Epidemiological characteristics of hand, foot, and mouth disease clusters in Beijing, China, 2019–2024

Epidemiological characteristics of hand, foot, and mouth disease clusters in Beijing, China, 2019–2024 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiological characteristics of hand, foot, and mouth disease clusters in Beijing, China, 2019–2024 Hao Zhao, Da Huo, Hui Xu, Zhiyong Gao, Shuaibing Dong, Jiaxin Feng, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6327143/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Hand, foot, and mouth disease (HFMD) is a common enteric infectious disease that poses a threat to children's health. The disease exhibits high epidemic intensity and frequent clusters in Beijing, the capital of China. The present study analyzed data on HFMD clusters in Beijing from 2019 to 2024, reported by the district-level Centers for Disease Control and Prevention and compiled by the Beijing Center for Disease Control and Prevention. This study comprehensively examined the epidemiological characteristics of HFMD clusters, including demographic information, regional distribution, and pathogen associations. The Seasonal Autoregressive Integrated Moving Average (i.e., “SARIMA”) model was used to predict cluster incidence by 2025. From 2019 to 2024, 4265 HFMD clusters were reported in Beijing, exhibiting a pattern of high incidence every other year and two peaks annually, with significant seasonal epidemic characteristics. The primary locations of the clusters were kindergartens, schools, and households. Analysis of regional distribution revealed that the near suburbs had a higher incidence than the central and outer suburbs. It is recommended that key locations, such as kindergartens and schools in the near suburbs and urban-rural junctions, further implement HFMD prevention and control measures, strengthen surveillance, closely monitor changes in viral strains, and prepare in advance for HFMD cluster prevention and control. Hand foot and mouth disease clusters Epidemiology Pathogenesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. INTRODUCTION Hand, foot, and mouth disease (HFMD) is a common infectious disease caused by infection with enteroviruses. It can be transmitted through direct or indirect routes, such as the fecal-oral route or via respiratory droplets. The disease primarily affects children < 5 years of age, who are more susceptible to severe complications due to their relatively lower immune levels. 1 Clinical manifestations primarily include fever and the appearance of rashes or blisters on the hands, feet, mouth, buttocks, and other areas. Most patients experience mild symptoms; however, a small number may develop aseptic meningitis, encephalitis, or myocarditis. In rare cases, severe illness in children can progress rapidly and may lead to death. 2 HFMD was first identified and named in New Zealand in 1957. Subsequently, large-scale clusters have occurred in various geographical regions, particularly in East and Southeast Asia. 3 – 5 In 2008, a severe outbreak of HFMD occurred in Anhui Province, China, primarily caused by EV-A71, resulting in tens of thousands of infections and > 100 deaths. 6 In May 2008, China classified HFMD as a Category C infectious disease for management. 2 Since 2008, HFMD cases have been reported annually in Beijing. In 2008, the number of cases exceeded 10,000, primarily affecting children < 5 years of age. 7 Initially, HFMD was primarily caused by EV-A71 and CV-A16. The Beijing municipal government and health authorities placed high importance on the disease, strengthening epidemic surveillance and prevention and control measures. 8 In 2016, the promotion of EV-A71 vaccination led to a significant reduction in HFMD cases caused by EV-A71. However, cases caused by CV-A6, CV-A16, and other enteroviruses continue to be prevalent. 9 , 10 In recent years, the reported number of HFMD cases in Beijing still accounts for a relatively high proportion of notifiable infectious diseases. 11 The clusters occur frequently every year, with young children remaining the primary target of the virus, and schools and childcare institutions continue to be hotspots for disease clusters. This study analyzed the epidemiological trends and etiological characteristics of HFMD clusters in Beijing from 2019 to 2024, and used the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the incidence of HFMD clusters in Beijing for 2025. The aim was to better understand the characteristics of HFMD clusters in Beijing and to implement preventive measures in advance to address potential epidemics in the coming year. 2. MATERIALS AND METHODS 2.1 Data source Data used for this study comprised surveillance information on HFMD clusters in Beijing from 2019 to 2024. According to the regulations set by Beijing’s health administrative departments, whenever an HFMD cluster occurs, the local district Centers for Disease Control and Prevention (CDC) must conduct epidemiological investigations, cluster management, and pathogen detection, with all relevant information reported to the Beijing Center for Disease Prevention and Control. 2.2 Related Definitions 2.2.1 HFMD clusters According to the Beijing HFMD and Herpangina Surveillance and Outbreak Response Work Plan (2024 Edition), an HFMD cluster is defined as follows: > 5 but < 10 cases occurring within 1 week in the same childcare facility, preschool, school, or other collective institution; ≥ 2 cases occurring in the same class (or dormitory); ≥ 3 but < 5 cases occurring in the same natural village/neighborhood committee; or ≥ 2 cases occurring within the same household. 2.2.2 Regional Division of Beijing Beijing comprises 16 administrative districts that can be categorized based on factors including geographical location, urban functional layout, economic development level, and population density in the central area (Districts of Dongcheng, Xicheng, Chaoyang, Haidian, Fengtai, and Shijingshan), nearby suburbs (Districts of Daxing, Tongzhou, Shunyi, Changping, Mentougou, Fangshan), and outer suburbs (Districts of Huairou, Pinggu, Yanqing and Miyun). 2.3 Requirements for cluster management and sample collection The epidemiological investigation performed for HFMD clusters included collecting information regarding the time, location, type of institution, demographic details of cases, and details regarding the onset of illness and medical visits. At least two case specimens were collected from each cluster for pathogen detection. 2.4 Data processing and statistical analyses Information regarding the clusters is summarized using spreadsheet software (Excel, Microsoft Corp., Redmond, WA, USA). Quantitative data, such as age, are expressed as median (interquartile range [IQR]), while categorical data, such as sex, were compared using the chi-squared test. The Kruskal–Wallis test was used to statistically compare the differences in the cluster scale caused by different types of enteroviruses, followed by pairwise comparisons. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA). The regional distribution was visualized using ArcMap 10.6. The prediction of HFMD clusters in Beijing for 2025 was performed using R version 4.4.2 (R Core Team [2020]; R Foundation for Statistical Computing, Vienna, Austria), and SARIMA (2,0,0)(0,1,1) 12 was generated as the optimum model, with an Akaike information criterion of 160.64, and root mean square error of 0.74. 3. RESULTS From 2019 to 2024, Beijing reported 4265 HFMD clusters, with an average of 710 clusters annually, involving 18,365 cases. Among these, 12,396 patients, with a median age of 5 years, were investigated in detail. Of the 4265 clusters, those involving < 5 cases, 5–9 cases, 10–19 cases, and ≥ 20 cases accounted for 77.2% (3291/4265), 11.2% (476/4265), 10.5% (446/4265), and 1.2% (52/4265), respectively. The overall attack rate of HFMD clusters in schools and childcare institutions was 2.2%, with the attack rate per cluster ranging from 0.08–3.2%. The trends in the number of reported HFMD cases and clusters in Beijing from 2019 to 2024 were consistent, exhibiting an alternating high-incidence pattern every other year (Fig. 1 ). The median interval between the onset date of the first case and the reporting date was 4 days, and the median interval between the onset dates of the first and last cases was 3 days. Using the SARIMA model to predict the incidence of HFMD clusters in Beijing in 2025, the results indicated a bimodal trend with a primary peak in autumn (Fig. 2 ). From 2019 to 2024, the highest number of clusters occurred in 2023, whereas the lowest occurred in 2022. The monthly number of clusters peaked at 714 in September 2023 and dropped to 0 in some months. Seasonally, the cluster peaks mainly occurred in summer and autumn. Bimodal patterns were observed, except in 2020 and 2022, which did not show significant peaks. The annual peak months were November 2019, November 2020, July 2021, September 2022, and June 2023 (Fig. 1 ). Among the 12,396 cases associated with clusters, 57.8% (7164/12,396) comprised male patients, with a male-to-female ratio of 1.4:1. The median patient age was 5 years (IQR 4–7 years) (Table 1 ). Of these, 91.5% were students or preschoolers. Except in 2023, when student cases accounted for 54.4% of the total, preschool students represented the majority annually. Mild cases accounted for 90.9% of all cases (11,266/12,396). The symptoms included fever (69.4% [8,601/12,396]), rash/blisters (84.7% [10,496/12,396]), pneumonia (0.12% [15/12,396]), and encephalitis (0.04% [5/12,396]) (Table 2 ). Table 1 Demographic characteristics of HFMD cluster cases in Beijing during 2019 to 2024 Characteristics 2019 (N = 3522) 2020 (N = 357) 2021 (N = 2095) 2022 (N = 236) 2023 (N = 4762) 2024 (N = 1424) p Age,year,median(IQR) 4(3–5) 4(3–5) 4(4–5) 4(3–6) 6(4–9) 5(4–7) < 0.001 a Sex,n(%) < 0.001 b Boy 2065(58.6) 190(53.2) 1191(56.8) 139(58.9) 2952(62.0) 776(54.5) Girl 1457(46.8) 167(46.8) 904(43.2) 97(41.1) 1810(38.0) 648(45.5) Population type,n(%) < 0.001 b scattered children 307(8.7) 26(7.3) 125(6.0) 33(14.0) 260(5.5) 15(1.1) Kindergarten children 2469(70.1) 256(71.7) 1598(76.3) 153(64.8) 1775(37.3) 926(65.0) Student 649(18.4) 62(17.4) 349(16.7) 46(19.5) 2591(54.4) 466(32.7) Others 97(2.8) 13(3.6) 23(1.1) 4(1.7) 136(2.9) 17(1.2) Symptoms Mild symptoms 3088(87.7) 344(96.4) 1909(91.1) 230(97.5) 4332(91.0) 1363(95.7) Pyrexia 2086(59.2) 232(65.0) 1338(63.9) 145(61.4) 3858(81.0) 942(66.2) vesicles 2991(84.9) 327(91.6) 1834(87.5) 221(93.6) 4013(84.3) 1110(77.9) IQR: Interquartile range a Kruskal-Wallis test. b Chi-square test. Note: The comparison of the demographic characteristics of HFMD cases across different years. Table 2 Characteristics of HFMD cluster in Beijing during 2019 to 2024 Variables 2019(N = 1206) 2020(N = 140) 2021(N = 678) 2022(N = 98) 2023(N = 1719) 2024(N = 424) p Location,n(%) < 0.001 a Kindergarten 695(57.6) 78(55.7) 417(61.5) 42(42.9) 547(31.8) 262(61.8) School 158(13.1) 16(11.4) 76(11.2) 9(9.2) 772(44.9) 107(25.2) Household 349(28.9) 44(31.4) 173(25.5) 45(45.9) 383(22.3) 52(12.3) Community/Others 4(0.3) 2(1.4) 12(1.8) 2(2.0) 17(1.0) 3(0.7) Region,n(%) < 0.001 b Central area 540(44.8) 60(42.9) 254(37.5) 27(27.6) 561(32.6) 183(43.2) Near suburbs 542(44.9) 75(53.6) 357(52.7) 66(67.3) 910(52.9) 203(47.9) Other suburbs 124(10.3) 5(3.6) 67(9.9) 5(5.1) 248(14.4) 38(9.0) Among all the outbreak locations from 2019 to 2024, kindergartens accounted for the highest proportion (52.7%), followed by schools (29.4%), and households/communities (17.9%). According to location, the proportion of kindergarten clusters was highest in 2024 (65.6%) and lowest in 2023 (32.0%). The proportion of clusters in schools was the highest in 2023 (50.7%) and lowest in 2022 (9.3%). The proportion of clusters in households/communities was the highest in 2022 (39.8%) and lowest in 2024 (7.9%) (Fig.3). From 2019 to 2024, the districts with the highest number of clusters were Chaoyang (707), Daxing (614), and Fangshan (480). The district with the fewest clusters was Mentougou (10 clusters). The central area, near the suburbs, and the outer suburbs reported 1625 (38.1%), 2153 (50.5%), and 487 (11.4%) clusters, respectively. In 2020 and 2022, the number of clusters was relatively low due to the impact of the coronavirus disease 2019 (COVID-19) pandemic, with no significant differences among the districts[Fig.4(B)(D)]. In 2019, 2021, 2023 and 2024, except for the Mentougou District, the number of clusters in the central area and near the suburbs was significantly higher than that in the outer suburbs[Fig.4(A)(C)(E)(F)]. The number of clusters in the Fangshan and Huairou districts exceeded 100 by 2023 . Fig.4. A total of 9767 specimens from cluster-related specimens were collected, corresponding to a positivity rate of 76.4% (7466/9767). Among the positive samples, the proportion of each subtype was as follows: CV-A6 (60.2%), other enteroviruses (21.7%), CV-A16 (16.9%), CV-A10 (1.2%), and EV-A71 (0.12%). The year with the highest positivity rate was 2024 (82.8% [840/1015]), while the year with the lowest positivity rate was 2022 (61.0% [128/210]) (Fig.5A). Except for 2024, when other enteroviruses accounted for 50%, the dominant strain was CV-A6, with its proportion reaching its highest value (90.7%) in 2023. Both CV-A16 and CV-A6 were present in all years. Monthly data revealed that the proportion of CV-A6 initially decreased and then increased, reaching its lowest point in June (21.6%), and gradually rising to its peak in November (70.8%) (Fig.5B). In contrast, the proportions of CV-A16 and other enteroviruses exhibited the opposite trend, initially increasing and then decreasing. Fig.5. The Kruskal–Wallis test was used to statistically compare differences in the number of cases caused by EV-A71, CV-A16, CV-A6, and other enteroviruses. The results revealed that the overal differences in cluster scale caused by the four types were statistically significant (χ²= 137.32, P < 0.001)(Table 3). Further pairwise comparisons revealed that these differences were mainly reflected in the cluster scales caused by CV-A16, CV-A6 (P < 0.001), CV-A6, and other enteroviruses (P < 0.001). Table 3 Cluster scale caused by pathogen spectrum Pathogen spectrum EV71 CoxA16 CoxA6 coxA10 OtherEV P Number of cases (median,IQR) 4(2,12) 3(2,9) 2(2,3) 2(2,4) 3(2,5) < 0.001 a IQR: Interquartile range a Kruskal-Wallis test. 4. DISCUSSION Results of the present study revealed that HFMD clusters in Beijing, from 2019 to 2024, exhibited a high incidence every other year, which is consistent with the overall trend of HFMD in Beijing. Research suggests that the biennial cycle of HFMD epidemics may be related to changes in the dominant circulating strains. 12 During this period, the incidence of HFMD clusters was relatively low from 2020 to 2022, likely because Beijing was managing a severe period of the COVID-19 pandemic. COVID-19 and HFMD share common transmission routes. A series of non-pharmacological interventions, such as “wearing masks, frequent handwashing, regular ventilation, and maintaining safe social distancing,” 13 which also effectively curbed the spread of HFMD. Shanghai, another megacity in China, exhibited comparable epidemic characteristics. 14 This may be because COVID-19 prevention and control measures influenced the transmission patterns of enteroviruses, leading to an atypical incidence pattern of HFMD. 15 The increase in the number of clusters in 2023 and the emergence of a large autumn peak indicate that the control measures during the COVID-19 pandemic did not have a lagging effect on the prevention and control of HFMD. The higher number of HFMD clusters in Beijing in 2023 may be attributed to the lower incidence of HFMD during the COVID-19 control period, resulting in reduced immunity levels among children against enteroviruses. After the control measures were lifted, increased social interactions and the heightened susceptibility of children to enteroviruses led to an increase in HFMD cases in 2023. 16 The seasonal epidemic characteristics of HFMD in Beijing were pronounced, likely influenced by climatic factors such as temperature and humidity. The peak incidence occurred during the epidemic season, reaching the highest level of clusters annually. In recent years, the high incidence of HFMD in autumn and winter has become particularly evident. The seasonal time-series model predicted that the epidemic characteristics of HFMD in Beijing in 2025 will be consistent with those in previous years, exhibiting a bimodal pattern with a primary peak in autumn. This phenomenon is reasonable because, even if 2025 is a high-incidence year, it is unlikely to reach the level of 2023 because the population's immunity to enteroviruses is not as low as during the COVID-19 pandemic period. The median age of cases involved in the clusters was 5 years, which was significantly higher than the median age of the overall cases in Beijing. 17 This is because the clusters predominantly occurred in schools and kindergartens, and sporadic cases among preschool children were not included. In addition, household clusters accounted for a smaller proportion of the sample, leading to an overall older age distribution. The median age exhibited an increasing trend annually, reaching 6.7 in 2023. The cases predominantly exhibited mild symptoms and a high proportion of rashes, which aligns with the characteristics of HFMD caused by the CV-A6 strain. 18 Among the cases involved in the clusters, preschool students accounted for the vast majority, indicating that HFMD clusters primarily occur in younger children. The higher proportion of males observed was consistent with findings from other studies. 19 - 21 This may be related to the fact that boys generally exhibit more active and energetic behaviors. In Beijing, the highest proportion of HFMD clusters were observed in kindergartens. Compared with schools, kindergartens are higher-risk settings for clusters, which may be related to the higher risk for HFMD infection among younger children. 22 The majority (77.2%) of clusters involved < 5 cases, indicating that most clusters likely occurred primarily within individual classes. Therefore, it is crucial to secure a “classroom” as a key control point. Containing the transmission chain within the classroom helps curb further spread of the cluster. Studies have shown that asymptomatic carriers are a significant risk factor for the transmission of HFMD in schools and kindergartens. 15,23 Therefore, enhancing ventilation, disinfection, frequent hand washing, and maintaining hygiene within classrooms are crucial measures for preventing the spread of clusters. Studies have shown that implementing zoned and grade-segregated teaching in childcare institutions can help control HFMD clusters. 24 It is recommended that kindergartens should establish reasonable teaching mechanisms and improve educational environments. For clusters occurring in schools and households that account for similar proportions, schools and kindergartens are advised to strengthen communication with families, encourage children to develop the habit of washing their hands when returning home to prevent transfer of the virus, and report any relevant symptoms to schools and teachers immediately to avoid further transmission. Our results show that the regional distribution characteristics of HFMD clusters in Beijing are consistent with previous research findings. 17,25 The regional distribution of HFMD clusters in Beijing exhibits the following pattern, with no significant annual variation: near suburbs > central areas > outer suburbs. Beijing, the capital of China, has a dense population and high mobility. The central area is relatively small and is primarily inhabited by permanent residents with Beijing household registration. The outer suburbs cover a vast area, but are far from administrative and financial centers, making employment less convenient. Therefore, for easier access to jobs and education, many migrants reside near the suburbs. Further prevention and control strategies should be developed for areas with dense migrant populations and urban–rural junctions, along with targeted health education campaigns. Studies have shown that the per capita greenspace area is a protective factor against HFMD incidence. 26 Recommendations are to increase greenspaces in the near suburbs and urban–rural junctions of Beijing, improve living environments, and control the spread of HFMD using scientific principles. The incidence of HFMD is not only higher in urban areas but also exhibits a higher number of severe cases and mortality rates in rural areas. 27 As such, it is essential to focus on preventing the spread of HFMD in urban areas while also improving medical treatment capabilities in suburban areas to strictly prevent severe cases of illness and deaths. From 2019 to 2024, the dominant strain causing HFMD clusters in Beijing was CV-A6, whereas clusters caused by EV-A71 were rare. In recent years, the proportions of CV-A6, CV-A16, and other enteroviruses have stabilized. Related studies have indicated that the pathogen spectrum of HFMD has shifted, with serotypes, such as CV-A6 and CV-A10, gradually replacing EV-A71 and CV-A16 as the primary pathogens. 28 However, such a shift has not yet occurred in Beijing. CV-A16 and other enteroviruses still accounted for a significant proportion, while CV-A6, although dominant, rarely exceeded 50%, and CV-A10 remained extremely low. The trends in the proportions of CV-A16 and other enteroviruses were consistent, whereas the proportion of CV-A6 decreased during the summer epidemic, exhibiting the opposite trend to that of CV-A16 and CV-A10. Previous studies have indicated a correlation between the incidence of HFMD and the different viral strains. 29 This study found that the scale of the clusters caused by different pathogen types varied. Compared with HFMD caused by CV-A16 and other enteroviruses, the clusters caused by CV-A6 were relatively smaller. This may be related to the high transmissibility and lower virulence of CV-A6, which can trigger clusters with fewer infected cases, but is less likely to cause large-scale infections due to its weaker pathogenicity. 30 5. CONCLUSION HFMD clusters in Beijing exhibited a biennial cycle with alternating high-incidence years. It is essential to further strengthen prevention and control measures in kindergartens and schools near the suburbs, implement strategies based on the characteristics of circulating viral strains, and prepare for upcoming epidemic seasons. Abbreviations DC Dongcheng XC Xicheng CY Chaoyang HD Haidian FT Fengtai SJS Shijingshan DX Daxing TZ Tongzhou SY Shunyi CP Changping MTG Mentougou FS Fangshan HR Huairou PG Pinggu MY Miyun YQ Yanqing). Declarations Funding information: Special Research Project for Capital Health Development (grant No: 2024-2G-3016); Capital's Funds for Health Improvement and Research (2022-1G-3014); High Level Public Health Technical Talent Training Plan (xuekedaitouren-01-03). Funding This study was supported by Special Research Project for Capital Health Development (grant No: 2024-2G-3016), Capital's Funds for Health Improvement and Research (2022-1G-3014), High Level Public Health Technical Talent Training Plan (xuekedaitouren-01-03). Ethics approval and consent to participate This study adhered to the Helsinki Declaration and was approved by the Human Research Ethics Committee of Beijing Center for Disease Control and Prevention (Beijing CDC). Informed consent was obtained from either the patient or the patient's guardian for sample collection. Consent for publication Not applicable. Availability of data and materials The analytical data in this study were sourced from the Beijing Center for Disease Control and Prevention(Beijing CDC) surveillance system and cannot be publicly disclosed due to privacy protection regulations. De-identified data are available from the corresponding author upon request. Competing interests The authors declare that they have no competing interests. Authors' contributions Hao Zhao and Da Huo and Shuaibing Dong and Jiaxin Feng are responsible for data collection and compilation. Da Huo and Zhiyong Gao and Lei Jia conducted the statistical design, Hao Zhao and Hui Xu performed the statistical analysis, Renqing Li and Zhichao Liang and Yang Yang conducted laboratory testing, Xiaoli Wang and Peng Yang and Daitao Zhang designed and guided the research approach. References Ramdass P, Mullick S, Farber HF. Viral skin diseases[J]. Prim Care, 2015, 42(4): 517-567. DOI: 10.1016/j.pop.2015.08.006. 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Peking Univ Heal Sci. 221;53:491-7. 10.19723/j.issn.1671-167X.2021.03.009. Huang L, Wang T, Liu X, Fu Y, Zhang S, Chu Q, Nie T, Tu H, Cheng J, Fan Y. Spatial-temporal-demographic and virological changes of hand, foot and mouth disease incidence after vaccination in a vulnerable region of China. BMC Public Health. 2022 Aug 1;22(1):1468. doi: 10.1186/s12889-022-13860-z. Wang J , Zheng J S , Zhang Y H .The comparisons of procalcitonin and age between mild and severe Hand, foot, and mouth disease[J].Translational Pediatrics, 2023, 12(4):7.DOI:10.21037/tp-23-146. Thammasonthijarern N, Kosoltanapiwat N, Nuprasert W, Sittikul P, Sriburin P, Pan-Ngum W, Maneekan P, Hataiyusuk S, Hattasingh W, Thaipadungpanit J, Chatchen S. Molecular Epidemiological Study of Hand, Foot, and Mouth Disease in a Kindergarten-Based Setting in Bangkok, Thailand. Pathogens. 2021 May 10;10(5):576. doi: 10.3390/pathogens10050576. PMID: 34068676; PMCID: PMC8150733. Liu X, Hou W, Zhao Z, Cheng J, van Beeck EF, Peng X, Jones K, Fu X, Zhou Y, Zhang Z, Richardus JH, Erasmus V. A hand hygiene intervention to decrease hand, foot and mouth disease and absence due to sickness among kindergarteners in China: A cluster-randomized controlled trial. J Infect. 2019 Jan;78(1):19-26. doi: 10.1016/j.jinf.2018.08.009. Epub 2018 Aug 19. PMID: 30134143. Jia J, Kong F, Xin X, Liang J, Xin H, Dong L, et al. Epidemiological Characteristics of Hand, Foot, and Mouth Disease clusters in Qingdao, 2009–2018. Iran J Public Health. 2021;50(5):999–1008. Epub 2021/06/30. doi: 10.18502/ijph.v50i5.6117 ; PubMed Central PMCID: PMC8223573. Wang, Y., Peng, W., Su, H., & Wang, W. (2022). Spatiotemporal characteristics of hand, foot, and mouth disease and influencing factors in China from 2011 to 2018. Chinese Journal of Epidemiology, 43(10), 1562-1567. Chen L, Xing Y, Zhang Y, Xie J, Su B, Jiang J, Geng M, Ren X, Guo T, Yuan W, Ma Q, Chen M, Cui M, Liu J, Song Y, Wang L, Dong Y, Ma J. Long-term variations of urban-Rural disparities in infectious disease burden of over 8.44 million children, adolescents, and youth in China from 2013 to 2021: An observational study. PLoS Med. 2024 Apr 12;21(4):e1004374. doi: 10.1371/journal.pmed.1004374. Wang J, Zhang S. Epidemiological characteristics and trends of hand-foot-mouth disease in Shanghai, China from 2011 to 2021. Front Public Health. 2023 May 30;11:1162209. doi: 10.3389/fpubh.2023.1162209. PMID: 37325298; PMCID: PMC10267978. Zhou X, Qian K, Zhu C, Yi L, Tu J, Yang S, Zhang Y, Zhang Y, Xia W, Ni X, Xu T, He F, Li H. Surveillance, epidemiology, and impact of the coronavirus disease 2019 interventions on the incidence of enterovirus infections in Nanchang, China, 2010-2022. Front Microbiol. 2023 Oct 18;14:1251683. doi: 10.3389/fmicb.2023.1251683. PMID: 37920267; PMCID: PMC10618362. Yuan Y, Chen Y, Huang J, Bao X, Shen W, Sun Y, Mao H. Epidemiological and etiological investigations of hand, foot, and mouth disease in Jiashan, northeastern Zhejiang Province, China, during 2016 to 2022. Front Public Health. 2024 May 1;12:1377861. doi: 10.3389/fpubh.2024.1377861. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6327143","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451034191,"identity":"f7e7f3b3-5d61-4bc4-bda0-95f2b4b57600","order_by":0,"name":"Hao Zhao","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Zhao","suffix":""},{"id":451034194,"identity":"7dde1e21-1329-4a72-ab07-15bbf2696fce","order_by":1,"name":"Da Huo","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Da","middleName":"","lastName":"Huo","suffix":""},{"id":451034196,"identity":"c1ca57f5-e6a4-48f8-94a8-644e713768b2","order_by":2,"name":"Hui Xu","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Xu","suffix":""},{"id":451034197,"identity":"2f38927e-1bec-4d08-9ecf-3e798d1b030f","order_by":3,"name":"Zhiyong Gao","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Zhiyong","middleName":"","lastName":"Gao","suffix":""},{"id":451034198,"identity":"dc7062c5-59a3-4d4a-b1e2-d04bcd987fae","order_by":4,"name":"Shuaibing Dong","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Shuaibing","middleName":"","lastName":"Dong","suffix":""},{"id":451034199,"identity":"c6fdbd91-3eaa-42d2-b8f8-2b41ade2d3df","order_by":5,"name":"Jiaxin Feng","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Jiaxin","middleName":"","lastName":"Feng","suffix":""},{"id":451034200,"identity":"c1662c92-aeba-481e-93d2-9381f51ca749","order_by":6,"name":"Renqing Li","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Renqing","middleName":"","lastName":"Li","suffix":""},{"id":451034201,"identity":"c7f40b46-e50c-485e-ba5c-2be4ffa62b20","order_by":7,"name":"Zhichao Liang","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Zhichao","middleName":"","lastName":"Liang","suffix":""},{"id":451034202,"identity":"297a402e-d23b-4eb6-a4e1-5b086903c774","order_by":8,"name":"Yang Yang","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Yang","suffix":""},{"id":451034203,"identity":"94903ef9-a763-4e67-85ac-77e4a091d323","order_by":9,"name":"Lei Jia","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Jia","suffix":""},{"id":451034204,"identity":"65cfbcc6-87db-4ccc-9bb7-b8453d1cc35e","order_by":10,"name":"Xiaoli Wang","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Wang","suffix":""},{"id":451034205,"identity":"a78130c6-7522-4ae6-9410-7d1dabcccc66","order_by":11,"name":"Peng Yang","email":"","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Yang","suffix":""},{"id":451034206,"identity":"02f0744a-dade-46ab-8d82-fce6be265164","order_by":12,"name":"Daitao Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYFCCBIYDCRU2PPz8DURrSWZ88OBMmozkjAPEa2E2fNhy2MagIYFIDfLt+cckEhvO8xgwHGD88DGHCC2MPY/ZJBJ33OYxZ25glpy5jQgtzBLJQC1nbvNYNhxgY+YlRgsbWEvbOR6DAwlEauGRSGY2SGw7QIIWCZ7Hhg8SziTzSM442EycX+TbEx8c/FFhZ8/P33zww0ditCABxgbS1I+CUTAKRsEowA0AaSw2hkFsqTwAAAAASUVORK5CYII=","orcid":"","institution":"Beijing Center for Disease Prevention and Control","correspondingAuthor":true,"prefix":"","firstName":"Daitao","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-03-28 10:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6327143/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6327143/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82308483,"identity":"f57d3d07-3987-49c7-ac2d-7d0c976e3b25","added_by":"auto","created_at":"2025-05-09 01:35:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84334,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMonthly distribution of HFMD cases and clusters in Beijing, 2019-2024. \u0026nbsp;Note:\u003c/strong\u003eThe comparison of monthly distribution between HFMD cases and clusters.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6327143/v1/500fef18917c5c30cafd7633.png"},{"id":82308484,"identity":"2461a0de-444f-4a73-9076-f16e652c647d","added_by":"auto","created_at":"2025-05-09 01:35:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46027,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMonthly distribution of HFMD clusters during 2019-2024 and the forecast in 2025.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003eThe blue line represents the forecast of the monthly distribution of HFMD clusters in 2025. The light gray shaded area denotes the 80% confidence interval, and the dark gray area represents the 95% confidence interval.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6327143/v1/907705d70eda0ef7cf0dd0f4.png"},{"id":82308496,"identity":"70fb54c6-8c92-42f3-8e9d-834a38b48dc3","added_by":"auto","created_at":"2025-05-09 01:35:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":30062,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of HFMD cluster locations in Beijing, 2019-2024. Note: Annual percentage distribution of HFMD cluster Locations.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6327143/v1/c03e756814575ddd0bc6e911.png"},{"id":82308494,"identity":"0c3eae67-6e58-4341-92b4-9e3b626c5b62","added_by":"auto","created_at":"2025-05-09 01:35:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":402625,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial distribution of HFMD clusters in Beijing during 2019-2024. (A)Spatial distribution of HFMD clusters in 2019. (B)Spatial distribution of HFMD clusters in 2020. (C)Spatial distribution of HFMD clusters in 2021. (D)Spatial distribution of HFMD clusters in 2022. (E)Spatial distribution of HFMD clusters in 2023. (F)Spatial distribution of HFMD clusters in 2024.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: DC, Dongcheng; XC, Xicheng; CY, Chaoyang; HD, Haidian; FT, Fengtai; SJS, Shijingshan; DX, Daxing; TZ, Tongzhou; SY, Shunyi; CP, Changping; MTG, Mentougou; FS, Fangshan; HR, Huairou; PG, Pinggu; MY, Miyun; YQ, Yanqing).\u003c/p\u003e\n\u003cp\u003eNote: Dots represent the clusters involving more than 10 cases. Central area (Districts of DC, XC, CY, HD, FT, SJS), Nearby suburbs (Districts of DX, TZ, SY, CP, MTG, FS), Outer suburbs (Districts of HR, PG, YQ MY).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6327143/v1/c0949a6712ee9188f01ad9fb.png"},{"id":82309338,"identity":"04e6867f-811a-473e-b5d6-27d5ba3e71d1","added_by":"auto","created_at":"2025-05-09 01:43:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":123766,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePathogen's spectrum of HFMD clusters in Beijing during 2019-2024. (A) The Pathogen spectrum and positivity rate of HFMD clusters. (B) The monthly distribution of HFMD clusters and pathogen spectrum.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6327143/v1/951d72cea7944ceeb0a099f6.png"},{"id":97212347,"identity":"93598b99-006d-4078-b929-9443ed10b1e3","added_by":"auto","created_at":"2025-12-02 05:09:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1667621,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6327143/v1/4385d625-05be-4ae7-b447-6e218111bb7f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiological characteristics of hand, foot, and mouth disease clusters in Beijing, China, 2019–2024","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eHand, foot, and mouth disease (HFMD) is a common infectious disease caused by infection with enteroviruses. It can be transmitted through direct or indirect routes, such as the fecal-oral route or via respiratory droplets. The disease primarily affects children\u0026thinsp;\u0026lt;\u0026thinsp;5 years of age, who are more susceptible to severe complications due to their relatively lower immune levels.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Clinical manifestations primarily include fever and the appearance of rashes or blisters on the hands, feet, mouth, buttocks, and other areas. Most patients experience mild symptoms; however, a small number may develop aseptic meningitis, encephalitis, or myocarditis. In rare cases, severe illness in children can progress rapidly and may lead to death.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e HFMD was first identified and named in New Zealand in 1957. Subsequently, large-scale clusters have occurred in various geographical regions, particularly in East and Southeast Asia.\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e In 2008, a severe outbreak of HFMD occurred in Anhui Province, China, primarily caused by EV-A71, resulting in tens of thousands of infections and \u0026gt;\u0026thinsp;100 deaths.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e In May 2008, China classified HFMD as a Category C infectious disease for management.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSince 2008, HFMD cases have been reported annually in Beijing. In 2008, the number of cases exceeded 10,000, primarily affecting children\u0026thinsp;\u0026lt;\u0026thinsp;5 years of age.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Initially, HFMD was primarily caused by EV-A71 and CV-A16. The Beijing municipal government and health authorities placed high importance on the disease, strengthening epidemic surveillance and prevention and control measures.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In 2016, the promotion of EV-A71 vaccination led to a significant reduction in HFMD cases caused by EV-A71. However, cases caused by CV-A6, CV-A16, and other enteroviruses continue to be prevalent.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e In recent years, the reported number of HFMD cases in Beijing still accounts for a relatively high proportion of notifiable infectious diseases.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e The clusters occur frequently every year, with young children remaining the primary target of the virus, and schools and childcare institutions continue to be hotspots for disease clusters. This study analyzed the epidemiological trends and etiological characteristics of HFMD clusters in Beijing from 2019 to 2024, and used the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the incidence of HFMD clusters in Beijing for 2025. The aim was to better understand the characteristics of HFMD clusters in Beijing and to implement preventive measures in advance to address potential epidemics in the coming year.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data source\u003c/h2\u003e \u003cp\u003eData used for this study comprised surveillance information on HFMD clusters in Beijing from 2019 to 2024. According to the regulations set by Beijing\u0026rsquo;s health administrative departments, whenever an HFMD cluster occurs, the local district Centers for Disease Control and Prevention (CDC) must conduct epidemiological investigations, cluster management, and pathogen detection, with all relevant information reported to the Beijing Center for Disease Prevention and Control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Related Definitions\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 HFMD clusters\u003c/h2\u003e \u003cp\u003eAccording to the Beijing HFMD and Herpangina Surveillance and Outbreak Response Work Plan (2024 Edition), an HFMD cluster is defined as follows: \u0026gt; 5 but \u0026lt;\u0026thinsp;10 cases occurring within 1 week in the same childcare facility, preschool, school, or other collective institution; \u0026ge; 2 cases occurring in the same class (or dormitory); \u0026ge; 3 but \u0026lt;\u0026thinsp;5 cases occurring in the same natural village/neighborhood committee; or \u0026ge;\u0026thinsp;2 cases occurring within the same household.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Regional Division of Beijing\u003c/h2\u003e \u003cp\u003eBeijing comprises 16 administrative districts that can be categorized based on factors including geographical location, urban functional layout, economic development level, and population density in the central area (Districts of Dongcheng, Xicheng, Chaoyang, Haidian, Fengtai, and Shijingshan), nearby suburbs (Districts of Daxing, Tongzhou, Shunyi, Changping, Mentougou, Fangshan), and outer suburbs (Districts of Huairou, Pinggu, Yanqing and Miyun).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Requirements for cluster management and sample collection\u003c/h2\u003e \u003cp\u003eThe epidemiological investigation performed for HFMD clusters included collecting information regarding the time, location, type of institution, demographic details of cases, and details regarding the onset of illness and medical visits. At least two case specimens were collected from each cluster for pathogen detection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data processing and statistical analyses\u003c/h2\u003e \u003cp\u003eInformation regarding the clusters is summarized using spreadsheet software (Excel, Microsoft Corp., Redmond, WA, USA). Quantitative data, such as age, are expressed as median (interquartile range [IQR]), while categorical data, such as sex, were compared using the chi-squared test. The Kruskal\u0026ndash;Wallis test was used to statistically compare the differences in the cluster scale caused by different types of enteroviruses, followed by pairwise comparisons. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA). The regional distribution was visualized using ArcMap 10.6. The prediction of HFMD clusters in Beijing for 2025 was performed using R version 4.4.2 (R Core Team [2020]; R Foundation for Statistical Computing, Vienna, Austria), and SARIMA (2,0,0)(0,1,1)\u003csub\u003e12\u003c/sub\u003e was generated as the optimum model, with an Akaike information criterion of 160.64, and root mean square error of 0.74.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eFrom 2019 to 2024, Beijing reported 4265 HFMD clusters, with an average of 710 clusters annually, involving 18,365 cases. Among these, 12,396 patients, with a median age of 5 years, were investigated in detail. Of the 4265 clusters, those involving\u0026thinsp;\u0026lt;\u0026thinsp;5 cases, 5\u0026ndash;9 cases, 10\u0026ndash;19 cases, and \u0026ge;\u0026thinsp;20 cases accounted for 77.2% (3291/4265), 11.2% (476/4265), 10.5% (446/4265), and 1.2% (52/4265), respectively. The overall attack rate of HFMD clusters in schools and childcare institutions was 2.2%, with the attack rate per cluster ranging from 0.08\u0026ndash;3.2%. The trends in the number of reported HFMD cases and clusters in Beijing from 2019 to 2024 were consistent, exhibiting an alternating high-incidence pattern every other year (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The median interval between the onset date of the first case and the reporting date was 4 days, and the median interval between the onset dates of the first and last cases was 3 days. Using the SARIMA model to predict the incidence of HFMD clusters in Beijing in 2025, the results indicated a bimodal trend with a primary peak in autumn (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFrom 2019 to 2024, the highest number of clusters occurred in 2023, whereas the lowest occurred in 2022. The monthly number of clusters peaked at 714 in September 2023 and dropped to 0 in some months. Seasonally, the cluster peaks mainly occurred in summer and autumn. Bimodal patterns were observed, except in 2020 and 2022, which did not show significant peaks. The annual peak months were November 2019, November 2020, July 2021, September 2022, and June 2023 (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the 12,396 cases associated with clusters, 57.8% (7164/12,396) comprised male patients, with a male-to-female ratio of 1.4:1. The median patient age was 5 years (IQR 4\u0026ndash;7 years) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Of these, 91.5% were students or preschoolers. Except in 2023, when student cases accounted for 54.4% of the total, preschool students represented the majority annually. Mild cases accounted for 90.9% of all cases (11,266/12,396). The symptoms included fever (69.4% [8,601/12,396]), rash/blisters (84.7% [10,496/12,396]), pneumonia (0.12% [15/12,396]), and encephalitis (0.04% [5/12,396]) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic characteristics of HFMD cluster cases in Beijing during 2019 to 2024\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;3522)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;357)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2095)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;236)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;4762)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2024\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;1424)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge,year,median(IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(3\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(3\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(4\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(3\u0026ndash;6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(4\u0026ndash;9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(4\u0026ndash;7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex,n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2065(58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e190(53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1191(56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139(58.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2952(62.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e776(54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGirl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1457(46.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167(46.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e904(43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97(41.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1810(38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e648(45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation type,n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003escattered children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33(14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e260(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKindergarten children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2469(70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e256(71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1598(76.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153(64.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1775(37.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e926(65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e649(18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e349(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46(19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2591(54.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e466(32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3088(87.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e344(96.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1909(91.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e230(97.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4332(91.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1363(95.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2086(59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e232(65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1338(63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145(61.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3858(81.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e942(66.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003evesicles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2991(84.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e327(91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1834(87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e221(93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4013(84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1110(77.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIQR: Interquartile range\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eKruskal-Wallis test.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eChi-square test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u0026nbsp;\u003c/strong\u003eThe comparison of the demographic characteristics of HFMD cases across different years.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of HFMD cluster in Beijing during 2019 to 2024\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2019(N\u0026thinsp;=\u0026thinsp;1206)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2020(N\u0026thinsp;=\u0026thinsp;140)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021(N\u0026thinsp;=\u0026thinsp;678)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022(N\u0026thinsp;=\u0026thinsp;98)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2023(N\u0026thinsp;=\u0026thinsp;1719)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2024(N\u0026thinsp;=\u0026thinsp;424)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation,n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKindergarten\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e695(57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78(55.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e417(61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e547(31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e262(61.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSchool\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e772(44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107(25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHousehold\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e349(28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44(31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e173(25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45(45.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e383(22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52(12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommunity/Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion,n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e540(44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e254(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27(27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e561(32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e183(43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNear suburbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e542(44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75(53.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e357(52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66(67.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e910(52.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e203(47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther suburbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67(9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e248(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38(9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cp\u003eAmong all the outbreak locations from 2019 to 2024, kindergartens accounted for the highest proportion (52.7%), followed by schools (29.4%), and households/communities (17.9%). According to location, the proportion of kindergarten clusters was highest in 2024 (65.6%) and lowest in 2023 (32.0%). The proportion of clusters in schools was the highest in 2023 (50.7%) and lowest in 2022 (9.3%). The proportion of clusters in households/communities was the highest in 2022 (39.8%) and lowest in 2024 (7.9%) (Fig.3).\u003c/p\u003e\n \u003cp\u003eFrom 2019 to 2024, the districts with the highest number of clusters were Chaoyang (707), Daxing (614), and Fangshan (480). The district with the fewest clusters was Mentougou (10 clusters). The central area, near the suburbs, and the outer suburbs reported 1625 (38.1%), 2153 (50.5%), and 487 (11.4%) clusters, respectively. In 2020 and 2022, the number of clusters was relatively low due to the impact of the coronavirus disease 2019 (COVID-19) pandemic, with no significant differences among the districts[Fig.4(B)(D)]. In 2019, 2021, 2023 and 2024, except for the Mentougou District, the number of clusters in the central area and near the suburbs was significantly higher than that in the outer suburbs[Fig.4(A)(C)(E)(F)]. The number of clusters in the Fangshan and Huairou districts exceeded 100 by 2023 .\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFig.4.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eA total of 9767 specimens from cluster-related specimens were collected, corresponding to a positivity rate of 76.4% (7466/9767). Among the positive samples, the proportion of each subtype was as follows: CV-A6 (60.2%), other enteroviruses (21.7%), CV-A16 (16.9%), CV-A10 (1.2%), and EV-A71 (0.12%). The year with the highest positivity rate was 2024 (82.8% [840/1015]), while the year with the lowest positivity rate was 2022 (61.0% [128/210]) (Fig.5A). Except for 2024, when other enteroviruses accounted for 50%, the dominant strain was CV-A6, with its proportion reaching its highest value (90.7%) in 2023. Both CV-A16 and CV-A6 were present in all years. Monthly data revealed that the proportion of CV-A6 initially decreased and then increased, reaching its lowest point in June (21.6%), and gradually rising to its peak in November (70.8%) (Fig.5B). In contrast, the proportions of CV-A16 and other enteroviruses exhibited the opposite trend, initially increasing and then decreasing.\u003c/p\u003e\n \u003cp\u003eFig.5.\u003c/p\u003e\n \u003cp\u003eThe Kruskal\u0026ndash;Wallis test was used to statistically compare differences in the number of cases caused by EV-A71, CV-A16, CV-A6, and other enteroviruses. The results revealed that the overal differences in cluster scale caused by the four types were statistically significant (\u0026chi;\u0026sup2;= 137.32, P \u0026lt; 0.001)(Table 3). Further pairwise comparisons revealed that these differences were mainly reflected in the cluster scales caused by CV-A16, CV-A6 (P \u0026lt; 0.001), CV-A6, and other enteroviruses (P \u0026lt; 0.001).\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCluster scale caused by pathogen spectrum\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePathogen spectrum\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEV71\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCoxA16\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCoxA6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ecoxA10\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOtherEV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of cases (median,IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(2,12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(2,9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(2,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(2,4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(2,5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eIQR: Interquartile range\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003eKruskal-Wallis test.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eResults of the present study revealed that HFMD clusters in Beijing, from 2019 to 2024, exhibited a high incidence every other year, which is consistent with the overall trend of HFMD in Beijing. Research suggests that the biennial cycle of HFMD epidemics may be related to changes in the dominant circulating strains.\u003csup\u003e12\u0026nbsp;\u003c/sup\u003eDuring this period, the incidence of HFMD clusters was relatively low from 2020 to 2022, likely because Beijing was managing a severe period of the COVID-19 pandemic.\u0026nbsp;COVID-19 and HFMD share common transmission routes. A series of non-pharmacological interventions, such as \u0026ldquo;wearing masks, frequent handwashing, regular ventilation,\u0026nbsp;and maintaining safe social distancing,\u0026rdquo;\u003csup\u003e13\u003c/sup\u003e which also effectively curbed the spread of HFMD. Shanghai, another megacity in China, exhibited comparable epidemic characteristics.\u003csup\u003e14\u0026nbsp;\u003c/sup\u003eThis may be because COVID-19 prevention and control measures influenced the transmission patterns of enteroviruses, leading to an atypical incidence pattern of HFMD.\u003csup\u003e15\u0026nbsp;\u003c/sup\u003eThe increase in the number of clusters in 2023 and the emergence of a large autumn peak indicate that the control measures during the COVID-19 pandemic did not have a lagging effect on the prevention and control of HFMD. The higher number of HFMD clusters in Beijing in 2023 may be attributed to the lower incidence of HFMD during the COVID-19 control period, resulting in reduced immunity levels among children against enteroviruses. After the control measures were lifted, increased social interactions and the heightened susceptibility of children to enteroviruses led to an increase in HFMD cases in 2023.\u003csup\u003e16\u0026nbsp;\u003c/sup\u003eThe seasonal epidemic characteristics of HFMD in Beijing were pronounced, likely influenced by climatic factors such as temperature and humidity. The peak incidence occurred during the epidemic season, reaching the highest level of clusters annually. In recent years, the high incidence of HFMD in autumn and winter has become particularly evident. The seasonal time-series model predicted that the epidemic characteristics of HFMD in Beijing in 2025 will be consistent with those in previous years, exhibiting a bimodal pattern with a primary peak in autumn. This phenomenon is reasonable because, even if 2025 is a high-incidence year, it is unlikely to reach the level of 2023 because the population\u0026apos;s immunity to enteroviruses is not as low as during the COVID-19 pandemic period.\u003c/p\u003e\n\u003cp\u003eThe median age of cases involved in the clusters was 5 years, which was significantly higher than the median age of the overall cases in Beijing.\u003csup\u003e17\u0026nbsp;\u003c/sup\u003eThis is because the clusters predominantly occurred in schools and kindergartens, and sporadic cases among preschool children were not included. In addition, household clusters accounted for a smaller proportion of the sample, leading to an overall older age distribution. The median age exhibited an increasing trend annually, reaching 6.7 in 2023. The cases predominantly exhibited mild symptoms and a high proportion of rashes, which aligns with the characteristics of HFMD caused by the CV-A6 strain.\u003csup\u003e18\u003c/sup\u003eAmong the cases involved in the clusters, preschool students accounted for the vast majority, indicating that HFMD clusters primarily occur in younger children. The higher proportion of males observed was consistent with findings from other studies.\u003csup\u003e19\u003c/sup\u003e\u003csup\u003e-\u003c/sup\u003e\u003csup\u003e21\u0026nbsp;\u003c/sup\u003eThis may be related to the fact that boys generally exhibit more active and energetic behaviors.\u003c/p\u003e\n\u003cp\u003eIn Beijing, the highest proportion of HFMD clusters were observed in kindergartens. Compared with schools, kindergartens are higher-risk settings for clusters, which may be related to the higher risk for HFMD infection among younger children.\u003csup\u003e22\u003c/sup\u003e The majority (77.2%) of clusters involved \u0026lt; 5 cases, indicating that most clusters likely occurred primarily within individual classes. Therefore, it is crucial to secure a \u0026ldquo;classroom\u0026rdquo; as a key control point. Containing the transmission chain within the classroom helps curb further spread of the cluster. Studies have shown that asymptomatic carriers are a significant risk factor for the transmission of HFMD in schools and kindergartens.\u003csup\u003e15,23\u0026nbsp;\u003c/sup\u003eTherefore, enhancing ventilation, disinfection, frequent hand washing, and maintaining hygiene within classrooms are crucial measures for preventing the spread of clusters. Studies have shown that implementing zoned and grade-segregated teaching in childcare institutions can help control HFMD clusters.\u003csup\u003e24\u003c/sup\u003e It is recommended that kindergartens should establish reasonable teaching mechanisms and improve educational environments. For clusters occurring in schools and households that account for similar proportions, schools and kindergartens are advised to strengthen communication with families, encourage children to develop the habit of washing their hands when returning home to prevent transfer of the virus, and report any relevant symptoms to schools and teachers immediately to avoid further transmission. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur results show that the regional distribution characteristics of HFMD clusters in Beijing are consistent with previous research findings.\u003csup\u003e17,25\u003c/sup\u003e The regional distribution of HFMD clusters in Beijing exhibits the following pattern, with no significant annual variation: near suburbs \u0026gt; central areas \u0026gt; outer suburbs. Beijing, the capital of China, has a dense population and high mobility. The central area is relatively small and is primarily inhabited by permanent residents with Beijing household registration. The outer suburbs cover a vast area, but are far from administrative and financial centers, making employment less convenient. Therefore, for easier access to jobs and education, many migrants reside near the suburbs. Further prevention and control strategies should be developed for areas with dense migrant populations and urban\u0026ndash;rural junctions, along with targeted health education campaigns. Studies have shown that the per capita greenspace area is a protective factor against HFMD incidence.\u003csup\u003e26\u0026nbsp;\u003c/sup\u003eRecommendations are to increase greenspaces in the near suburbs and urban\u0026ndash;rural junctions of Beijing, improve living environments, and control the spread of HFMD using scientific principles. The incidence of HFMD is not only higher in urban areas but also exhibits a higher number of severe cases and mortality rates in rural areas.\u003csup\u003e27\u0026nbsp;\u003c/sup\u003eAs such, it is essential to focus on preventing the spread of HFMD in urban areas while also improving medical treatment capabilities in suburban areas to strictly prevent severe cases of illness and deaths.\u003c/p\u003e\n\u003cp\u003eFrom 2019 to 2024, the dominant strain causing HFMD clusters in Beijing was CV-A6, whereas clusters caused by EV-A71 were rare. In recent years, the proportions of CV-A6, CV-A16, and other enteroviruses have stabilized. Related studies have indicated that the pathogen spectrum of HFMD has shifted, with serotypes, such as CV-A6 and CV-A10, gradually replacing EV-A71 and CV-A16 as the primary pathogens.\u003csup\u003e28\u0026nbsp;\u003c/sup\u003eHowever, such a shift has not yet occurred in Beijing. CV-A16 and other enteroviruses still accounted for a significant proportion, while CV-A6, although dominant, rarely exceeded 50%, and CV-A10 remained extremely low. The trends in the proportions of CV-A16 and other enteroviruses were consistent, whereas the proportion of CV-A6 decreased during the summer epidemic, exhibiting the opposite trend to that of CV-A16 and CV-A10. Previous studies have indicated a correlation between the incidence of HFMD and the different viral strains.\u003csup\u003e29\u0026nbsp;\u003c/sup\u003eThis study found that the scale of the clusters caused by different pathogen types varied. Compared with HFMD caused by CV-A16 and other enteroviruses, the clusters caused by CV-A6 were relatively smaller. This may be related to the high transmissibility and lower virulence of CV-A6, which can trigger clusters with fewer infected cases, but is less likely to cause large-scale infections due to its weaker pathogenicity.\u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eHFMD clusters in Beijing exhibited a biennial cycle with alternating high-incidence years. It is essential to further strengthen prevention and control measures in kindergartens and schools near the suburbs, implement strategies based on the characteristics of circulating viral strains, and prepare for upcoming epidemic seasons.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDongcheng\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eXC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eXicheng\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCY\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChaoyang\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHaidian\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFengtai\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSJS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eShijingshan\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDX\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDaxing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTZ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTongzhou\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSY\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eShunyi\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChangping\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMTG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMentougou\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFangshan\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuairou\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePinggu\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMY\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMiyun\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eYQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eYanqing).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpecial Research Project for Capital Health Development (grant No: 2024-2G-3016); Capital\u0026apos;s Funds for Health Improvement and Research (2022-1G-3014); High Level Public Health Technical Talent Training Plan (xuekedaitouren-01-03).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Special Research Project for Capital Health Development (grant No: 2024-2G-3016), Capital\u0026apos;s Funds for Health Improvement and Research (2022-1G-3014), High Level Public Health Technical Talent Training Plan (xuekedaitouren-01-03).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhered to the Helsinki Declaration and was approved by the Human Research Ethics Committee of Beijing Center for Disease Control and Prevention (Beijing CDC). Informed consent was obtained from either the patient or the patient\u0026apos;s guardian for sample collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analytical data in this study were sourced from the Beijing Center for Disease Control and Prevention(Beijing CDC) surveillance system and cannot be publicly disclosed due to privacy protection regulations. De-identified data are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHao Zhao and Da Huo and Shuaibing Dong and Jiaxin Feng are responsible for data collection and compilation. Da Huo and Zhiyong Gao and Lei Jia conducted the statistical design, Hao Zhao and Hui Xu performed the statistical analysis, Renqing Li and Zhichao Liang and Yang Yang conducted laboratory testing, Xiaoli Wang and Peng Yang and Daitao Zhang designed and guided the research approach.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eRamdass P, Mullick S, Farber HF. Viral skin diseases[J]. Prim Care, 2015, 42(4): 517-567. 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Front Public Health. 2023 May 30;11:1162209. doi: 15.3389/fpubh.2023.1162209. PMID: 37325298; PMCID: PMC10267978.\u003c/li\u003e\n \u003cli\u003eYuan Y, Chen Y, Huang J, Bao X, Shen W, Sun Y, Mao H. Epidemiological and etiological investigations of hand, foot, and mouth disease in Jiashan, northeastern Zhejiang Province, China, during 2016 to 2022. Front Public Health. 2024 May 1;12:1377861. doi: 10.3389/fpubh.2024.1377861. PMID: 38751577; PMCID: PMC11094292.\u003c/li\u003e\n \u003cli\u003eDing Z, Lu Q, Wu H, Wu C, Lin J, Wang X, Fu T, Yang K, Song Q. Trend of hand, foot and mouth disease before, during, and after China\u0026apos;s COVID control policies in Zhejiang, China. Front Public Health. 2024 Nov 19;12:1472944. doi: 10.3389/fpubh.2024.1472944. PMID: 39628807; PMCID: PMC11611829.\u003c/li\u003e\n \u003cli\u003eZhao, H., Pu, X., Dong, S., et al. Epidemiological characteristics and spatiotemporal clustering analysis of hand, foot, and mouth disease in Beijing, 2017\u0026ndash;2019. International Journal of Virology, 29(6), 6. DOI:10.3760/cma.j.issn.1673-4092.2022.06.005\u003c/li\u003e\n \u003cli\u003eZhu, P., Ji, W., Li, D. et al. Current status of hand-foot-and-mouth disease. J Biomed Sci 30, 15 (2023). https://doi.org/10.1186/s12929-023-00908-4.\u003c/li\u003e\n \u003cli\u003eZhao H, Hong L, Chen J, Zhou Y, Min J, Xu F, et al. Epidemiological characteristics of hand, foot and mouth disease in children from 2011 to 2016 in Nanjing and its association with temperature. J Chin School Health. 2021;42(623\u0026ndash;6):30. doi: 10.16835/j.cnki.1000-9817.2021.04.033.\u003c/li\u003e\n \u003cli\u003eLiu L, Liu Z, Zhang L, Li N, Fang T, Zhang D, et al. Epidemiological and etiological characteristics of hand, foot and mouth disease among children aged 5 years and younger in Ningbo (2016 to 2019). Peking Univ Heal Sci. 221;53:491-7. 10.19723/j.issn.1671-167X.2021.03.009.\u003c/li\u003e\n \u003cli\u003eHuang L, Wang T, Liu X, Fu Y, Zhang S, Chu Q, Nie T, Tu H, Cheng J, Fan Y. Spatial-temporal-demographic and virological changes of hand, foot and mouth disease incidence after vaccination in a vulnerable region of China. BMC Public Health. 2022 Aug 1;22(1):1468. doi: 10.1186/s12889-022-13860-z.\u003c/li\u003e\n \u003cli\u003eWang J , Zheng J S , Zhang Y H .The comparisons of procalcitonin and age between mild and severe Hand, foot, and mouth disease[J].Translational Pediatrics, 2023, 12(4):7.DOI:10.21037/tp-23-146.\u003c/li\u003e\n \u003cli\u003eThammasonthijarern N, Kosoltanapiwat N, Nuprasert W, Sittikul P, Sriburin P, Pan-Ngum W, Maneekan P, Hataiyusuk S, Hattasingh W, Thaipadungpanit J, Chatchen S. Molecular Epidemiological Study of Hand, Foot, and Mouth Disease in a Kindergarten-Based Setting in Bangkok, Thailand. 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Spatiotemporal characteristics of hand, foot, and mouth disease and influencing factors in China from 2011 to 2018. Chinese Journal of Epidemiology, 43(10), 1562-1567.\u003c/li\u003e\n \u003cli\u003eChen L, Xing Y, Zhang Y, Xie J, Su B, Jiang J, Geng M, Ren X, Guo T, Yuan W, Ma Q, Chen M, Cui M, Liu J, Song Y, Wang L, Dong Y, Ma J. Long-term variations of urban-Rural disparities in infectious disease burden of over 8.44 million children, adolescents, and youth in China from 2013 to 2021: An observational study. PLoS Med. 2024 Apr 12;21(4):e1004374. doi: 10.1371/journal.pmed.1004374.\u003c/li\u003e\n \u003cli\u003eWang J, Zhang S. Epidemiological characteristics and trends of hand-foot-mouth disease in Shanghai, China from 2011 to 2021. Front Public Health. 2023 May 30;11:1162209. doi: 10.3389/fpubh.2023.1162209. PMID: 37325298; PMCID: PMC10267978.\u003c/li\u003e\n \u003cli\u003eZhou X, Qian K, Zhu C, Yi L, Tu J, Yang S, Zhang Y, Zhang Y, Xia W, Ni X, Xu T, He F, Li H. Surveillance, epidemiology, and impact of the coronavirus disease 2019 interventions on the incidence of enterovirus infections in Nanchang, China, 2010-2022. Front Microbiol. 2023 Oct 18;14:1251683. doi: 10.3389/fmicb.2023.1251683. PMID: 37920267; PMCID: PMC10618362.\u003c/li\u003e\n \u003cli\u003eYuan Y, Chen Y, Huang J, Bao X, Shen W, Sun Y, Mao H. Epidemiological and etiological investigations of hand, foot, and mouth disease in Jiashan, northeastern Zhejiang Province, China, during 2016 to 2022. Front Public Health. 2024 May 1;12:1377861. doi: 10.3389/fpubh.2024.1377861.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hand, foot, and mouth disease clusters, Epidemiology, Pathogenesis","lastPublishedDoi":"10.21203/rs.3.rs-6327143/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6327143/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHand, foot, and mouth disease (HFMD) is a common enteric infectious disease that poses a threat to children's health. The disease exhibits high epidemic intensity and frequent clusters in Beijing, the capital of China. The present study analyzed data on HFMD clusters in Beijing from 2019 to 2024, reported by the district-level Centers for Disease Control and Prevention and compiled by the Beijing Center for Disease Control and Prevention. This study comprehensively examined the epidemiological characteristics of HFMD clusters, including demographic information, regional distribution, and pathogen associations. The Seasonal Autoregressive Integrated Moving Average (i.e., \u0026ldquo;SARIMA\u0026rdquo;) model was used to predict cluster incidence by 2025. From 2019 to 2024, 4265 HFMD clusters were reported in Beijing, exhibiting a pattern of high incidence every other year and two peaks annually, with significant seasonal epidemic characteristics. The primary locations of the clusters were kindergartens, schools, and households. Analysis of regional distribution revealed that the near suburbs had a higher incidence than the central and outer suburbs. It is recommended that key locations, such as kindergartens and schools in the near suburbs and urban-rural junctions, further implement HFMD prevention and control measures, strengthen surveillance, closely monitor changes in viral strains, and prepare in advance for HFMD cluster prevention and control.\u003c/p\u003e","manuscriptTitle":"Epidemiological characteristics of hand, foot, and mouth disease clusters in Beijing, China, 2019–2024","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 01:35:05","doi":"10.21203/rs.3.rs-6327143/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cd0df9fb-dd0f-42f0-96f8-972921ba9dd3","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-02T05:08:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 01:35:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6327143","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6327143","identity":"rs-6327143","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}