Front. Public Health Frontiers in Public Health Front. Public Health 2296-2565 Frontiers Media S.A. 10.3389/fpubh.2025.1650142 Public Health Correction Correction: Long-term trends in rubella incidence across various regions and age groups in China, 2004–2021 Su Yongjian 1 2 † Su Zhengqin 1 † Huang Zixiu 3 † Yang Shan 4 * Li Zhongyou 1 * Li Hai 1 * 1School of Public Health and Management, Guangxi University of Chinese Medicine, Nanning, China 2Ruikang Hospital Affiliated with Guangxi University of Chinese Medicine, Nanning, China 3College of Computer Science and Electronic Engineering, Hunan University, Changsha, China 4School of Innovation and Entrepreneurship, Guangxi University of Traditional Chinese Medicine, Nanning, China

Edited and reviewed by: Marc Jean Struelens, Université libre de Bruxelles, Belgium

 *Correspondence: Shan Yang 1402650@qq.com Zhongyou Li 582893156@qq.com Hai Li lihai6609@hotmail.com

†These authors share first authorship

 09 07 2025 2025 13 1650142 19 06 2025 23 06 2025 Copyright © 2025 Su, Su, Huang, Yang, Li and Li. 2025 Su, Su, Huang, Yang, Li and Li

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.

 A Correction on Long-term trends in rubella incidence across various regions and age groups in China, 2004–2021 by Su, Y., Su, Z., Huang, Z., Yang, S., Li, Z., and Li, H. (2025). Front. Public Health. 13:1566999. doi: 10.3389/fpubh.2025.1566999 rubella incidence descriptive study joinpoint regression model China section-at-acceptance Infectious Diseases: Epidemiology and Prevention

The reference for [15] was erroneously written as “Zhu Z, Wang HL, Zhang Y. Analysis of serum IgM antibody and viral nucleic acid detection results in measles and rubella cases in China from 2014 to 2023. Chinese J Prev Med. (2024) 8:1318–23. doi: 10.3760/cma.j.cn112150-20240306-00191”. It should be “Zhu Z, Wang HL, Zhang Y. Analysis of serum IgM antibody and viral nucleic acid detection results in measles and rubella cases in China from 2014 to 2023. Chin J Prev Med. (2024) 8:1318–23. doi: 10.3760/cma.j.cn112150-20240306-00191”.

There was a mistake in Figures 1, 4, 5, 6, 7 and 8 as published. To ensure academic rigor, we have rechecked the data and performed additional analyses using the latest procedures, providing more accurate data and higher-resolution figures. The corrected Figures 1, 4, 5, 6, 7 and 8 appear below.

The annual number of cases and incidence of rubella in China from 2004 to 2021.

Bar and line graph showing the number of cases and incidence rates from 2004 to 2021. Cases peak in 2008 with over 120,000, while incidence also peaks then. Both metrics decrease significantly after 2008, with a minor rise in 2019.

The long-term trend of rubella incidence in China from 2004 to 2021.

Line graph of crude rates per 100,000 in Mainland China from 2004 to 2021, with observed data points shown as red diamonds. A blue line represents a rising trend with an annual percent change (APC) of 46.58 from 2004 to the joinpoint in 2008. After 2008, a green line shows a declining trend with an APC of -18.41 until 2021.

Distribution map of rubella incidence in different regions of China from 2004 to 2021.

Map of China showing average annual incidence rates per 100,000 people for different regions. Tibet has the highest rate at 8.63, shown in dark purple. Other high-incidence regions include Ningxia at 7.72 and Liaoning at 7.13. Lower rates are highlighted in lighter colors. Beijing is marked with a red star, showing a rate of 2.66. A color scale indicates ranges of incidence rates from light to dark purple.

Distribution of rubella incidence with decreasing trends in five regions of China from 2004 to 2021.

Map of China highlighting regional differences in AAPC percentages. Dark green regions, including Sinkiang, Jilin, Ningxia, Zhejiang, and Tianjian, show significant decreases from -18.75 to -21.81. Beijing is marked with a star. A legend indicates color-coded AAPC percentage ranges.

The number of cases and the average annual incidence of rubella in different age groups from 2004 to 2021.

Bar and line graph showing the number of cases and average annual incidence per 100,000 across different age groups. Green bars represent case numbers peaking at ages ten to fourteen. The red line indicates incidence, highest at ages ten to fourteen, then declining.

Distribution of the long-term trends of rubella incidence in different age groups from 2004 to 2021.

Bar chart showing Average Annual Percent Change (AAPC) in various age groups, with significant values marked by asterisks.For statistically significant results, negative values appear for ages zero to nine, fifty to fifty-four, and seventy to seventy-nine. The remaining fourteen age groups trends may seem negatively or positively value, but there are considered statistically non-significant.

There was a mistake in Tables 1 and 2 as published. To ensure academic rigor, we have rechecked the data and performed additional analyses using the latest procedures, providing more accurate data. The corrected Tables 1 and 2 appear below.

The long-term trends of rubella incidence in the whole country and 31 regions from 2004 to 2021.

Regions Trends AAPC (%) AAPC 95% CI (%) Z P-value
Lower CI Upper CI
Beijing Stable −10.20 −20.69 1.67 −1.70 0.090
Tianjin Decrease −19.39 −32.02 −4.41 −2.48 0.013
Hebei Stable 5.19 −31.55 61.64 0.23 0.817
Shanxi Stable −5.87 −22.58 14.46 −0.61 0.544
Inner Mongolia Stable −5.77 −29.58 26.08 −0.40 0.689
Liaoning Stable 1.62 −29.88 47.27 0.08 0.932
Jilin Decrease −21.81 −33.00 −8.75 −3.12 0.002
Heilongjiang Stable 12.88 −40.31 113.47 0.37 0.709
Shanghai Stable 1.11 −16.21 21.99 0.11 0.909
Jiangsu Stable 2.08 −13.19 20.05 0.25 0.803
Zhejiang Decrease −18.86 −28.35 −8.11 −3.29 0.001
Anhui Stable −2.16 −14.38 11.80 −0.32 0.748
Fujian Stable −6.97 −14.21 0.89 −1.89 0.077
Jiangxi Stable −4.06 −15.50 8.93 −0.64 0.523
Shandong Stable −4.16 −26.59 25.10 −0.31 0.754
Henan Stable −9.14 −23.00 7.22 −1.13 0.256
Hubei Stable 14.87 −10.22 46.98 1.10 0.270
Hunan Stable −14.6 −67.82 126.67 −0.32 0.751
Guangdong Stable −13.12 −39.45 24.66 −0.76 0.445
Guangxi Stable 2.13 −35.36 61.36 0.09 0.928
Hainan Stable 15.36 −26.64 81.39 0.62 0.536
Chungking Stable −0.61 −9.67 9.36 −0.14 0.893
Sichuan Stable −6.88 −14.25 1.12 −1.83 0.085
Guizhou Stable −7.78 −16.20 1.49 −1.79 0.092
Yunnan Stable −4.53 −19.62 13.40 −0.53 0.598
Tibet Stable −10.75 −45.03 44.89 −0.46 0.645
Shaanxi Stable −6.16 −16.87 5.94 −1.03 0.304
Gansu Stable −22.79 −76.32 151.76 −0.43 0.668
Qinghai Stable 4.47 −24.96 45.46 0.26 0.796
Ningxia Decrease −18.75 −29.62 −6.21 −2.84 0.005
Sinkiang Decrease −19.69 −28.03 −10.38 −3.92 < 0.001
Mainland China Stable −6.36 −17.09 5.77 −1.06 0.291

The long-term trends of rubella incidence in 26 age groups from 2004 to 2021.

Age groups Trends AAPC (%) AAPC 95% CI (%) Z P-Value
Lower CI Upper CI
0– Decrease −14.35 −22.67 −5.12 −2.97 0.003
1– Decrease −18.46 −25.86 −10.32 −4.2 < 0.001
2– Decrease −20.98 −27.73 −13.59 −5.17 < 0.001
3– Decrease −22.78 −29.64 −15.24 −5.44 < 0.001
4– Decrease −25.2 −32.77 −16.78 −5.33 < 0.001
5– Decrease −28.32 −37.95 −17.19 −4.52 < 0.001
6– Decrease −29.96 −39.8 −18.5 −4.61 < 0.001
7– Decrease −18.67 −28.82 −7.07 −3.04 0.002
8– Decrease −22.25 −30.02 −13.62 −4.68 < 0.001
9– Decrease −16.96 −24.25 −8.97 −3.96 < 0.001
10– Stable 10.12 −35.01 86.59 0.36 0.72
15– Stable −16.5 −62.94 88.15 −0.44 0.664
20– Stable 22.55 −23.83 97.16 0.84 0.402
25– Stable 5.76 −16.08 33.29 0.47 0.635
30– Stable 4.34 −10.12 21.13 0.56 0.577
35– Stable 5.05 −9.89 22.48 0.63 0.529
40– Stable −0.07 −6.67 7 −0.02 0.982
45– Stable −1.04 −14.3 14.27 −0.14 0.887
50– Decrease −8.27 −14.59 −1.47 −2.37 0.018
55– Stable −6.7 −16.6 4.39 −1.21 0.226
60– Stable −7.8 −15.77 0.93 −1.76 0.078
65– Stable −6.4 −22.04 12.38 −0.71 0.478
70– Decrease −12.39 −19.5 −4.64 −3.06 0.002
75– Decrease −13.13 −19.56 −6.19 −3.59 < 0.001
80– Stable −9.24 −19.34 2.13 −1.61 0.107
85– Stable −7.12 −30.27 23.73 −0.5 0.614

A correction has been made to Section 2.2 Research methods, 2.2.1 Basic statistical description, paragraph 1. The text “(incidence = number of cases/number of exposed population *100,000%)” has been changed to “(incidence = number of cases/number of exposed population *100,000).”

The original version of this article has been updated.

Publisher's note

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.