ABSTRACT
Influenza activity peaks in southern (59.62%) and northern China (57.60%) during the 2022/2023 season reached the highest levels in the past 10 years. The 2023/2024 season witnessed a longer duration of the winter–spring epidemic weeks and a higher disease burden compared with previous high‐epidemic years. The A(H3N2), A(H1N1)pdm09, and B/Victoria lineages alternated among the predominant circulating strains from the 2022/2023 season to the 2024/2025 season. After the 2022/2023 and 2023/2024 seasons of disruption and fluctuation, influenza in the 2024/2025 season has reverted to its previous epidemic pattern.
Keywords: disease burden, epidemiological pattern, influenza
1. Introduction
Accumulated evidence [1] indicates the influenza‐associated all‐cause mortality rate in China is 14.33 per 100,000 persons during 2005–2019. Based on surveillance data in China from 2022 to 2025, this study analyzed the trends in epidemiology, virological characteristics, and disease burden to provide evidence for improving influenza protection and control strategies.
2. Methods
2.1. Data Sources
Based on the Influenza Weekly Report of the China Center for Disease Control and Prevention, we collected data on the test‐positive rate, the percentage of influenza‐like illness among total outpatient and emergency department visits (ILI%), and virological surveillance of the southern and northern China from Week 14 of 2022 to Week 13 of 2025.
2.2. Relevant Definitions
Influenza activity intensity [2]: The average positive rate among all epidemic weeks of one surveillance year was classified into high(≥ 25%), moderate(≥ 20% to <25%), and low(20%) levels.
- Influenza attack rate:
The attack rate was defined as “The proportion of an exposed population that develops influenza within a specified period [3].” In this study, the attack rate was used as the indicator of disease burden. We indirectly estimated the influenza attack rate by leveraging real‐world vaccination coverage and outpatient rate, applying a self‐comparison method across different surveillance years in southern and northern China. We simplified the equation by cancellation of constants and addressed the challenge of limited access to certain real‐time parameters. Specifically, since 2022, the total population, the outpatient rate, and the influenza vaccine efficacy remained relatively stable, and influenza vaccination coverage in mainland China has remained low without abrupt increases. As such, we used the weekly product of ILI% and influenza test‐positive rate as a composite parameter to construct a time‐series curve. The area under the curve (AUC) and its fold changes between influenza seasons were used as indirect measures of variation in confirmed influenza attack rate across different periods.
2.3. Statistical Analysis
R version 4.5.0 and Excel were used for descriptive analysis and Chi‐square test of influenza relevant data.
3. Results
3.1. Influenza Activity Intensity
The average positive rates in the south from the 2022/2023 to 2024/2025 seasons reached high epidemic levels (30.66%, 31.47%, and 25.45%, respectively). Those in the north reached high epidemic levels (26.73% and 26.95%) in the 2022/2023 and 2023/2024 seasons, while they decreased to a moderate epidemic level (21.88%) during the 2024/2025 season. Additionally, the activity peaks of the south (59.62%) and north (57.60%) in the 2022/2023 season have reached the highest levels in the past 10 years (p < 0.001) (Table 1).
TABLE 1.
Influenza activity intensity and peak in China, 2013/2014 to 2024/2025 seasons.
| Surveillance year | The south | The north | ||||||
|---|---|---|---|---|---|---|---|---|
| Activity intensity (%) | Peak (%) | χ2 | P‐value | Activity intensity (%) | Peak (%) | χ2 | P‐value | |
| 2013–2014 | 23.73 | 42.57 a | 2302.6 | < 0.001 | 21.38 | 36.25 a | 1240.2 | < 0.001 |
| 2014–2015 | 18.12 | 25.57 a | 18.66 | 39.12 a | ||||
| 2015–2016 | 21.10 | 33.78 a | 28.93 | 41.98 a | ||||
| 2016–2017 | 15.74 | 24.82 a | 20.03 | 26.73 a | ||||
| 2017–2018 | 26.65 | 47.97 a | 32.38 | 48.47 a | ||||
| 2018–2019 | 33.23 | 44.86 a | 31.87 | 41.00 a | ||||
| 2022–2023 | 30.66 | 59.62 # | 26.73 | 57.60 # | ||||
| 2023–2024 | 31.47 | 55.23 a | 26.95 | 43.93 a | ||||
| 2024–2025 | 25.45 | 35.75 a | 21.88 | 35.35 a | ||||
Note: Chi‐square test was used for overall testing of influenza activity peaks during each surveillance year, with Bonferroni correction applied to control the family‐wise error rate in multiple comparisons.
Reference group.
A statistically significant difference was shown when comparing to the reference group.
3.2. Seasonality and Virological Characteristics
China has a winter–spring epidemic peak each year (Figure 1). Notably, the high activity intensity in the south previously during summer disappeared in the 2023/2024 and 2024/2025 seasons. The duration of the winter–spring epidemic weeks in the south (28 weeks) and north (20 weeks) in the 2023/2024 season reached the highest levels in the past 5 years. The peak onset time in the south (Week 13 of 2023) and north (Week 10 of 2023) during the 2023/2024 season exhibited an approximately 10‐week delay in comparison with those from the 2016/2017 to 2018/2019 seasons (Table 2).
FIGURE 1.
Observed influenza activity in 2022–2025 and fitted levels using 2013–2019 historical data. a, the south; b, the north.
TABLE 2.
Duration of the winter–spring epidemic weeks and peak onset time of influenza in China, 2013/2014 to 2024/2025 seasons.
| Surveillance year | The south | The north | ||
|---|---|---|---|---|
| Duration of epidemic weeks | Peak onset time (nature week) | Duration of epidemic weeks | Peak onset time (nature week) | |
| 2013–2014 | 20 | Week 2 of 2014 | 17 | Week 14 of 2014 |
| 2014–2015 | 15 | Week 4 of 2015 | 12 | Week 52 of 2014 |
| 2015–2016 | 21 | Week 12 of 2016 | 17 | Week 11 of 2016 |
| 2016–2017 | 30 | Week 51 of 2016 | 18 | Week 52 of 2016 |
| 2017–2018 | 18 | Week 3 of 2018 | 16 | Week 2 of 2018 |
| 2018–2019 | 15 | Week 4 of 2019 | 15 | Week 3 of 2019 |
| 2022–2023 | 11 | Week 13 of 2023 | 10 | Week 10 of 2023 |
| 2023–2024 | 28 | Week 50 of 2023 | 20 | Week 49 of 2023 |
| 2024–2025 | 14 | Week 2 of 2025 | 12 | Week 1 of 2025 |
A(H3N2) was the predominant circulating strain through Week 6 of 2023. Subsequently, A(H3N2) and A(H1N1)pdm09 showed cocirculation characteristics. The A(H3N2) and B/Victoria lineages alternated with the predominant circulating strains during the 2023/2024 season. A(H1N1)pdm09 became the predominant circulating strain during the 2024/2025 season (Figures S1 and S2).
3.3. Disease Burden
The disease burden in the south during the 2022/2023 season reached 1.88 times the previous high epidemic level, while that in the north was 0.84 times the previous high. The disease burden in the south during the 2023/2024 season reached 2.12 times the previous high epidemic level, while that in the north was 1.65 times the previous high. The disease burden in the south during the 2024/2025 season was 0.64 times the previous high epidemic level, while that in the north was 1.11 times the previous moderate epidemic level (Figure 2).
FIGURE 2.
Observed influenza disease burden in 2022–2025 and fitted levels using 2013–2019 historical data. a, the south; b, the north.
4. Discussion
Implementing systematic surveillance and summarizing the dynamics of influenza are crucial for prevention and control. This study found that the 2022/2023 season witnessed the highest activity peak in the last 10 years. Other studies have reported this phenomenon [4, 5]. First, due to increasing population, more frequent indoor activity, and climate change, the risk of influenza transmission has intensified. Second, disparities in immune protection levels among different populations resulting from different prior immune exposure histories have aggravated the intensity of influenza activity in China [6, 7]. A summer epidemic level occurred in northern China, and there was no influenza peak in winter during the 2022/2023 season. Instead, there was a delayed epidemic peak in spring, which may be related to the late 2022 epidemic of SARS‐CoV‐2 in China, leading to a delayed peak in influenza and a “see‐saw” effect [8].
Accumulated evidence [1, 9, 10] indicates influenza epidemics contributed to a severe disease burden. This study revealed that the 2023/2024 season had the highest disease burden in the last decade, which was consistent with the findings of Du [11, 12]. First, the activity intensity in the 2023/2024 season reached a high epidemic level. Second, the duration of the winter–spring epidemic weeks in the southern and northern China during the 2023/2024 season were 28 and 20 weeks, respectively. The combination of high activity intensity and protracted duration of epidemic weeks in the 2023/2024 season contributed to a severe disease burden. Zhao's study found that influenza mortality rates increased by 366.67% and showed a significantly increased trend during 2004–2020 [13]. A study from Zhejiang province in China also comprehensively considered the influenza test‐positive rate as well as ILI% to estimate the incidence, indicating a monotonically increasing trend [14].
In summary, during the atypical variations of the 2022/2023 and 2023/2024 seasons, the epidemiological characteristics of influenza showed a normal trend. This suggests the prevention and control of influenza could return to the regular standard, and strengthening influenza vaccinations remains an effective measure to protect susceptible populations [15].
5. Conclusion
The 2022/2023 and 2023/2024 influenza seasons were characterized by disruption and fluctuation. Influenza exhibited high epidemic levels and several influenza virus subtypes, except for the B/Yamagata lineage, which alternated with the predominant circulating strain from the 2022/2023 to 2024/2025 seasons. Since the 2024/2025 season, influenza has been reverting to its previous epidemic pattern.
Author Contributions
Hairu Yu: conceptualization, software, data curation, formal analysis, writing – original draft, writing – review and editing, visualization. Qing Wang: conceptualization, software, writing – review and editing, methodology, supervision, validation. Boer Qi: writing – review and editing. Jie Qian: funding acquisition, writing – review and editing. Weizhong Yang: writing – review and editing, funding acquisition, supervision. Luzhao Feng: conceptualization, methodology, funding acquisition, supervision, writing – review and editing, project administration, resources.
Ethics Statement
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Peer Review
The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/irv.70151.
Supporting information
Figure S1: Observed virological characteristic of influenza in the south during 2022–2025.
Figure S2: Observed virological characteristic of influenza in the north during 2022–2025.
Acknowledgments
We extend our gratitude to the staff of the China Center for Disease Control and Prevention. We also sincerely thank all the staff of sentinel hospitals and network laboratories in China, which provided the foundation for this study.
Yu H., Wang Q., Qi B., Qian J., Yang W., and Feng L., “Changing Epidemiological Pattern and Higher Disease Burden of Influenza in China, 2022 to 2025,” Influenza and Other Respiratory Viruses 19, no. 9 (2025): e70151, 10.1111/irv.70151.
Hairu Yu and Qing Wang contributed equally to this work and share first authorship.
Funding: This work was supported by the Non‐profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2021‐RC330‐002) and Beijing Natural Science Foundation‐Haidian Original Innovation Joint Fund Project (L222029 and L222028).
Data Availability Statement
The data that support the findings of this study are openly available in the Influenza Weekly Report of China Center for Disease Control and Prevention at https://ivdc.chinacdc.cn/cnic/.
References
- 1. Li J., Chen Y., Wang X., and Yu H., “Influenza‐Associated Disease Burden in Mainland China: A Systematic Review and Meta‐Analysis,” Scientific Reports 11, no. 1 (2021): 2886, 10.1038/s41598-021-82161-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Feng L., Zhang T., Wang Q., et al., “Impact of COVID‐19 Outbreaks and Interventions on Influenza in China and the United States,” Nature Communications 12, no. 1 (2021): 3249, 10.1038/s41467-021-23440-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Principles of Epidemiology in Public Health Practice, Third Edition: An Introduction (U.S. Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and Office of Workforce and Career Development, 2006), updated in May 2012. [Google Scholar]
- 4. Kandeel A., Fahim M., Deghedy O., et al., “Resurgence of Influenza and Respiratory Syncytial Virus in Egypt Following Two Years of Decline During the COVID‐19 Pandemic: Outpatient Clinic Survey of Infants and Children, October 2022,” BMC Public Health 23, no. 1 (2023): 1067, 10.1186/s12889-023-15880-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Li Z., Xiong Y., Long J., et al., “Resurgence of Influenza During COVID‐19 in Chongqing, China: A Retrospective Analysis,” Journal of Medical Virology 95, no. 11 (2023): e29249, 10.1002/jmv.29249. [DOI] [PubMed] [Google Scholar]
- 6. Zeng H., Cai M., Li S., et al., “Epidemiological Characteristics of Seasonal Influenza Under Implementation of Zero‐COVID‐19 Strategy in China,” Journal of Infection and Public Health 16, no. 8 (2023): 1158–1166, 10.1016/j.jiph.2023.05.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Wu D., Lu J., Liu Y., Zhang Z., and Luo L., “Positive Effects of COVID‐19 Control Measures on Influenza Prevention,” International Journal of Infectious Diseases 95 (2020): 345–346, 10.1016/j.ijid.2020.04.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Wang Q., Jia M., Jiang M., et al., “Seesaw Effect Between COVID‐19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis,” JMIR Public Health and Surveillance 9 (2023): e44970, 10.2196/44970. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Maleki F., Welch V., Lopez S. M. C., et al., “Understanding the Global Burden of Influenza in Adults Aged 18‐64 Years: A Systematic Literature Review From 2012 to 2022,” Advances in Therapy 40, no. 10 (2023): 4166–4188, 10.1007/s12325-023-02610-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Zhang R., Dong X., Wang D., et al., “One Hundred Years of Influenza Since the 1918 Pandemic — Is China Prepared Today?,” China CDC Weekly 1, no. 4 (2019): 56–61, 10.46234/ccdcw2019.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Du Z., Shao Z., Zhang X., et al., “Nowcasting and Forecasting Seasonal Influenza Epidemics—China, 2022–2023,” China CDC Weekly 5, no. 49 (2023): 1100–1106, 10.46234/ccdcw2023.206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Ali S. T., Lau Y. C., Shan S., et al., “Prediction of Upcoming Global Infection Burden of Influenza Seasons After Relaxation of Public Health and Social Measures During the COVID‐19 Pandemic: A Modelling Study,” Lancet Global Health 10, no. 11 (2022): e1612–e1622, 10.1016/S2214-109X(22)00358-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Zhao N., Wang S., Wang L., et al., “Epidemiological Features and Trends in the Mortality Rates of 10 Notifiable Respiratory Infectious Diseases in China From 2004 to 2020: Based on National Surveillance,” Frontiers in Public Health 11 (2023): 1102747, 10.3389/fpubh.2023.1102747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Wu H., Xue M., Wu C., et al., “Estimation of Influenza Incidence and Analysis of Epidemic Characteristics From 2009 to 2022 in Zhejiang Province, China,” Frontiers in Public Health 11 (2023): 1154944, 10.3389/fpubh.2023.1154944. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Zhang J., Zhang L., Li J., et al., “Moderate Effectiveness of Influenza Vaccine in Outpatient Settings: A Test‐Negative Study in Beijing, China, 2023/24 Season,” Vaccine 46 (2025): 126662, 10.1016/j.vaccine.2024.126662. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1: Observed virological characteristic of influenza in the south during 2022–2025.
Figure S2: Observed virological characteristic of influenza in the north during 2022–2025.
Data Availability Statement
The data that support the findings of this study are openly available in the Influenza Weekly Report of China Center for Disease Control and Prevention at https://ivdc.chinacdc.cn/cnic/.