country-specific data on disease metrics. Chart A displays percentage change for prevalence, incidence, deaths, and DALYs globally and in ten countries, all showing negative change. Chart B indicates EAPC of the rate for the same metrics, with most values below zero. Both charts highlight declines across all categories, with variations per country.</alt-text>
</graphic>
</fig>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Temporal trend of disease burden of children and adolescents in BRICS-plus countries. <bold>(A)</bold> Percentage change in prevalent cases. <bold>(B)</bold> Percentage change in incident cases. <bold>(C)</bold> Percentage change in death cases. <bold>(D)</bold> Percentage change in DALYs cases. DALYs, disability-adjusted life years.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g002.tif">
<alt-text content-type="machine-generated">World maps in four panels (A, B, C, D) illustrating changes in pandemic-related cases. Each panel shows variations in different categories: A) Prevalence cases, B) Incidence cases, C) Deaths, and D) Disability-adjusted life years. Color gradients indicate changes in various countries, with specific focus on Brazil, South Africa, China/India, and a group including KSA, Egypt, UAE, Ethiopia, Iran, and Russia. Insets provide detailed regional views for these countries. Each map uses different colors to represent differing levels of change.</alt-text>
</graphic>
</fig>
<p>In 2021, Ethiopia had the highest measles-associated DALYs at 124542.02 (95% UI: 64010.84 to 219173.95). In contrast, the Russian Federation reported a minimal count at 1.74 (95% UI: 0.14 to 4.41). Ethiopia also had the highest DALYs rate per 100,000 population at 21773.84 (95% UI: 11191.1 to 38318.47), while the Russian Federation presented the lowest rate per 100,000 population at 0.51 (95% UI: 0.04 to 1.31). These results showed that the burden of measles on children and adolescents in BRICS-plus countries continued to decrease (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref>; <xref ref-type="fig" rid="fig1">Figures 1</xref>, <xref ref-type="fig" rid="fig2">2</xref>). The trends of the prevalence, incidence, mortality, and DALYs of measles in different regions over time are displayed in <xref ref-type="fig" rid="fig3">Figure 3</xref>. The prevalence, incidence, mortality, and DALYs of measles in the global scope and BRICS-plus countries gradually decreased. The downward trend was particularly significant in India and remained relatively stable in other countries.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>The cases of prevalence, incidence, deaths, and DALYs from 1990 to 2021. <bold>(A)</bold> Prevalence cases. <bold>(B)</bold> Incidence cases. <bold>(C)</bold> Mortality cases. <bold>(D)</bold> DALYs cases. DALYs, disability-adjusted life years.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g003.tif">
<alt-text content-type="machine-generated">Four line graphs labeled A, B, C, and D depict global health data from 1990 to 2020. Each graph shows data for various countries and regions, including Brazil, Russia, India, China, and others. Graph A displays cases of prevalence, B shows cases of incidence, C illustrates cases of deaths, and D represents cases of disability-adjusted life years (DALYs). Each graph has an inset highlighting data trends in smaller line variations. The overall trends indicate a decline in cases over time for most categories.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec19">
<label>3.2</label>
<title>Link between the measles burden and SDI</title>
<p>Significant regional differences were observed in the link between SDI and measles burden in BRICS-plus countries. In 2021, as the SDI level improved in 204 countries and regions worldwide, the burden of measles among children and adolescents in BRICS-plus countries decreased significantly, indicating a significant negative correlation between SDI and measles. From 1990 to 2021, the prevalence of measles among children and adolescents in BRICS-plus countries showed a downward trend with the increase of SDI (<italic>R</italic>&#x202F;=&#x202F;&#x2212;0.703, <italic>p&#x202F;&#x003C;</italic> 0.001). The downward trend was most apparent when SDI was between 0.00 and 0.50; countries with high-middle SDI (e.g., Russia and China) and middle SDI (e.g., Brazil and Iran) showed lower-than-expected measles prevalence (<xref ref-type="fig" rid="fig4">Figure 4A</xref>). Moreover, from 1990 to 2021, the incidence (<italic>R</italic>&#x202F;=&#x202F;&#x2212;0.703, <italic>p&#x202F;&#x003C;</italic> 0.001), mortality (<italic>R</italic>&#x202F;=&#x202F;&#x2212;0.687, <italic>p&#x202F;&#x003C;</italic> 0.001), and DALYs of measles (<italic>R</italic>&#x202F;=&#x202F;&#x2212;0.687, <italic>p&#x202F;&#x003C;</italic> 0.001) were negatively correlated with SDI (<xref ref-type="fig" rid="fig4">Figures 4B</xref>&#x2013;<xref ref-type="fig" rid="fig4">D</xref>).</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>The associations between the SDI and burden of measles (per 100,000 population) in children and adolescents in BRICS-plus countries. <bold>(A)</bold> Prevalence rates. <bold>(B)</bold> Incidence rates. <bold>(C)</bold> Mortality rates. <bold>(D)</bold> DALYs rates. SDI, socio-demographic index; DALYs, disability-adjusted life years.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g004.tif">
<alt-text content-type="machine-generated">Four scatter plots labeled A, B, C, and D, display health data against the Socio-Demographic Index for different countries. Each plot features a black trend line. Plot A shows prevalence rates per 100,000 population, B shows incidence rates, C shows death rates, and D shows DALYs rates, each compared to the Socio-Demographic Index. A color-coded legend indicates countries, including Brazil, Egypt, and others, with negative correlation coefficients and p-values indicated.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec20">
<label>3.3</label>
<title>Age and sex patterns</title>
<p>Measles prevalence was higher globally in the under-five age group, with females (17.09 per 100,000) having a slightly higher prevalence than males (16.88 per 100,000). In BRICS-plus countries, the prevalence of measles was highest among children under 5&#x202F;years, especially in Ethiopia (19.52 per 100,000 for males and 19.34 per 100,000 for females), followed by South Africa and India. Russia, on the other hand, showed the lowest prevalence. In addition, among children and adolescents in BRICS-plus countries, the prevalence rate of measles decreased with age (<xref ref-type="fig" rid="fig5">Figure 5A</xref> and <xref rid="SM1" ref-type="supplementary-material">Supplementary Table 2</xref>). The incidence rate of measles was higher in the under-five age group globally and in BRICS-plus countries. According to the data in 2021, Ethiopia showed the most new cases of measles, with males (712.52 per 100,000) slightly higher than females (705.91 per 100,000) (<xref ref-type="fig" rid="fig5">Figure 5B</xref> and <xref rid="SM1" ref-type="supplementary-material">Supplementary Table 2</xref>). The mortality rate of measles in the under-five age group was the highest in Ethiopia, followed by South Africa and India. However, the overall measles mortality rate was low globally and in BRICS-plus countries (<xref ref-type="fig" rid="fig5">Figure 5C</xref> and <xref rid="SM1" ref-type="supplementary-material">Supplementary Table 2</xref>). The analysis of DALYs rate showed a similar trend to the prevalence. DALYs rate gradually decreased with age. Ethiopia showed the largest difference in DALYs rate between sexes among children under 5&#x202F;years (females 630.01 per 100,000 vs. males 820.53 per 100,000), followed by the age group of 5&#x2013;9&#x202F;years old (females 45.74 per 100,000 vs. males 33.97 per 100,000) and the age group of 10&#x2013;14&#x202F;years old (females 13.07 per 100,000 vs. males 11.88 per 100,000) (<xref ref-type="fig" rid="fig5">Figure 5D</xref> and <xref rid="SM1" ref-type="supplementary-material">Supplementary Table 2</xref>).</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Sex- and age-structured analysis of measles burden in 2021. <bold>(A)</bold> Prevalence rates. <bold>(B)</bold> Incidence rates. <bold>(C)</bold> Mortality rates. <bold>(D)</bold> DALYs rates. DALYs, disability-adjusted life years.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g005.tif">
<alt-text content-type="machine-generated">Four panels of bar graphs depict health data by country and sex. Panel A shows prevalence rates, panel B shows incidence rates, panel C shows death rates, and panel D shows disability-adjusted life years (DALYs) rates per 100,000 population. Each panel compares data for females (blue bars) and males (orange bars) across various countries, including Global, Brazil, Russia, India, China, South Africa, Saudi Arabia, Egypt, UAE, Iran, and Ethiopia. Data suggest visible differences between sexes across all metrics.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec21">
<label>3.4</label>
<title>Temporal joinpoint analysis</title>
<p>Joinpoint regression analysis showed a downward trend in the global prevalence of measles in children and adolescents from 1990 to 2021 (AAPC&#x202F;=&#x202F;&#x2212;7.94; 95% CI: &#x2212;8.58 to &#x2212;7.3; <italic>p</italic>&#x202F;=&#x202F;0.001). However, the change in the prevalence among female patients between 2008 and 2011 was not significant (APC&#x202F;=&#x202F;&#x2212;1.68; 95% CI: &#x2212;12.25 to 10.16; <italic>p</italic>&#x202F;=&#x202F;0.758) (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table 3</xref>). Incidence and prevalence showed similar trends. Notably, changes in mortality and DALYs were not significant between 2008 and 2011 for either male or female patients, while other indicators demonstrated consistent trends with prevalence and incidence (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table 3</xref>). <xref ref-type="fig" rid="fig6">Figure 6</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref> present joinpoint regression analyses of the prevalence, incidence, mortality, and DALYs of measles among children and adolescents in BRICS-plus countries from 1990 to 2021. The measles burden on children and adolescents in BRICS-plus countries showed a decreasing trend. However, the burden in China, South Africa, the United Arab Emirates, and Iran fluctuated significantly over time while relatively stable in other countries. With a large population base, India showed a significant downward trend in overall disease and measles burden at all stages. Despite the overall downward trend in China, the mortality (APC&#x202F;=&#x202F;191.88; 95% CI: 4.47 to 715.47; <italic>p</italic>&#x202F;=&#x202F;0.042) and DALYs of measles (APC&#x202F;=&#x202F;183.99; 95% CI: 0.28 to 704.23; <italic>p</italic>&#x202F;=&#x202F;0.049) were increased in children and adolescents between 2019 and 2021 (<xref ref-type="fig" rid="fig6">Figure 6</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref>; <xref rid="SM1" ref-type="supplementary-material">Supplementary Tables 4&#x2013;13</xref>).</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Joinpoint regression analysis of measles burden among children and adolescents in the BRICS countries. <bold>(A)</bold> Prevalence cases. <bold>(B)</bold> Incidence cases. <bold>(C)</bold> Mortality cases. <bold>(D)</bold> DALYs cases. DALYs, disability-adjusted life years.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g006.tif">
<alt-text content-type="machine-generated">Four rows, labeled A to D, each containing four graphs with different line plots on a grid. Each graph has a legend and axes labeled as "time" and "temperature". The patterns vary in each set, displaying different data trends and line colors.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec22">
<label>3.5</label>
<title>Temporal trend of measles burden in different age groups</title>
<p>Most measles cases worldwide were recorded in patients under 5&#x202F;years old, and a similar distribution was observed in almost all BRICS-plus countries (<xref ref-type="fig" rid="fig7">Figure 7A</xref>; <xref ref-type="supplementary-material" rid="SM2">Supplementary Figures S2A</xref>&#x2013;<xref ref-type="supplementary-material" rid="SM4">S4A</xref>). From 1990 to 2021, the age distribution of measles cases in the world and BRICS-plus countries was relatively stable, mainly concentrated in people under 5&#x202F;years old. However, with time, the prevalence, incidence, mortality, and DALYs of measles gradually declined. Among BRICS-plus countries, the number of measles cases in India and Ethiopia was relatively stable, while Russia showed a certain degree of fluctuation.</p>
<fig position="float" id="fig7">
<label>Figure 7</label>
<caption>
<p>Age distribution of measles prevalence and age-period-cohort effects in the BRICS-plus countries across SDI quintiles. <bold>(A)</bold> Temporal change in the relative proportion of measles across age groups (&#x003C;5, 5&#x2013;9, 10&#x2013;14, 15&#x2013;19&#x202F;years), 1990&#x2013;2021. <bold>(B)</bold> Age effects are shown by the fitted longitudinal age curves of prevalence rate (per 100,000 person-years) adjusted for period deviations. <bold>(C)</bold> Period effects are shown by the relative risk of prevalence rate (prevalence rate ratio) and computed as the ratio of age-specific rates with the referent period set at 2002&#x2013;2006. <bold>(D)</bold> Cohort effects are shown by the relative risk of prevalence rate and computed as the ratio of age-specific rates with the referent cohort set in 1997. The dots and shaded areas denote prevalence rates or rate ratios and their corresponding 95% CIs. SDI, socio-demographic index; CIs, confidence intervals.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g007.tif">
<alt-text content-type="machine-generated">The image contains four sections labeled A, B, C, and D. Section A displays multiple stacked bar charts with orange and blue segments. Section B consists of line graphs with shaded areas under the curves. Sections C and D show various line graphs with data points and error bars. Each section appears to illustrate different data visualizations, possibly related to statistical analysis or experimental results. All graphs include labeled axes.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec23">
<label>3.6</label>
<title>The effect of age, period, and cohort on prevalence, incidence, mortality, and DALYs</title>
<p><xref ref-type="fig" rid="fig7">Figures 7B</xref>&#x2013;<xref ref-type="fig" rid="fig7">D</xref>; <xref ref-type="supplementary-material" rid="SM2">Supplementary Figures S2B&#x2013;D</xref>&#x2013;<xref ref-type="supplementary-material" rid="SM4">S4B&#x2013;D</xref> present the age-period-cohort effect estimates for measles in children and adolescents in BRICS-plus countries. Overall, cohort effects were similar in all countries. After adjusting for period effects, the prevalence and incidence of measles decreased with age in the reference cohort. Almost all countries, except Brazil, showed similar age effects. They leveled off, showing an &#x201C;L-shaped&#x201D; curve. In both male and female individuals, the highest prevalence and incidence of measles were found in the 0&#x2013;5 age group, while BRICS-plus countries, except Brazil, showed lowered prevalence and incidence of measles after 10&#x202F;years old (<xref ref-type="fig" rid="fig7">Figure 7B</xref>; <xref ref-type="supplementary-material" rid="SM2">Supplementary Figure S2B</xref>). <xref ref-type="fig" rid="fig7">Figure 7C</xref> illustrates the estimated cyclical effects by sex over the entire study period. Brazil and Saudi Arabia showed an overall downward trend but a slight rebound between 2017 and 2022. However, the prevalence of measles in Brazil was greatly lower in females than in males, while the opposite pattern was revealed in Saudi Arabia. Russia had the lowest prevalence of measles between 2007 and 2012; India and Ethiopia showed a clear downward trend, with the risk remaining below 1 since 2007; and the risk also remained below 1 in China, except for 2002&#x2013;2007. The risk remained consistently above 1 in South Africa until 1997 and stabilized at 1 and below since 2002, with a slight upward trend between 2017 and 2022. Egypt consistently had a risk above 1 between 2012 and 2017, showing a slight upward trend. The United Arab Emirates primarily maintained its risk above 1, although it eventually showed a downward trend. Iran had a risk above 1 from 1997 to 2002, trending below 1 since then, and its prevalence remained stable since 2012. <xref ref-type="supplementary-material" rid="SM2">Supplementary Figure S2C</xref> illustrates the trend in measles incidence among children and adolescents between 1990 and 2021. The incidence in all age groups showed an almost downward trend over time. In particular, the incidence was higher in the 0&#x2013;5-year age group and lower in the age groups &#x2265;10&#x202F;years. <xref ref-type="fig" rid="fig7">Figure 7D</xref>; <xref ref-type="supplementary-material" rid="SM2">Supplementary Figure S2D</xref> illustrate cohort-based changes in prevalence and incidence for specific age groups. The prevalence and incidence of measles showed a gradual decrease with age. <xref ref-type="supplementary-material" rid="SM3">Supplementary Figures S3B&#x2013;D</xref>, <xref ref-type="supplementary-material" rid="SM4">S4B&#x2013;D</xref> illustrate changes in mortality and DALYs.</p>
</sec>
<sec id="sec24">
<label>3.7</label>
<title>Prediction of measles burden on children and adolescents in the globe and BRICS-plus countries in 2032</title>
<p>BAPC model predictions indicated that during this period, the prevalence and incidence of measles will show a downward trend worldwide. By 2032, the number of overall measles cases will reach 183319.78 (95% UI: &#x2212;321397.99 to 688037.55) (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table 14</xref>), and the number of new cases is expected to be 6273361.11 (95% UI: &#x2212;11029405.35 to 23576127.56) (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table 15</xref>). <xref ref-type="fig" rid="fig8">Figure 8A</xref> shows that the prevalence and number of patients in the initial BRICS countries will continue to decrease. India has the highest prevalence, followed by China, Brazil, and South Africa. In Russia, no one is expected to be infected with measles. <xref ref-type="fig" rid="fig8">Figure 8B</xref> shows that the incidence and number of patients in the initial BRICS countries will continue to decrease. The incidence trend is similar in China and India, two countries with large populations, but India shows slightly severe situations. There will be a few new cases in Brazil and South Africa, while Russia shows no new cases. The ARIMA model further confirmed the overall trend in the prevalence and incidence in the five countries mentioned above (<xref ref-type="supplementary-material" rid="SM5">Supplementary Figure S5</xref>).</p>
<fig position="float" id="fig8">
<label>Figure 8</label>
<caption>
<p>BAPC model prediction of measles burden of children and adolescents in the initial BRICS countries in 2032. <bold>(A)</bold> Forecasted prevalence for measles. <bold>(B)</bold> Forecasted incidence for measles.</p>
</caption>
<graphic xlink:href="fmicb-16-1612124-g008.tif">
<alt-text content-type="machine-generated">Comparison of histograms for Brazil, Russia, India, China, and South Africa in two panels, A and B. Each country's histogram displays data distribution with insets showing finer details on a different scale. Brazil and Russia have prominent peaks with some outliers, while India, China, and South Africa show more evenly spread distributions with additional spikes.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="sec25">
<label>4</label>
<title>Discussion</title>
<p>Measles is a major cause of death among children in low- and middle-income countries (<xref ref-type="bibr" rid="ref63">Stevens et al., 2015</xref>; <xref ref-type="bibr" rid="ref40">Lopez et al., 2006</xref>). This study utilized the GBD database 2021, combined with joinpoint analysis and age-period-cohort models, to reveal the burden of measles on children and adolescents globally and in BRICS-plus countries from 1990 to 2021. Additionally, the BAPC model was employed to predict the trend of measles from 2022 to 2032.</p>
<sec id="sec26">
<label>4.1</label>
<title>Global and BRICS-plus trends in measles burden</title>
<p>The results showed that the global measles burden among children and adolescents declined significantly during 1990&#x2013;2021, with the number of measles cases decreasing from 1701026.49 cases in 1990 to 130392.93 cases in 2021, a decrease of 92%, and an average annual decrease of 6.80%. This trend may be related to the increase in global vaccination coverage and public health interventions (<xref ref-type="bibr" rid="ref37">Leong and Wilder-Smith, 2019</xref>; <xref ref-type="bibr" rid="ref5">Auzenbergs et al., 2023</xref>). However, there was no significant decline in the prevalence of measles in female patients during 2008&#x2013;2011, and mortality and DALYs also stagnated, which may be related to the contraction of public health investments in low- and middle-income countries (<xref ref-type="bibr" rid="ref4">Andrietta et al., 2020</xref>; <xref ref-type="bibr" rid="ref1">Addis et al., 2024</xref>). The burden of measles in the BRICS-plus countries also showed a significant downward trend. Saudi Arabia showed the most significant decrease in measles prevalence, which reached 100%, with an average annual decrease of 15.20%; in Brazil, the average annual decrease in measles prevalence was 4.09%. Ethiopia showed the highest DALYs (124542.02); the Russian Federation showed the lowest DALYs with only 1.74, indicating that low-income country Ethiopia suffers from a heavy burden of measles, while the high-income country Russia has a very low burden of measles.</p>
<p>Previous studies have confirmed that the risk of measles outbreaks is significantly elevated in areas with less than 95% measles vaccination coverage, leading to a surge in YLLs and YLDs (<xref ref-type="bibr" rid="ref21">Fu et al., 2021</xref>; <xref ref-type="bibr" rid="ref29">Gianfredi et al., 2020</xref>). Supplementary immunization targeting specific populations is effective in controlling measles incidence (<xref ref-type="bibr" rid="ref33">Kuddus et al., 2023</xref>; <xref ref-type="bibr" rid="ref55">Sato and Haraguchi, 2021</xref>). Between 2000 and 2017, the average annual number of deaths declined by 80% globally due to universal access to MCV (<xref ref-type="bibr" rid="ref14">Dabbagh et al., 2018</xref>). However, millions of children missed vaccination during the COVID-19 pandemic, resulting in an 18% increase in the number of measles cases and a 43% increase in deaths globally in 2022 compared to 2021, showing signs of an epidemic rebound (<xref ref-type="bibr" rid="ref43">Minta et al., 2023</xref>). China reported an abnormal surge in measles mortality and DALYs among children and adolescents in 2019&#x2013;2021, which may be associated with a decline in routine immunization rates during COVID-19, missed vaccination of migrant children, and strained healthcare resources (<xref ref-type="bibr" rid="ref70">Wu et al., 2020</xref>; <xref ref-type="bibr" rid="ref36">Lee et al., 2022</xref>; <xref ref-type="bibr" rid="ref39">Locke et al., 2023</xref>). Recent research findings (<xref ref-type="bibr" rid="ref9">Chen et al., 2025</xref>) indicate that during the COVID-19 pandemic from 2019 to 2021, the global burden of measles decreased overall, but mortality and DALYs rates in East Asia increased significantly, with EAPC of 155.55 and 146.94, respectively. In addition, the pandemic has disrupted vaccination efforts. Among 204 countries, 75 countries reported a significant decline in the coverage rate for the first dose of MCV, and 68 countries showed a decline in the vaccination rate for the second dose of MCV. We further explored possible influencing factors by conducting a retrospective analysis of the epidemiological situation of measles among children and adolescents in China from 2019 to 2021. This included, but was not limited to, changes in vaccination coverage, population mobility patterns, allocation of medical resources, and socioeconomic factors. By comprehensively analyzing these factors, we hope to gain a more comprehensive understanding of the reasons behind the rise in measles mortality rates and provide data support and recommendations for future public health strategies. We have added the content to the discussion section. The fluctuation in South Africa may be related to the accumulation of susceptible populations, increased population density, and human immunodeficiency virus (HIV) infection, which have led to repeated outbreaks (<xref ref-type="bibr" rid="ref54">Sartorius et al., 2013</xref>; <xref ref-type="bibr" rid="ref42">McMorrow et al., 2009</xref>). In addition, political mismanagement and funding deficiency have negatively impacted vaccination (<xref ref-type="bibr" rid="ref53">Pustake et al., 2022</xref>). Thus, it is evident that the measles burden is influenced by differences in healthcare resources, vaccination coverage, and socioeconomic development.</p>
</sec>
<sec id="sec27">
<label>4.2</label>
<title>Negative correlation between SDI and measles burden</title>
<p>SDI is significantly negatively correlated with measles incidence and mortality (<xref ref-type="bibr" rid="ref65">Wang et al., 2021</xref>; <xref ref-type="bibr" rid="ref23">GBD 2015 Maternal Mortality Collaborators, 2016</xref>). This study found that the prevalence, incidence, mortality, and DALYs of measles among children and adolescents in the BRICS-plus countries declined significantly as the SDI increased. Among them, Brazil, Russia, China, and Iran had lower-than-expected measles prevalence. High-SDI country Russia (SDI&#x202F;=&#x202F;0.82) had the lowest prevalence rate (0.01 per 100,000 population), and its vaccination coverage was more than 95%, suggesting that the measles epidemic was effectively controlled (<xref ref-type="bibr" rid="ref48">Onishchenko et al., 2011</xref>); whereas, Ethiopia (SDI&#x202F;=&#x202F;0.35) had a low level of economic status and lack of healthcare resources, with vaccination coverage of less than 60%, which resulted in a persistently high burden of measles. This may be closely related to its low vaccination coverage and low level of socio-economic development (<xref ref-type="bibr" rid="ref59">Shiferie et al., 2024</xref>). Previous studies have noted that rising measles vaccination rates can significantly reduce measles incidence and mortality globally, with the most significant reductions in high-SDI countries, such as Russia and China (<xref ref-type="bibr" rid="ref22">Gasta&#x00F1;aduy et al., 2021</xref>; <xref ref-type="bibr" rid="ref65">Wang et al., 2021</xref>; <xref ref-type="bibr" rid="ref69">Wang H. et al., 2023</xref>). Consistently, the present study further confirmed the negative association between SDI and measles burden (<xref ref-type="bibr" rid="ref28">George et al., 2024</xref>; <xref ref-type="bibr" rid="ref7">Bidari and Yang, 2024</xref>).</p>
</sec>
<sec id="sec28">
<label>4.3</label>
<title>Age and sex patterns analysis of measles in BRICS-plus</title>
<p>The highly contagious nature makes measles a leading cause of childhood deaths globally, especially in areas with low vaccination rates (<xref ref-type="bibr" rid="ref35">Lazar et al., 2019</xref>; <xref ref-type="bibr" rid="ref17">Do et al., 2021</xref>; <xref ref-type="bibr" rid="ref62">Stein-Zamir et al., 2024</xref>). About 350,000 measles cases were reported globally in 2018, resulting in about 142,000 deaths, the majority of which were in children under 5&#x202F;years of age (<xref ref-type="bibr" rid="ref44">Misin et al., 2020</xref>). The present study suggested that about 50% of global measles cases occurred in the under-five group, consistent with previous studies (<xref ref-type="bibr" rid="ref44">Misin et al., 2020</xref>; <xref ref-type="bibr" rid="ref65">Wang et al., 2021</xref>). This may stem from the fact that infants and young children have immature immune systems and are more susceptible to infection (<xref ref-type="bibr" rid="ref61">Simon et al., 2015</xref>), indicating the importance of measles vaccination programs for children within 5&#x202F;years after birth. Ethiopia had the highest prevalence of measles among children under 5&#x202F;years of age in BRICS-plus countries, followed by South Africa and India. The study also found a significant decline in measles burden with age. DALYs in Ethiopian children under 5&#x202F;years of age was 820.53 per 100,000 population for males and 630.01 per 100,000 population for females. It declined to 11.88 per 100,000 population and 13.07 per 100,000 population, respectively, in the age group of 10&#x2013;14&#x202F;years. This may be attributed to the cumulative effect of the mature immune system and vaccination (<xref ref-type="bibr" rid="ref61">Simon et al., 2015</xref>; <xref ref-type="bibr" rid="ref68">Wang Q. et al., 2023</xref>).</p>
</sec>
<sec id="sec29">
<label>4.4</label>
<title>Age-period-cohort analysis of measles in BRICS-plus</title>
<p>This study analyzed the prevalence and incidence of measles among children and adolescents in BRICS-plus countries using an age-period-cohort model. The prevalence and incidence of measles in the reference cohort showed a significant age-dependent decline, forming a typical &#x201C;L-shaped&#x201D; curve. The 0&#x2013;5 age group had the highest prevalence and incidence of measles, which was related to the waning of maternal antibodies and the immature immune system (<xref ref-type="bibr" rid="ref61">Simon et al., 2015</xref>; <xref ref-type="bibr" rid="ref68">Wang Q. et al., 2023</xref>; <xref ref-type="bibr" rid="ref15">Dagan et al., 1995</xref>). Although most countries have included the first dose of MCV in the routine immunization program for infants, vaccine interruptions, vaccine hesitancy, or insufficient coverage in some regions may lead to a continued high risk in this age group (<xref ref-type="bibr" rid="ref32">Kostandova et al., 2022</xref>; <xref ref-type="bibr" rid="ref18">Durrheim et al., 2024</xref>). Period effect analysis showed that Brazil and Saudi Arabia experienced a rebound in incidence between 2017 and 2022, which may be related to the disrupted routine immunization, vaccine hesitancy, delayed vaccination, and imported cases associated with religious gatherings during the COVID-19 pandemic (<xref ref-type="bibr" rid="ref36">Lee et al., 2022</xref>; <xref ref-type="bibr" rid="ref49">Packham et al., 2024</xref>; <xref ref-type="bibr" rid="ref11">Chiappini et al., 2021</xref>; <xref ref-type="bibr" rid="ref57">Shafi et al., 2016</xref>). The risk of measles in China, India, and Ethiopia has continued to decline since 2007, indicating the effectiveness of supplementary vaccination campaigns (<xref ref-type="bibr" rid="ref5">Auzenbergs et al., 2023</xref>; <xref ref-type="bibr" rid="ref68">Wang Q. et al., 2023</xref>; <xref ref-type="bibr" rid="ref58">Shen et al., 2022</xref>). Cohort effect analysis further demonstrated that the incidence in more recent birth cohorts was significantly lower than that in earlier cohorts, confirming the cumulative protective effect of vaccination programs (<xref ref-type="bibr" rid="ref5">Auzenbergs et al., 2023</xref>; <xref ref-type="bibr" rid="ref68">Wang Q. et al., 2023</xref>). Therefore, precise interventions targeting the 0&#x2013;5 age group are needed for measles elimination worldwide.</p>
</sec>
<sec id="sec30">
<label>4.5</label>
<title>Global and BRICS-plus measles trends by 2032</title>
<p>Predictive models of measles prevalence and incidence globally and in BRICS-plus countries for 2032 revealed the potential progress and persistent challenges in measles elimination. The predictions showed a downward trend in the global number of measles patients, but the wide range of the confidence interval, especially negative values, indicated the sensitivity of the predictive model to public health emergencies. Among BRICS-plus countries, India may maintain the highest prevalence, mainly attributed to the disparity in immunization coverage under its large population base (<xref ref-type="bibr" rid="ref50">Panda et al., 2020</xref>; <xref ref-type="bibr" rid="ref56">Scobie et al., 2015</xref>). Although China showed a similar downward trend, densely-populated areas may lead to local outbreaks. The predicted low incidence in Brazil and South Africa is based on the stability of the existing prevention and control systems, but the immunosuppressed state of HIV-infected children in South Africa remains a potential threat (<xref ref-type="bibr" rid="ref54">Sartorius et al., 2013</xref>; <xref ref-type="bibr" rid="ref12">Coetzee et al., 2014</xref>). Therefore, future public health policies should continue to increase vaccination coverage, especially in countries with a high measles burden, to further lower the incidence and mortality of measles.</p>
</sec>
<sec id="sec31">
<label>4.6</label>
<title>Limitations</title>
<p>Although this study provides a detailed analysis of the measles burden globally and in BRICS-plus countries, there are still certain limitations. Firstly, the GBD database has low data quality in some low-income countries, which may lead to underreporting. Secondly, the timespan (from 1990 to 2021) does not fully consider the impact of the recent decline in vaccination coverage in some countries, especially the rebound in the measles burden from 2019 to 2021, which may be related to interrupted vaccination due to the COVID-19 pandemic. In addition, this study focuses on the relationship between SDI and measles burden but does not deeply explore other influencing factors, such as the allocation of medical resources, population mobility, and changes in public health policies. These factors may have significant impacts on the measles burden in specific countries or regions. Future studies should further explore the independent and interactive effects of these factors to improve the reliability of research results.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec32">
<label>5</label>
<title>Conclusion</title>
<p>In conclusion, over the past three decades, the burden of measles among children and adolescents in BRICS-plus countries has significantly declined and is closely related to the improvement of SDI. However, there are complex differences in the age, period, and cohort effects of the measles burden among different countries, especially in low- and middle-income countries. For future public health strategies, it is necessary to continuously enhance the vaccination coverage rate, particularly in countries with a heavy burden of measles, such as India and Ethiopia, to further reduce the incidence and mortality of measles. Additionally, all countries need to strengthen measles surveillance systems to ensure the timely detection and control of measles outbreaks and prevent their large-scale recurrence.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec33">
<title>Data availability statement</title>
<p>This study provides an in-depth analysis of publicly available datasets. The names and registration numbers of the relevant repositories are as follows: <ext-link xlink:href="http://ghdx.healthdata.org/gbd-results-tool" ext-link-type="uri">http://ghdx.healthdata.org/gbd-results-tool</ext-link>.</p>
</sec>
<sec sec-type="author-contributions" id="sec34">
<title>Author contributions</title>
<p>HY: Formal analysis, Writing &#x2013; original draft, Conceptualization, Investigation, Writing &#x2013; review &#x0026; editing. BY: Writing &#x2013; review &#x0026; editing, Formal analysis, Methodology. YC: Data curation, Conceptualization, Writing &#x2013; review &#x0026; editing. LW: Resources, Project administration, Conceptualization, Investigation, Writing &#x2013; review &#x0026; editing. YJ: Data curation, Conceptualization, Project administration, Supervision, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec35">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This research was supported by the Liaoning Province Science and Technology Plan Joint Initiative (Natural Science Fund-General Project) (grant no. 2024-MSLH-162) and the Scientific Research Fund of the First Affiliated Hospital of Jinzhou Medical University (grant no. KYTD-2022004).</p>
</sec>
<ack>
<p>Thanks to the IHME and the GBD study collaborations.</p>
</ack>
<sec sec-type="COI-statement" id="sec36">
<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="sec37">
<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="sec38">
<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="sec39">
<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/fmicb.2025.1612124/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fmicb.2025.1612124/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Image_1.jpg" mimetype="image/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink" id="SM1"><label>SUPPLEMENTARY FIGURE S1</label><caption><p>Joinpoint regression analyses of measles burden among children and adolescents in Saudi Arabia, Egypt, United Arab Emirates, Iran, and Ethiopia. <bold>(A)</bold> Prevalence cases. <bold>(B)</bold> Incidence cases. <bold>(C)</bold> Mortality cases. <bold>(D)</bold> DALYs cases. DALYs, disability-adjusted life years.</p></caption></supplementary-material>
<supplementary-material xlink:href="Image_2.jpg" mimetype="image/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink" id="SM2"><label>SUPPLEMENTARY FIGURE S2</label><caption><p>Age distribution of measles incidence and age-period-cohort effects in the BRICS-plus countries across SDI quintiles. <bold>(A)</bold> Temporal change in the relative proportion of measles across age groups (&#x003C;5, 5&#x2013;9, 10&#x2013;14, 15&#x2013;19&#x202F;years), 1990&#x2013;2021. <bold>(B)</bold> Age effects are shown by the fitted longitudinal age curves of incidence rate (per 100,000 person-years) adjusted for period deviations. <bold>(C)</bold> Period effects are shown by the relative risk of incidence rate (incidence rate ratio) and computed as the ratio of age-specific rates with the referent period set at 2002&#x2013;2006. <bold>(D)</bold> Cohort effects are shown by the relative risk of incidence rate and computed as the ratio of age-specific rates with the referent cohort set in 1997. The dots and shaded areas denote incidence rates or rate ratios and their corresponding 95% CIs. SDI, socio-demographic index; CIs, confidence intervals.</p></caption></supplementary-material>
<supplementary-material xlink:href="Image_3.jpg" mimetype="image/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink" id="SM3"><label>SUPPLEMENTARY FIGURE S3</label><caption><p>Age distribution of measles deaths and age-period-cohort effects in the BRICS-plus countries across SDI quintiles. <bold>(A)</bold> Temporal change in the relative proportion of measles across age groups (&#x003C;5, 5&#x2013;9, 10&#x2013;14, 15&#x2013;19&#x202F;years), 1990&#x2013;2021. <bold>(B)</bold> Age effects are shown by the fitted longitudinal age curves of death rate (per 100,000 person-years) adjusted for period deviations. <bold>(C)</bold> Period effects are shown by the relative risk of death rate (death rate ratio) and computed as the ratio of age-specific rates with the referent period set at 2002&#x2013;2006. <bold>(D)</bold> Cohort effects are shown by the relative risk of death rate and computed as the ratio of age-specific rates with the referent cohort set in 1997. The dots and shaded areas denote death rates or rate ratios and their corresponding 95% CIs. SDI, socio-demographic index; CIs, confidence intervals.</p></caption></supplementary-material>
<supplementary-material xlink:href="Image_4.jpg" mimetype="image/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink" id="SM4"><label>SUPPLEMENTARY FIGURE S4</label><caption><p>Age distribution of measles DALYs and age-period-cohort effects in the BRICS-plus countries across SDI quintiles. <bold>(A)</bold> Temporal change in the relative proportion of measles across age groups (&#x003C;5, 5&#x2013;9, 10&#x2013;14, 15&#x2013;19&#x202F;years), 1990&#x2013;2021. <bold>(B)</bold> Age effects are shown by the fitted longitudinal age curves of DALYs rate (per 100,000 person-years) adjusted for period deviations. <bold>(C)</bold> Period effects are shown by the relative risk of DALYs rate (DALYs rate ratio) and computed as the ratio of age-specific rates with the referent period set at 2002&#x2013;2006. <bold>(D)</bold> Cohort effects are shown by the relative risk of DALYs rate and computed as the ratio of age-specific rates with the referent cohort set in 1997. The dots and shaded areas denote DALYs rates or rate ratios and their corresponding 95% CIs. SDI, socio-demographic index; CIs, confidence intervals; DALYs, disability-adjusted life years.</p></caption></supplementary-material>
<supplementary-material xlink:href="Image_5.tif" mimetype="image/tiff" xmlns:xlink="http://www.w3.org/1999/xlink" id="SM5"><label>SUPPLEMENTARY FIGURE S5</label><caption><p>ARIMA model prediction of measles burden trends among children and adolescents in initial BRICS countries from 2022 to 2032. <bold>(A)</bold> Predicted trends of prevalence. <bold>(B)</bold> Predicted trends of incidence.</p></caption></supplementary-material>
<supplementary-material xlink:href="Table_1.xlsx" id="SM6" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_2.xlsx" id="SM7" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_3.xlsx" id="SM8" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_4.xlsx" id="SM9" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_5.xlsx" id="SM10" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_6.xlsx" id="SM11" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_7.xlsx" id="SM12" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_8.xlsx" id="SM13" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_9.xlsx" id="SM14" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_10.xlsx" id="SM15" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_11.xlsx" id="SM16" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_12.xlsx" id="SM17" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_13.xlsx" id="SM18" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_14.xlsx" id="SM19" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table_15.xlsx" id="SM20" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<fn-group>
<fn id="fn0001"><p><sup>1</sup><ext-link xlink:href="https://www.who.int/zh/news-room/fact-sheets/detail/measles" ext-link-type="uri">https://www.who.int/zh/news-room/fact-sheets/detail/measles</ext-link></p></fn>
<fn id="fn0002"><p><sup>2</sup><ext-link xlink:href="https://ghdx.healthdata.org/gbd-2021/" ext-link-type="uri">https://ghdx.healthdata.org/gbd-2021/</ext-link></p></fn>
</fn-group>
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