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Zhang Y, Zhang J, Zhang X, Jin H. How urbanization shapes the effectiveness of school closures on hand, foot, and mouth disease. Int J Infect Dis 2025; 154:107845. [PMID: 39978752 DOI: 10.1016/j.ijid.2025.107845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2025] [Revised: 02/12/2025] [Accepted: 02/12/2025] [Indexed: 02/22/2025] Open
Abstract
OBJECTIVE This study analyzed the influence of urbanization on the effectiveness of school closures in controlling hand, foot, and mouth disease (HFMD). METHODS Data were collected from 31 provinces in mainland China between 2010 and 2019. The effect of school closures on HFMD was estimated and synthesized for high and low urbanization groups. Discrepancies in effectiveness were hypothesized to be explained by transmission potential, which was estimated with its influencing factors identified. Considering time lags or seasons, system dynamics models were constructed to verify this hypothesis. RESULTS The relative risk of school closures on HFMD epidemics was 0.68, with a negative correlation between urbanization and the effectiveness of school closures. Urbanization and human mobility significantly increased the transmission potential of HFMD. Controlling for the positive effects of specific humidity, school closures reduced the effective reproductive number of HFMD by 10.52% and 17.07% in the high and low urbanization groups, respectively (P < 0.0001). Timely response or school closures in autumn led to a notable decline in the number of HFMD cases. CONCLUSIONS Increased urbanization reduced the effectiveness of school closures in controlling HFMD by greater transmission potential, highlighting the need for additional public health interventions.
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Affiliation(s)
- Yazhen Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, Jiangsu, China
| | - Juan Zhang
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, China
| | - Xuefeng Zhang
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Hui Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, Jiangsu, China; Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, China.
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Liu Y, Song Y, Liu F, Chen Y, Liu Y, Shi J, Li K, Yin Y, Liang Q, Liu N, Ming M, Hua L, Shi Q, Xu J, Yuan R, Li S, Zhang L, Zhao Y, Wang N, Zhang J, Zhang Y, Chang Z, Zhang Z. Effectiveness of the enterovirus A71 vaccine on hand, foot, and mouth disease: a real-world study in China. Clin Microbiol Infect 2025; 31:258-265. [PMID: 39343096 DOI: 10.1016/j.cmi.2024.09.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 09/08/2024] [Accepted: 09/23/2024] [Indexed: 10/01/2024]
Abstract
OBJECTIVES For the prevention of hand, foot, and mouth disease (HFMD), enterovirus A71 (EV-A71) vaccines have been used in China since 2016. To better inform vaccination strategies, we assess the real-world effectiveness of EV-A71 vaccination in China. METHODS The analysis was based on surveillance data of HFMD caused by EV-A71 in children under the age of 5 in China, along with meteorological and demographic data. The seasonal autoregressive integrated moving average model and the interrupted time series analysis were used to estimate the effectiveness of the EV-A71 vaccination on the EV-A71 HFMD incidence and to predict the counterfactual cases with no EV-A71 vaccine. RESULTS Between 2010 and 2018, 6 712 613 cases of HFMD caused by EV-A71 were reported in children under 5 years old in 260 Chinese cities. During 2017-2018, the EV-A71 vaccination was associated with a reduction in EV-A71 HFMD incidence, with a relative risk of 0.83 (95% CI, 0.81-0.86), and an estimated reduction of 297 946 (95% CI, 250 534-346 658) cases. However, this association varied across cities (I2 = 85.6%, p < 0.001) and the effectiveness of the EV-A71 vaccination decreased as population density increased. Higher vaccination coverage was associated with greater effectiveness of the EV-A71 vaccination and an earlier point in EV-A71 case reduction. Specifically, when the vaccination coverage exceeded ∼20%, the relative risk was rapidly reduced to below 0.71 (95% CI, 0.69-0.72). DISCUSSION Our study demonstrated that the EV-A71 vaccination was associated with a reduction in the incidence of EV-A71 HFMD, but the association varied with regions and was influenced by vaccination coverage and population density. To optimize EV-A71 HFMD prevention, increasing vaccination coverage (>20%) is recommended for children under 5 years old.
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Affiliation(s)
- Yuanhua Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yang Song
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Fengfeng Liu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Yang Liu
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jin Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Ke Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yun Yin
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Qingqing Liang
- Health Information Center, Guilin Center for Disease Control and Prevention, Guilin, China
| | - Na Liu
- Department of Immunization Program, Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Ming Ming
- Department of Immunization Program, Taian Center for Disease Control and Prevention, Taian, China
| | - Lei Hua
- Department of Immunization Program, Baoji Center for Disease Control and Prevention, Baoji, China
| | - Qian Shi
- Department of Immunization Program, Chaoyang District Center for Disease Control and Prevention, Beijing, China
| | - Jiayao Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Rui Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Shuting Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lele Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yu Zhao
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Na Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jidan Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yanping Zhang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaorui Chang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhijie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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3
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Gam PH, Dung NM, Aziz JMA, Makram AM, Elsheikh R, Huy NT. Vaccine for hand, foot, and mouth disease (HFMD): A call to action. Vaccine 2025; 44:126491. [PMID: 39467726 DOI: 10.1016/j.vaccine.2024.126491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2024] [Revised: 10/23/2024] [Accepted: 10/24/2024] [Indexed: 10/30/2024]
Affiliation(s)
- Pham Hong Gam
- Faculty of Pharmacy, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Viet Nam; Online Research Club, Nagasaki, Japan
| | - Nguyen Minh Dung
- Online Research Club, Nagasaki, Japan; Trauma and Orthopaedics Department, Orthopaedics and Rehabilitation Hospital, Ho Chi Minh City, Viet Nam
| | - Jeza Muhamad Abdul Aziz
- Biomedical Science Department, Komar University of Science and Technology, Sulaimaniyah, Kurdistan Region, Iraq; Baxshin Research Center, Baxshin Hospital, Sulaimaniyah, Kurdistan Region, Iraq
| | | | - Randa Elsheikh
- Deanery of Biomedical Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom..
| | - Nguyen Tien Huy
- Institute of Research and Development, Duy Tan University, Da Nang, Viet Nam; School of Medicine and Pharmacy, Duy Tan University, Da Nang, Viet Nam; Graduate School of Tropical Medicine and Global Health (TMGH), Nagasaki University, Nagasaki, Japan.
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4
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Madden WG, Jin W, Lopman B, Zufle A, Dalziel B, E. Metcalf CJ, Grenfell BT, Lau MSY. Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models. PLoS Comput Biol 2024; 20:e1012616. [PMID: 39570994 PMCID: PMC11620694 DOI: 10.1371/journal.pcbi.1012616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 12/05/2024] [Accepted: 11/04/2024] [Indexed: 12/07/2024] Open
Abstract
Measles is an important infectious disease system both for its burden on public health and as an opportunity for studying nonlinear spatio-temporal disease dynamics. Traditional mechanistic models often struggle to fully capture the complex nonlinear spatio-temporal dynamics inherent in measles outbreaks. In this paper, we first develop a high-dimensional feed-forward neural network model with spatial features (SFNN) to forecast endemic measles outbreaks and systematically compare its predictive power with that of a classical mechanistic model (TSIR). We illustrate the utility of our model using England and Wales measles data from 1944-1965. These data present multiple modeling challenges due to the interplay between metapopulations, seasonal trends, and nonlinear dynamics related to demographic changes. Our results show that while the TSIR model yields similarly performant short-term (1 to 2 biweeks ahead) forecasts for highly populous cities, our neural network model (SFNN) consistently achieves lower root mean squared error (RMSE) across other forecasting windows. Furthermore, we show that our spatial-feature neural network model, without imposing mechanistic assumptions a priori, can uncover gravity-model-like spatial hierarchy of measles spread in which major cities play an important role in driving regional outbreaks. We then turn our attention to integrative approaches that combine mechanistic and machine learning models. Specifically, we investigate how the TSIR can be utilized to improve a state-of-the-art approach known as Physics-Informed-Neural-Networks (PINN) which explicitly combines compartmental models and neural networks. Our results show that the TSIR can facilitate the reconstruction of latent susceptible dynamics, thereby enhancing both forecasts in terms of mean absolute error (MAE) and parameter inference of measles dynamics within the PINN. In summary, our results show that appropriately designed neural network-based models can outperform traditional mechanistic models for short to long-term forecasts, while simultaneously providing mechanistic interpretability. Our work also provides valuable insights into more effectively integrating machine learning models with mechanistic models to enhance public health responses to measles and similar infectious disease systems.
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Affiliation(s)
- Wyatt G. Madden
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Wei Jin
- Department of Computer Science, College of Arts and Sciences, Emory University, Atlanta, Georgia, United States of America
| | - Benjamin Lopman
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Andreas Zufle
- Department of Computer Science, College of Arts and Sciences, Emory University, Atlanta, Georgia, United States of America
| | - Benjamin Dalziel
- Department of Integrative Biology, Oregon State University, Oregon, United States of America
| | - C. Jessica E. Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Bryan T. Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Max S. Y. Lau
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
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5
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Zhu R, Wu Y, Huang Y, Jiang Y, Jiang Y, Zhang D, Sun H, Zhou Z, Zhou L, Weng S, Chen H, Chen X, Ning W, Zou Y, He M, Yang H, Deng W, Li Y, Chen Z, Ye X, Han J, Yin Z, Zhao H, Liu C, Que Y, Fang M, Yu H, Zhang J, Luo W, Li S, Zheng Q, Xu L, Xia N, Cheng T. Broadly therapeutic antibody provides cross-serotype protection against enteroviruses via Fc effector functions and by mimicking SCARB2. Nat Microbiol 2024; 9:2939-2953. [PMID: 39424982 DOI: 10.1038/s41564-024-01822-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 09/03/2024] [Indexed: 10/21/2024]
Abstract
Enteroviruses contain multiple serotypes and can cause severe neurological complications. The intricate life cycle of enteroviruses involving dynamic virus-receptor interaction hampers the development of broad therapeutics and vaccines. Here, using function-based screening, we identify a broadly therapeutic antibody h1A6.2 that potently protects mice in lethal models of infection with both enterovirus A71 and coxsackievirus A16 through multiple mechanisms, including inhibition of the virion-SCARB2 interactions and monocyte/macrophage-dependent Fc effector functions. h1A6.2 mitigates inflammation and improves intramuscular mechanics, which are associated with diminished innate immune signalling and preserved tissue repair. Moreover, cryogenic electron microscopy structures delineate an adaptive binding of h1A6.2 to the flexible and dynamic nature of the VP2 EF loop with a binding angle mimicking the SCARB2 receptor. The coordinated binding mode results in efficient binding of h1A6.2 to all viral particle types and facilitates broad neutralization of enterovirus, therefore informing a promising target for the structure-guided design of pan-enterovirus vaccine.
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Affiliation(s)
- Rui Zhu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yuanyuan Wu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yang Huang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yanan Jiang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yichao Jiang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Dongqing Zhang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Hui Sun
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Zhenhong Zhou
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Lizhi Zhou
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Shihan Weng
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Hao Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Xiaoqing Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Wenjing Ning
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yuxiang Zou
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Maozhou He
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Hongwei Yang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Weixi Deng
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yu Li
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Zhenqin Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Xiangzhong Ye
- Beijing Wantai Biological Pharmacy Enterprise Co., Ltd, Beijing, PR China
| | - Jinle Han
- Beijing Wantai Biological Pharmacy Enterprise Co., Ltd, Beijing, PR China
| | - Zhichao Yin
- Beijing Wantai Biological Pharmacy Enterprise Co., Ltd, Beijing, PR China
| | - Huan Zhao
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Che Liu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Yuqiong Que
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Mujin Fang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Hai Yu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Jun Zhang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China
| | - Wenxin Luo
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China.
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China.
| | - Shaowei Li
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China.
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China.
| | - Qingbing Zheng
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China.
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China.
| | - Longfa Xu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China.
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China.
| | - Ningshao Xia
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China.
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China.
- Research Unit of Frontier Technology of Structural Vaccinology, Chinese Academy of Medical Sciences, Xiamen, Fujian, PR China.
| | - Tong Cheng
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Life Sciences, School of Public Health, Xiamen University, Xiamen, PR China.
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, PR China.
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6
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Zheng D, Shen L, Wen W, Zhuang Z, Qian SE, Ling F, Miao Z, Li R, McMillin SE, Bass S, Sun J, Lin H, Liu K. Effect of EV71 Vaccination on Transmission Dynamics of Hand, Foot, and Mouth Disease and Its Epidemic Prevention Threshold. Vaccines (Basel) 2024; 12:1166. [PMID: 39460332 PMCID: PMC11511198 DOI: 10.3390/vaccines12101166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2024] [Revised: 10/09/2024] [Accepted: 10/11/2024] [Indexed: 10/28/2024] Open
Abstract
OBJECTIVE To investigate the effect of Enterovirus A71 (EV71) vaccination on the transmissibility of different enterovirus serotypes of hand, foot, and mouth disease (HFMD) in Zhejiang, China. METHODS Daily surveillance data of HFMD and EV71 vaccination from August 2016 to December 2019 were collected. Epidemic periods for each HFMD type were defined, and the time-varying effective reproduction number (Rt) was estimated, which could provide more direct evidence of disease epidemics than case number. General additive models (GAMs) were employed to analyze associations between EV71 vaccination quantity and rate and HFMD transmissibility. The epidemic prevention threshold, represented by required vaccination numbers and rates, was also estimated. RESULTS Vaccinating every 100,000 children ≤ 5 years could lead to a decrease in the Rt of EV71-associated HFMD by 14.44% (95%CI: 6.76%, 21.42%). Additionally, a positive correlation was observed between vaccinations among children ≤ 5 years old (per 100,000) and the increased transmissibility of other HFMD types (caused by enteroviruses other than EV71 and CA16) at 1.82% (95%CI: 0.80%, 2.84%). It was estimated that an additional 362,381 vaccinations, corresponding to increased vaccine coverage to 54.51% among children ≤ 5 years could effectively prevent EV71 epidemics in Zhejiang. CONCLUSIONS Our findings highlight the importance of enhancing EV71 vaccine coverage for controlling the epidemic of EV71-HFMD and assisting government officials in developing strategies to prevent HFMD.
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Affiliation(s)
- Dashan Zheng
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Lingzhi Shen
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Wanqi Wen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Zitong Zhuang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Samantha E. Qian
- College of Arts and Sciences, Saint Louis University, Saint Louis, MO 63108, USA
| | - Feng Ling
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Ziping Miao
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Rui Li
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, 169 Changle West Road, Xi’an 710032, China
| | | | - Sabel Bass
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO 63104, USA
| | - Jimin Sun
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (D.Z.); (H.L.)
| | - Kun Liu
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, 169 Changle West Road, Xi’an 710032, China
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Park SW, Cobey S, Metcalf CJE, Levine JM, Grenfell BT. Predicting pathogen mutual invasibility and co-circulation. Science 2024; 386:175-179. [PMID: 39388572 DOI: 10.1126/science.adq0072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 09/05/2024] [Indexed: 10/12/2024]
Abstract
Observations of pathogen community structure provide evidence for both the coexistence and replacement of related strains. Despite many studies of specific host-pathogen systems, a unifying framework for predicting the outcomes of interactions among pathogens has remained elusive. We address this gap by developing a pathogen invasion theory (PIT) based on modern ecological coexistence theory and testing the resulting framework against empirical systems. Across major human pathogens, PIT predicts near-universal mutual susceptibility of one strain to invasion by another strain. However, predicting co-circulation from mutual invasion also depends on the degree to which susceptible abundance is reduced below the invasion threshold by overcompensatory epidemic dynamics, and the time it takes for susceptibles to replenish. The transmission advantage of an invading strain and the strength and duration of immunity are key determinants of susceptible dynamics. PIT unifies existing ideas about pathogen co-circulation, offering a quantitative framework for predicting the emergence of novel pathogen strains.
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Affiliation(s)
- Sang Woo Park
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA
| | - Jonathan M Levine
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA
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8
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Kalam N, Balasubramaniam V. Changing Epidemiology of Hand, Foot, and Mouth Disease Causative Agents and Contributing Factors. Am J Trop Med Hyg 2024; 111:740-755. [PMID: 39106854 PMCID: PMC11448535 DOI: 10.4269/ajtmh.23-0852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 05/18/2024] [Indexed: 08/09/2024] Open
Abstract
Hand, foot, and mouth disease (HFMD) is a common viral infection primarily affecting children. It causes vesicles on the skin and inside the mouth. Although most cases get better on their own, severe cases can lead to complications such as brain stem encephalitis, meningoencephalitis, acute flaccid paralysis, and pulmonary edema. Hand, foot, and mouth disease is caused by various enteroviruses, with enterovirus A71 (EV-A71) and coxsackievirus A16 being the most common. However, recent studies have shown a shift in the molecular epidemiology of HFMD-causing pathogens, with coxsackievirus A6 and coxsackievirus A10 causing more infections. In addition, extensive recombination events have been identified among enterovirus strains, which may have a role in faster evolution and extinction of dominant enterovirus serotypes. Other strains of enterovirus can also cause severe complications, and there has been an increase in mortality associated with brain stem encephalitis in children under 3 years of age and teenagers. Currently, there are no effective antiviral therapies available to treat enterovirus infections. Vaccines against EV-A71 have been approved and are now used in mainland China. Studying the changing epidemiology of HFMD pathogens and the evolution patterns of its causative agents is crucial in developing effective prevention and control strategies. Increased interest in the molecular epidemiology of HFMD causative agents has led to a better understanding of the critical drivers of HFMD outbreaks, which can inform efforts to prevent and control the disease.
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Affiliation(s)
- Nida Kalam
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Malaysia
| | - Vinod Balasubramaniam
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Malaysia
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9
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Baker RE, Yang W, Vecchi GA, Takahashi S. Increasing intensity of enterovirus outbreaks projected with climate change. Nat Commun 2024; 15:6466. [PMID: 39085256 PMCID: PMC11291881 DOI: 10.1038/s41467-024-50936-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 07/25/2024] [Indexed: 08/02/2024] Open
Abstract
Pathogens of the enterovirus genus, including poliovirus and coxsackieviruses, typically circulate in the summer months suggesting a possible positive association between warmer weather and transmission. Here we evaluate the environmental and demographic drivers of enterovirus transmission, as well as the implications of climate change for future enterovirus circulation. We leverage pre-vaccination era data on polio in the US as well as data on two enterovirus A serotypes in China and Japan that are known to cause hand, foot, and mouth disease. Using mechanistic modeling and statistical approaches, we find that enterovirus transmission appears positively correlated with temperature although demographic factors, particularly the timing of school semesters, remain important. We use temperature projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate future outbreaks under late 21st-century climate change for Chinese provinces. We find that outbreak size increases with climate change on average, though results differ across climate models depending on the degree of wintertime warming. In the worst-case scenario, we project peak outbreaks in some locations could increase by up to 40%.
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Affiliation(s)
- Rachel E Baker
- Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA.
- Institute at Brown for Environment and Society, Brown University, Providence, RI, USA.
| | - Wenchang Yang
- Department of Geosciences, Princeton University, Princeton, NJ, USA
| | - Gabriel A Vecchi
- Department of Geosciences, Princeton University, Princeton, NJ, USA
- High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA
| | - Saki Takahashi
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Sun J, Zhang W, Yao G, Gu J, Wu W, Wang D, Du Z, Hao Y. Assessing the modification impact of vaccination on the relationship of the Discomfort Index with hand, foot, and mouth disease in Guizhou: A multicounty study. PLoS Negl Trop Dis 2024; 18:e0012008. [PMID: 38949988 PMCID: PMC11216560 DOI: 10.1371/journal.pntd.0012008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 06/02/2024] [Indexed: 07/03/2024] Open
Abstract
BACKGROUND Hand, foot, and mouth disease (HFMD) is a major public health issue in China while temperature and humidity are well-documented predictors. However, evidence on the combined effect of temperature and humidity is still limited. It also remains unclear whether such an effect could be modified by the enterovirus 71 (EV71) vaccination. METHODS Based on 320,042 reported HFMD cases during the summer months between 2012 and 2019, we conducted a study utilizing Distributed Lag Non-Linear Models (DLNM) and time-varying DLNM to examine how China's HFMD EV71 vaccine strategy would affect the correlation between meteorological conditions and HFMD risk. RESULTS The incidence of HFMD changed with the Discomfort Index in an arm-shaped form. The 14-day cumulative risk of HFMD exhibited a statistically significant increase during the period of 2017-2019 (following the implementation of the EV71 vaccine policy) compared to 2012-2016 (prior to the vaccine implementation). For the total population, the range of relative risk (RR) values for HFMD at the 75th, 90th, and 99th percentiles increased from 1.082-1.303 in 2012-2016 to 1.836-2.022 in 2017-2019. In the stratified analyses, Han Chinese areas show stronger relative growth, with RR values at the 75th, 90th, and 99th percentiles increased by 14.3%, 39.1%, and 134.4% post-vaccination, compared to increases of 22.7%, 41.6%, and 38.8% in minority areas. Similarly, boys showed greater increases (24.4%, 47.7%, 121.5%) compared to girls (8.1%, 28.1%, 58.3%). Additionally, the central Guizhou urban agglomeration displayed a tendency for stronger relative growth compared to other counties. CONCLUSIONS Although the EV71 vaccine policy has been implemented, it hasn't effectively controlled the overall risk of HFMD. There's been a shift in the main viral subtypes, potentially altering population susceptibility and influencing HFMD occurrences. The modulating effects of vaccine intervention may also be influenced by factors such as race, sex, and economic level.
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Affiliation(s)
- Jie Sun
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
- Institute for the Control of Infectious Diseases, Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Guanghai Yao
- Institute for the Control of Infectious Diseases, Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, China
| | - Jing Gu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Dan Wang
- Institute for the Control of Infectious Diseases, Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
- Guangzhou Joint Research Center for Disease Surveillance and Risk Assessment, Sun Yat-sen University & Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Peking University, Beijing, China
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11
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Moss DL, Paine AC, Krug PW, Kanekiyo M, Ruckwardt TJ. Enterovirus virus-like-particle and inactivated poliovirus vaccines do not elicit substantive cross-reactive antibody responses. PLoS Pathog 2024; 20:e1012159. [PMID: 38662650 PMCID: PMC11045126 DOI: 10.1371/journal.ppat.1012159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024] Open
Abstract
Human enteroviruses are the most common human pathogen with over 300 distinct genotypes. Previous work with poliovirus has suggested that it is possible to generate antibody responses in humans and animals that can recognize members of multiple enterovirus species. However, cross protective immunity across multiple enteroviruses is not observed epidemiologically in humans. Here we investigated whether immunization of mice or baboons with inactivated poliovirus or enterovirus virus-like-particles (VLPs) vaccines generates antibody responses that can recognize enterovirus D68 or A71. We found that mice only generated antibodies specific for the antigen they were immunized with, and repeated immunization failed to generate cross-reactive antibody responses as measured by both ELISA and neutralization assay. Immunization of baboons with IPV failed to generate neutralizing antibody responses against enterovirus D68 or A71. These results suggest that a multivalent approach to enterovirus vaccination is necessary to protect against enterovirus disease in vulnerable populations.
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Affiliation(s)
- Daniel L. Moss
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Alden C. Paine
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Peter W. Krug
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Masaru Kanekiyo
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Tracy J. Ruckwardt
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
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12
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Luo C, Ma Y, Lu K, Li Y, Liu Y, Zhang T, Yin F, Shui T. How multiple air pollutants affect hand, foot, and mouth disease incidence in children: assessing effect modification by geographical context in multicity of Sichuan, southwest China. BMC Public Health 2024; 24:263. [PMID: 38263020 PMCID: PMC10804470 DOI: 10.1186/s12889-023-17484-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 12/14/2023] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Several studies have suggested a significant association of hand, foot, and mouth disease (HFMD) with ambient air pollutants. Existing studies have characterized the role of air pollutants on HFMD using only risk ratio measures while ignoring the attributable burden. And whether the geographical context (i.e., diverse topographic features) could modulate the relationships is unclear. METHODS Daily reported childhood HFMD counts, ambient air pollution, and meteorological data during 2015-2017 were collected for each of 21 cities in Sichuan Province. A multistage analysis was carried out in different populations based on geographical context to assess effect modification by topographic conditions. We first constructed a distributed lag nonlinear model (DLNM) for each city to describe the relationships with risk ratio measures. Then, we applied a multivariate meta-regression to estimate the pooled effects of multiple air pollutants on HFMD from the exposure and lagged dimensions. Finally, attributable risks measures were calculated to quantify HFMD burden by air pollution. RESULTS Based on 207554 HFMD cases in Sichuan Province, significant associations of HFMD with ambient air pollutants were observed mainly at relatively high exposure ranges. The effects of ambient air pollutants on HFMD are most pronounced on lag0 or around lag7, with relative risks gradually approaching the reference line thereafter. The attributable risks of O3 were much greater than those of other air pollutants, particularly in basin and mountain regions. CONCLUSIONS This study revealed significant pooled relationships between multiple air pollutants and HFMD incidence from both exposure and lag dimensions. However, the specific effects, including RRs and ARs, differ depending on the air pollution variable and geographical context. These findings provide local authorities with more evidence to determine key air pollutants and regions for devising and implementing targeted interventions.
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Affiliation(s)
- Caiying Luo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Kai Lu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ying Li
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Yaqiong Liu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, China.
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13
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Zheng D, Shen L, Wen W, Ling F, Miao Z, Sun J, Lin H. The impact of EV71 vaccination program on hand, foot and mouth disease in Zhejiang Province, China: A negative control study. Infect Dis Model 2023; 8:1088-1096. [PMID: 37745754 PMCID: PMC10514095 DOI: 10.1016/j.idm.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 08/30/2023] [Accepted: 09/03/2023] [Indexed: 09/26/2023] Open
Abstract
Objective To estimate the potential causal impact of Enterovirus A71 (EV71) vaccination program on the reduction of EV71-infected hand, foot, and mouth disease (HFMD) in Zhejiang Province. Methods We utilized the longitudinal surveillance dataset of HFMD and EV71 vaccination in Zhejiang Province during 2010-2019. We estimated vaccine efficacy using a Bayesian structured time series (BSTS) model, and employed a negative control outcome (NCO) model to detect unmeasured confounding and reveal potential causal association. Results We estimated that 20,132 EV71 cases (95% CI: 16,733, 23,532) were prevented by vaccination program during 2017-2019, corresponding to a reduction of 29% (95% CI: 24%, 34%). The effectiveness of vaccination increased annually, with reductions of 11% (95% CI: 6%, 16%) in 2017 and 66% (95% CI: 61%, 71%) in 2019. Children under 5 years old obtained greater benefits compared to those over 5 years. Cities with higher vaccination coverage experienced a sharper EV71 reduction compared to those with lower coverage. The NCO model detected no confounding factors in the association between vaccination and EV71 cases reduction. Conclusions This study suggested a potential causal effect of the EV71 vaccination, highlighting the importance of achieving higher vaccine coverage to control the HFMD.
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Affiliation(s)
- Dashan Zheng
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Lingzhi Shen
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, 310051, China
| | - Wanqi Wen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Feng Ling
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, 310051, China
| | - Ziping Miao
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, 310051, China
| | - Jimin Sun
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, 310051, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
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Li K, Wang J, Xie J, Rui J, Abudunaibi B, Wei H, Liu H, Zhang S, Li Q, Niu Y, Chen T. Advancements in Defining and Estimating the Reproduction Number in Infectious Disease Epidemiology. China CDC Wkly 2023; 5:829-834. [PMID: 37814634 PMCID: PMC10560332 DOI: 10.46234/ccdcw2023.158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/11/2023] [Indexed: 10/11/2023] Open
Affiliation(s)
- Kangguo Li
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Jiayi Wang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Jiayuan Xie
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Jia Rui
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Buasiyamu Abudunaibi
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Hongjie Wei
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Hong Liu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Shuo Zhang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
| | - Qun Li
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yan Niu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tianmu Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China
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15
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Wang L, Xu C, Wang J, Qiao J, Wu N, Li L. Spatiotemporal associations between hand, foot and mouth disease and meteorological factors over multiple climate zones. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2023; 67:1493-1504. [PMID: 37458818 DOI: 10.1007/s00484-023-02519-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 05/25/2023] [Accepted: 07/05/2023] [Indexed: 08/17/2023]
Abstract
Prior studies of hand, foot, and mouth disease (HFMD) have often observed inconsistent results regarding meteorological factors. We propose the hypothesis that these meteorological associations vary in regions because of the heterogeneity of their geographical characteristics. We have tested this hypothesis by applying a geographical detector and Bayesian space-time hierarchy model to measure stratified spatiotemporal heterogeneity and local associations between meteorological factors and HFMD risk in five climate zones in China from January 2016 to December 2017. We found a significant spatial stratified heterogeneity in HFMD risk and climate zone explained 15% of the spatial stratified heterogeneity. Meanwhile, there was a significant temporal stratified heterogeneity of 14% as determined by meteorological factors. Average temperatures and relative humidity had a significant positive effect on HFMD in all climate zones, they were the most obvious in the southern temperate zone. In northern temperate, southern temperate, northern subtropics, middle subtropics and southern subtropics climate zone, a 1 °C rise in temperature was related to an increase of 3.99%, 13.76%, 4.38%, 3.99%, and 7.74% in HFMD, and a 1% increment in relative humidity was associated with a 1.51%, 5.40%, 2.21%, 3.44%, and 4.78% increase, respectively. These findings provide strong support for our hypotheses that HFMD incidence has a significant spatiotemporal stratified heterogeneity and different climate zones have distinct influences on the disease. These findings provide strong support for our hypotheses: HFMD incidence had significant spatiotemporal stratified heterogeneity and different climate zones had distinct influences on it. The study suggested that HFMD prevention and policy should be made according to meteorological variation in each climate zone.
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Affiliation(s)
- Li Wang
- College of Geography and Environmental Science, Henan University, Kaifeng, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, China
| | - Chengdong Xu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | - Jiajun Qiao
- College of Geography and Environmental Science, Henan University, Kaifeng, China.
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, China.
| | - Nalin Wu
- College of Geography and Environmental Science, Henan University, Kaifeng, China
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, China
| | - Li Li
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
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16
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Tan C, Li S, Li Y, Peng Z. Dynamic modeling and data fitting of climatic and environmental factors and people's behavior factors on hand, foot, and mouth disease (HFMD) in Shanghai, China. Heliyon 2023; 9:e18212. [PMID: 37576260 PMCID: PMC10412780 DOI: 10.1016/j.heliyon.2023.e18212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 07/08/2023] [Accepted: 07/11/2023] [Indexed: 08/15/2023] Open
Abstract
Background Hand, foot, and mouth disease (HFMD) appear to be a multi-wave outbreak with unknown mechanisms. We investigate the effects of climatic and environmental factors and changes in people's behavior factors that may be caused by external factors: temperature, relative humidity, and school opening and closing. Methods Distributed lag nonlinear model (DLNM) and dynamic model are used to research multi-wave outbreaks of HFMD. Climatic and environmental factors impact on transmission rate β ( t ) is modeled through DLNM and then substituted into this relationship to establish the dynamic model with reported case data to test for validity. Results Relative risk (RR) of HFMD infection increases with increasing temperature. The RR of infection first increases and then decreases with the increase of relative humidity. For the model fitting HFMD dynamic, time average basic reproduction number [ R 0 ] of Stage I (without vaccine) and Stage II (with EV71 vaccine) are 1.9362 and 1.5478, respectively. Temperature has the highest explanatory power, followed by school opening and closing, and relative humidity. Conclusion We obtain three conclusions about the prevention and control of HFMD. 1) According to the temperature, relative humidity and school start time, the outbreak peak of HFMD should be warned and targeted prevention and control measures should be taken. 2) Reduce high indoor temperature when more than 31.5 oC, and increase low relative humidity when less than 77.5% by opening the window for ventilation, adding houseplants, using air conditioners and humidifiers, reducing the incidence of HFMD and the number of infections. 3) The risk of HFMD transmission during winter vacations is higher than during summer vacations. It is necessary to strengthen the publicity of HFMD prevention knowledge before winter vacations and strengthen the disinfection control measures during winter vacations in children's hospitals, school classrooms, and other places where children gather to reduce the frequency of staff turnover during winter vacations.
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Affiliation(s)
- Changlei Tan
- School of Information and Mathematics, Yangtze University, Jingzhou, 434023, Hubei, PR China
- Information Engineering College, Hunan Applied Technology University, Changde, 415100, Hunan, PR China
| | - Shuang Li
- College of Mathematics and Information Science, Henan Normal University, Xinxiang, 453000, Henan, PR China
| | - Yong Li
- School of Information and Mathematics, Yangtze University, Jingzhou, 434023, Hubei, PR China
| | - Zhihang Peng
- School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, PR China
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17
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Kingston NJ, Snowden JS, Martyna A, Shegdar M, Grehan K, Tedcastle A, Pegg E, Fox H, Macadam AJ, Martin J, Hogle JM, Rowlands DJ, Stonehouse NJ. Production of antigenically stable enterovirus A71 virus-like particles in Pichia pastoris as a vaccine candidate. J Gen Virol 2023; 104:001867. [PMID: 37390009 PMCID: PMC10773253 DOI: 10.1099/jgv.0.001867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 06/12/2023] [Indexed: 07/02/2023] Open
Abstract
Enterovirus A71 (EVA71) causes widespread disease in young children with occasional fatal consequences. In common with other picornaviruses, both empty capsids (ECs) and infectious virions are produced during the viral lifecycle. While initially antigenically indistinguishable from virions, ECs readily convert to an expanded conformation at moderate temperatures. In the closely related poliovirus, these conformational changes result in loss of antigenic sites required to elicit protective immune responses. Whether this is true for EVA71 remains to be determined and is the subject of this investigation.We previously reported the selection of a thermally resistant EVA71 genogroup B2 population using successive rounds of heating and passage. The mutations found in the structural protein-coding region of the selected population conferred increased thermal stability to both virions and naturally produced ECs. Here, we introduced these mutations into a recombinant expression system to produce stabilized virus-like particles (VLPs) in Pichia pastoris.The stabilized VLPs retain the native virion-like antigenic conformation as determined by reactivity with a specific antibody. Structural studies suggest multiple potential mechanisms of antigenic stabilization, however, unlike poliovirus, both native and expanded EVA71 particles elicited antibodies able to directly neutralize virus in vitro. Therefore, anti-EVA71 neutralizing antibodies are elicited by sites which are not canonically associated with the native conformation, but whether antigenic sites specific to the native conformation provide additional protective responses in vivo remains unclear. VLPs are likely to provide cheaper and safer alternatives for vaccine production and these data show that VLP vaccines are comparable with inactivated virus vaccines at inducing neutralising antibodies.
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Affiliation(s)
- Natalie J. Kingston
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Joseph S. Snowden
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Agnieszka Martyna
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - Mona Shegdar
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Keith Grehan
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Alison Tedcastle
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - Elaine Pegg
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - Helen Fox
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - Andrew J. Macadam
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - Javier Martin
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - James M. Hogle
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - David J. Rowlands
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Nicola J. Stonehouse
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
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18
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Jiang X, Ma Y, Lv Q, Liu Y, Zhang T, Yin F, Shui T. Influence of social and meteorological factors on hand, foot, and mouth disease in Sichuan Province. BMC Public Health 2023; 23:849. [PMID: 37165358 PMCID: PMC10170695 DOI: 10.1186/s12889-023-15699-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 04/18/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND Hand, foot and mouth disease (HFMD) caused by a variety of enteroviruses remains a major public health problem in China. Previous studies have found that social factors may contribute to the inconsistency of the relationship patterns between meteorological factors and HFMD, but the conclusions are inconsistent. The influence of social factors on the association between meteorology and HFMD is still less well understood. We aimed to analyze whether social factors affected the effect of meteorological factors on HFMD in Sichuan Province. METHOD We collected daily data on HFMD, meteorological factors and social factors in Sichuan Province from 2011 to 2017. First, we used a Bayesian spatiotemporal model combined with a distributed lag nonlinear model to evaluate the exposure-lag-response association between meteorological factors and HFMD. Second, by constructing the interaction of meteorological factors and social factors in the above model, the changes in the relative risk (RR) under different levels of social factors were evaluated. RESULTS The cumulative exposure curves for average temperature, relative humidity, and HFMD were shaped like an inverted "V" and a "U" shape. As the average temperature increased, the RR increased and peaked at 19 °C (RR 1.020 [95% confidence interval CI 1.004-1.050]). The urbanization rate, per capita gross domestic product (GDP), population density, birth rate, number of beds in health care centers and number of kindergartens interacted with relative humidity. With the increase in social factors, the correlation curve between relative humidity and HFMD changed from an "S" shape to a "U" shape. CONCLUSIONS Relative humidity and average temperature increased the risk of HFMD within a certain range, and social factors enhanced the impact of high relative humidity. These results could provide insights into the combined role of environmental factors in HFMD and useful information for regional interventions.
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Affiliation(s)
- Xiaohong Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiang Lv
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Yaqiong Liu
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China.
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Cheng J, Wang Y, Zhou Y, Lu J, Tang X. Highly sensitive and rapid identification of coxsackievirus A16 based on reverse transcription multiple cross displacement amplification combined with nanoparticle-based lateral flow biosensor assay. Front Microbiol 2023; 14:1121930. [PMID: 36970677 PMCID: PMC10030491 DOI: 10.3389/fmicb.2023.1121930] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 02/17/2023] [Indexed: 03/10/2023] Open
Abstract
IntroductionOne of the main pathogens responsible for human hand, foot, and mouth disease (HFMD), coxsackievirus A16, has put young children’s health at danger, especially in countries in the Asia-Pacific region. Early quick identification is essential for the avoidance and control of the disorder since there are no vaccinations or antiviral medications available to prevent and manage CVA16 infection.MethodsHere, we describe the creation of an easy, speedy, and accurate CVA16 infection detection approach using lateral flow biosensors (LFB) and reverse transcriptionmultiple cross displacement amplification (RT-MCDA). A group of 10 primers was developed for the RT-MCDA system in order to amplify the genes in an isothermal amplification device while targeting the highly conserved region of the CVA16 VP1 gene. Then, without requiring any extra tools, RT-MCDA amplification reaction products might well be detected by visual detection reagent (VDR) and LFB.ResultsThe outcomes showed that 64°C within 40 min was the ideal reaction setting for the CVA16-MCDA test. Target sequences with <40 copies might be found using the CVA16-MCDA. There was no cross-reaction among CVA16 strains and other strains. The findings demonstrated that the CVA16-MCDA test could promptly and successfully identify all of the CVA16-positive (46/220) samples identified by the traditional real-time quantitative polymerase chain reaction (qRT-PCR) assays for 220 clinical anal swab samples. The whole process, such as the processing of the sample (15 min), the MCDA reaction (40 min), and the documenting of the results (2 min), could be finished in 1 h.ConclusionThe CVA16-MCDA-LFB assay, which targeted the VP1 gene, was an efficient, simple, and highly specific examination that might be used extensively in rural regions’ basic healthcare institutions and point-of-care settings.
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Affiliation(s)
- Jinzhi Cheng
- School of Basic Medical Sciences, Guizhou Medical University, Guiyang, China
| | - Yu Wang
- Department of Clinical Laboratory, The First People’s Hospital of Guiyang, Guiyang, Guizhou, China
- *Correspondence: Yu Wang, ; Xiaomin Tang,
| | - Yuhong Zhou
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Jingrun Lu
- Department of Clinical Laboratory, The First People’s Hospital of Guiyang, Guiyang, Guizhou, China
| | - Xiaomin Tang
- Laboratory of Bacterial Infectious Disease of Experimental Center, Guizhou Provincial Centre for Disease Control and Prevention, Guiyang, Guizhou, China
- *Correspondence: Yu Wang, ; Xiaomin Tang,
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20
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Kingston NJ, Snowden JS, Martyna A, Shegdar M, Grehan K, Tedcastle A, Pegg E, Fox H, Macadam AJ, Martin J, Hogle JM, Rowlands DJ, Stonehouse NJ. Production of antigenically stable enterovirus A71 virus-like particles in Pichia pastoris as a vaccine candidate. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.30.526315. [PMID: 36778240 PMCID: PMC9915507 DOI: 10.1101/2023.01.30.526315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Enterovirus A71 (EVA71) causes widespread disease in young children with occasional fatal consequences. In common with other picornaviruses, both empty capsids (ECs) and infectious virions are produced during the viral lifecycle. While initially antigenically indistinguishable from virions, ECs readily convert to an expanded conformation at moderate temperatures. In the closely related poliovirus, these conformational changes result in loss of antigenic sites required to elicit protective immune responses. Whether this is true for EVA71 remains to be determined and is the subject of this investigation. We previously reported the selection of a thermally resistant EVA71 genogroup B2 population using successive rounds of heating and passage. The mutations found in the structural protein-coding region of the selected population conferred increased thermal stability to both virions and naturally produced ECs. Here, we introduced these mutations into a recombinant expression system to produce stabilised virus-like particles (VLPs) in Pichia pastoris . The stabilised VLPs retain the native virion-like antigenic conformation as determined by reactivity with a specific antibody. Structural studies suggest multiple potential mechanisms of antigenic stabilisation, however, unlike poliovirus, both native and expanded EVA71 particles elicited antibodies able to directly neutralise virus in vitro . Therefore, the anti-EVA71 neutralising antibodies are elicited by sites which are not canonically associated with the native conformation, but whether antigenic sites specific to the native conformation provide additional protective responses in vivo remains unclear. VLPs are likely to provide cheaper and safer alternatives for vaccine production and these data show that VLP vaccines are comparable with inactivated virus vaccines at inducing neutralising antibodies.
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Affiliation(s)
- Natalie J Kingston
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Joseph S Snowden
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Agnieszka Martyna
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, United Kingdom
| | - Mona Shegdar
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Keith Grehan
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Alison Tedcastle
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, United Kingdom
| | - Elaine Pegg
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, United Kingdom
| | - Helen Fox
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, United Kingdom
| | - Andrew J Macadam
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, United Kingdom
| | - Javier Martin
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, United Kingdom
| | - James M Hogle
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - David J Rowlands
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Nicola J Stonehouse
- Astbury Centre for Structural Molecular Biology, School of Molecular & Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
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21
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Huang J, Ma Y, Lv Q, Liu Y, Zhang T, Yin F, Shui T. Interactive effects of meteorological factors and air pollutants on hand, foot, and mouth disease in Chengdu, China: a time-series study. BMJ Open 2022; 12:e067127. [PMID: 36450433 PMCID: PMC9716848 DOI: 10.1136/bmjopen-2022-067127] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/15/2022] [Indexed: 12/03/2022] Open
Abstract
OBJECTIVES Hand, foot, and mouth disease (HFMD) is a viral infectious disease that poses a substantial threat in the Asia-Pacific region. It is widely reported that meteorological factors are associated with HFMD. However, the relationships between air pollutants and HFMD are still controversial. In addition, the interactive effects between meteorological factors and air pollutants on HFMD remain unknown. To fill this research gap, we conducted a time-series study. DESIGN A time-series study. SETTING AND PARTICIPANTS Daily cases of HFMD as well as meteorological and air pollution data were collected in Chengdu from 2011 to 2017. A total of 184 610 HFMD cases under the age of 15 were included in our study. OUTCOME MEASURES Distributed lag nonlinear models were used to investigate the relationships between HFMD and environmental factors, including mean temperature, relative humidity, SO2, NO2, and PM10. Then, the relative excess risk due to interaction (RERI) and the proportion attributable to interaction were calculated to quantitatively evaluate the interactions between meteorological factors and air pollutants on HFMD. Bivariate response surface models were used to visually display the interactive effects. RESULTS The cumulative exposure-response curves of SO2 and NO2 were inverted 'V'-shaped and 'M'-shaped, respectively, and the risk of HFMD gradually decreased with increasing PM10 concentrations. We found that there were synergistic interactions between mean temperature and SO2, relative humidity and SO2, as well as relative humidity and PM10 on HFMD, with individual RERIs of 0.334 (95% CI 0.119 to 0.548), 0.428 (95% CI 0.214 to 0.642) and 0.501 (95% CI 0.262 to 0.741), respectively, indicating that the effects of SO2 and PM10 on HFMD were stronger under high temperature (>17.3°C) or high humidity (>80.0%) conditions. CONCLUSIONS There were interactive effects between meteorological factors and air pollutants on HFMD. Our findings could provide guidance for targeted and timely preventive and control measures for HFMD.
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Affiliation(s)
- Jiaqi Huang
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Yue Ma
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Qiang Lv
- Department of Acute Infectious Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Yaqiong Liu
- Department of Acute Infectious Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Tao Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Fei Yin
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Tiejun Shui
- Department of Leprosy Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
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22
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Yang J, Liao Q, Luo K, Liu F, Zhou Y, Zou G, Huang W, Yu S, Wei X, Zhou J, Dai B, Qiu Q, Altmeyer R, Hu H, Paireau J, Luo L, Gao L, Nikolay B, Hu S, Xing W, Wu P, van Doorn HR, Horby PW, Simmonds P, Leung GM, Cowling BJ, Cauchemez S, Yu H. Seroepidemiology of enterovirus A71 infection in prospective cohort studies of children in southern China, 2013-2018. Nat Commun 2022; 13:7280. [PMID: 36435844 PMCID: PMC9701185 DOI: 10.1038/s41467-022-34992-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 11/11/2022] [Indexed: 11/28/2022] Open
Abstract
Enterovirus A71 (EV-A71)-related hand, foot, and mouth disease (HFMD) imposes a substantial clinical burden in the Asia Pacific region. To inform policy on the introduction of the EV-A71 vaccine into the National Immunization Programme, we investigated the seroepidemiological characteristics of EV-A71 in two prospective cohorts of children in southern China conducted between 2013 and 2018. Our results show that maternal antibody titres declined rapidly in neonates, with over half becoming susceptible to EV-A71 at 1 month of age. Between 6 months and 2 years of age, over 80% of study participants were susceptible, while one third remained susceptible at 5 years old. The highest incidence of EV-A71 infections was observed in children aged 5-6 months. Our findings support EV-A71 vaccination before 6 months for birth cohorts in southern China, potentially with a one-time catch-up vaccination for children 6 months-5 years old. More regionally representative longitudinal seroepidemiological studies are needed to further validate these findings.
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Affiliation(s)
- Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Qiaohong Liao
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kaiwei Luo
- Hunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha, China
| | - Fengfeng Liu
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yonghong Zhou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Gang Zou
- Institut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai, China
| | - Wei Huang
- Hunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha, China
| | - Shuanbao Yu
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xianglin Wei
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jiaxin Zhou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Bingbing Dai
- Anhua County Center for Disease Control and Prevention, Yiyang, China
| | - Qi Qiu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Ralf Altmeyer
- Institut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai, China
- Medusa Therapeutics Limited, Hong Kong Special Administrative Region, Hong Kong, China
| | - Hongan Hu
- Anhua County Center for Disease Control and Prevention, Yiyang, China
| | - Juliette Paireau
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, UMR2000, CNRS, 75015, Paris, France
- Infectious Diseases Department, Santé publique France, Saint-Maurice, France
| | - Li Luo
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lidong Gao
- Hunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha, China
| | - Birgit Nikolay
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, UMR2000, CNRS, 75015, Paris, France
| | - Shixiong Hu
- Hunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha, China
| | - Weijia Xing
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - H Rogier van Doorn
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Peter W Horby
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Peter Simmonds
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Gabriel M Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, UMR2000, CNRS, 75015, Paris, France
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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23
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Guo J, Cao Z, Liu H, Xu J, Zhao L, Gao L, Zuo Z, Song Y, Han Z, Zhang Y, Wang J. Epidemiology of hand, foot, and mouth disease and the genetic characteristics of Coxsackievirus A16 in Taiyuan, Shanxi, China from 2010 to 2021. Front Cell Infect Microbiol 2022; 12:1040414. [PMID: 36439232 PMCID: PMC9692002 DOI: 10.3389/fcimb.2022.1040414] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022] Open
Abstract
Hand, foot, and mouth disease (HFMD) is a common childhood infectious disease caused by human enteroviruses (EV). This study aimed to describe the epidemiological features of HFMD and the genetic characteristics of Coxsackievirus A16 (CVA16) in Taiyuan, Shanxi, China, from 2010 to 2021. Descriptive epidemiological methods were used to analyze the time and population distribution of HFMD and the genetic characteristics of CVA16. Except being affected by the COVID-19 epidemic in 2020, HFMD epidemics were sporadic from January to March each year, and began to increase in April, with a major epidemic peak from May to August, which declined in September, followed by a secondary peak from October to December. The prevalence of EV infection was the highest in children aged one to five years (84.42%), whereas its incidence was very low in children under one year of age (5.48%). Enterovirus nucleic acid was detected by real-time reverse transcription polymerase chain reaction in 6641 clinical specimens collected from patients with HFMD from 2010 to 2021, and 4236 EV-positive specimens were detected, including 988 enterovirus A71 (EV-A71), 1488 CVA16, and 1760 other enteroviruses. CVA16 remains prevalent and has co-circulated with other EVs in Taiyuan from 2010 to 2021. A phylogenetic tree constructed based on the VP1 region showed that all CVA16 strains belonged to two different clades of the B1 genotype, B1a and B1b. They showed a nucleotide similarity of 86.5-100%, and an amino acid similarity of 96.9-100%. Overall, these findings add to the global genetic resources of CVA16, demonstrate the epidemiological characteristics of HFMD as well as the genetic features of CVA16 in Taiyuan City during 2010-2021, and provide supporting evidence for the prevention and control of HFMD.
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Affiliation(s)
- Jiane Guo
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China,Department of Microbiology Test, Taiyuan Center for Disease Control and Prevention, Taiyuan, Shanxi, China
| | - Zijun Cao
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Hongyan Liu
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jihong Xu
- Department of Microbiology Test, Taiyuan Center for Disease Control and Prevention, Taiyuan, Shanxi, China
| | - Lifeng Zhao
- Department of Microbiology Test, Taiyuan Center for Disease Control and Prevention, Taiyuan, Shanxi, China
| | - Li Gao
- Department of Microbiology Test, Taiyuan Center for Disease Control and Prevention, Taiyuan, Shanxi, China
| | - Zhihong Zuo
- Department of Microbiology Test, Taiyuan Center for Disease Control and Prevention, Taiyuan, Shanxi, China
| | - Yang Song
- World Health Organization (WHO) Western Pacific Region Office (WPRO) Regional Polio Reference Laboratory, National Health Commission Key Laboratory of Biosafety, National Health Commission Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhenzhi Han
- World Health Organization (WHO) Western Pacific Region Office (WPRO) Regional Polio Reference Laboratory, National Health Commission Key Laboratory of Biosafety, National Health Commission Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Zhang
- World Health Organization (WHO) Western Pacific Region Office (WPRO) Regional Polio Reference Laboratory, National Health Commission Key Laboratory of Biosafety, National Health Commission Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China,Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China,*Correspondence: Jitao Wang, ; Yong Zhang,
| | - Jitao Wang
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China,Department of Microbiology Test, Taiyuan Center for Disease Control and Prevention, Taiyuan, Shanxi, China,*Correspondence: Jitao Wang, ; Yong Zhang,
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24
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Zhou J, Zhou Y, Luo K, Liao Q, Zheng W, Gong H, Shi H, Zhao S, Wang K, Qiu Q, Dai B, Ren L, Wang L, Gao L, Xu M, Liu N, Lu W, Zheng N, Chen X, Chen Z, Yang J, Cauchemez S, Yu H. The transfer of maternal antibodies and dynamics of maternal and natural infection-induced antibodies against coxsackievirus A16 in Chinese children 0-13 years of age: a longitudinal cohort study. BMC Med 2022; 20:436. [PMID: 36352415 PMCID: PMC9645321 DOI: 10.1186/s12916-022-02604-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 10/11/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A major hand-foot-and-mouth disease (HFMD) pathogen, coxsackievirus A16 (CVA16), has predominated in several of the last 10 years and caused the largest number of HFMD outbreaks between 2011 and 2018 in China. We evaluated the efficacy of maternal anti-CVA16 antibody transfer via the placenta and explored the dynamics of maternal and natural infection-induced neutralizing antibodies in children. METHODS Two population-based longitudinal cohorts in southern China were studied during 2013-2018. Participants were enrolled in autumn 2013, including 2475 children aged 1-9 years old and 1066 mother-neonate pairs, and followed for 3 years. Blood/cord samples were collected for CVA16-neutralizing antibody detection. The maternal antibody transfer efficacy, age-specific seroprevalence, geometric mean titre (GMT) and immune response kinetics were estimated. RESULTS The average maternal antibody transfer ratio was 0.88 (95% CI 0.80-0.96). Transferred maternal antibody levels declined rapidly (half-life: 2.0 months, 95% CI 1.9-2.2 months). The GMT decayed below the positive threshold (8) by 1.5 months of age. Due to natural infections, it increased above 8 after 1.4 years and reached 32 by 5 years of age, thereafter dropping slightly. Although the average duration of maternal antibody-mediated protection was < 3 months, the duration extended to 6 months on average for mothers with titres ≥ 64. CONCLUSIONS Anti-CVA16 maternal antibodies are efficiently transferred to neonates, but their levels decline quickly. Children aged 0-5 years are the main susceptible population and should be protected by CVA16 vaccination, with the optimal vaccination time between 1.5 months and 1 year of age.
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Affiliation(s)
- Jiaxin Zhou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yonghong Zhou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Kaiwei Luo
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Qiaohong Liao
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Wen Zheng
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Hui Gong
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Huilin Shi
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Shanlu Zhao
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Kai Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Qi Qiu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Bingbing Dai
- Anhua County Center for Disease Control and Prevention, Yiyang, China
| | - Lingshuang Ren
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lili Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lidong Gao
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Meng Xu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Nuolan Liu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Wanying Lu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Nan Zheng
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Xinhua Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Zhiyuan Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université de Paris, UMR2000, CNRS, 75015, Paris, France
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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25
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The spatial-temporal distribution and etiological characteristics of hand-foot-and-mouth disease before and after EV‑A71 vaccination in Kunming, China, 2017-2020. Sci Rep 2022; 12:17028. [PMID: 36220850 PMCID: PMC9552732 DOI: 10.1038/s41598-022-21312-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 09/26/2022] [Indexed: 12/29/2022] Open
Abstract
After vaccination with enterovirus 71 (EV-A71), the prevalence of hand-foot-and-mouth disease (HFMD) remained high, and the spatial-temporal distribution of enteroviruses changed. Therefore, it is essential to define the temporal features, spatial distributions, and epidemiological and etiological characteristics of HFMD in Kunming. Between 2017 and 2020, a total of 36,540 children were diagnosed with HFMD in Kunming, including 32,754 children with enterovirus-positive clinical samples. Demographic, geographical, epidemiological and etiological data of the cases were acquired and analyzed. Other enteroviruses replaced EV-A71, and the incidence of EV-A71 decreased dramatically, whereas coxsackievirus A6 (CV-A6) and coxsackievirus A16 (CV-A16) had substantial outbreaks in 2018 and 2019, respectively. The major and minor peaks all extended for 2-4 months compared to before vaccination with the EV-A71 vaccine. From 2019 to 2020, CV-A6, as the predominant serotype, showed only a single peak. Although a high incidence of HFMD was observed in Guandu, Chenggong and Xishan, the annual incidence of different enterovirus serotypes was different in different regions. In 2017, other enteroviruses were most prevalent in Shilin. In 2018, CV-A16 and CV-A6 were most prevalent in Luquan and Shilin, respectively. In 2019, CV-A16 was most prevalent in Jinning. In 2020, CV-A6 and coxsackievirus A10 (CV-A10) were most prevalent in Luquan and Shilin, respectively. Meanwhile, the epidemic cycle of CV-A6 and CV-A16 was only 1 year, and CV-A10 and other enteroviruses were potential risk pathogens. The spatial and temporal distribution of HFMD varies at different scales, and the incidence of HFMD associated with different pathogens has obvious regional differences and seasonal trends. Therefore, research on multivalent combined vaccines is urgently needed, and proper preventive and protective measures could effectively control the incidence of HFMD-like diseases.
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26
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Le TTV, Do PC. Molecular docking study of various Enterovirus—A71 3C protease proteins and their potential inhibitors. Front Microbiol 2022; 13:987801. [PMID: 36246267 PMCID: PMC9563145 DOI: 10.3389/fmicb.2022.987801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 08/23/2022] [Indexed: 12/04/2022] Open
Abstract
Hand, foot, and mouth disease (HFMD) is a common infection that primarily affects children in preschool and kindergarten; however, there is yet no vaccination or therapy available. Despite the fact that current research is only focused on numerous strains of Enterovirus—A71 (EV-A71) 3C protease (3Cpro), these investigations are entirely separate and unrelated. Antiviral agents must therefore be tested on several EV strains or mutations. In total, 21 previously reported inhibitors were evaluated for inhibitory effects on eight EV-A71 3Cpro, including wild-type and mutant proteins in this study, and another 29 powerful candidates with inhibitory effects on EV-A71 were investigated using the molecular docking approach. This method is to determine the broad-spectrum of the antiviral agents on a range of strains or mutants because the virus frequently has mutations. Even though Rupintrivir is reported to pass phase I clinical trial, 4-iminooxazolidin-2-one moiety (FIOMC) was shown to have a broader anti-3Cpro spectrum than Rupintrivir. Meanwhile, Hesperidin possessed a better 3Cpro inhibitory capability than FIOMC. Thus, it could be considered the most promising candidate for inhibiting various strains of EV-A71 3Cpro proteins in the newly anti-EV compounds group. Furthermore, the mutation at E71A has the most significant impact on the docking results of all ligands evaluated. Future in vitro experiments on Hesperidin’s ability to inhibit 3Cpro activity should be conducted to compare with FIOMC’s in vitro results and validate the current in silico work.
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Affiliation(s)
- Tran Thao Vy Le
- School of Biotechnology, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Phuc-Chau Do
- School of Biotechnology, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
- *Correspondence: Phuc-Chau Do,
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27
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Yang Z, Rui J, Qi L, Ye W, Niu Y, Luo K, Deng B, Zhang S, Yu S, Liu C, Li P, Wang R, Wei H, Zhang H, Huang L, Zuo S, Zhang L, Zhang S, Yang S, Guo Y, Zhao Q, Wu S, Li Q, Chen Y, Chen T. Study on the interaction between different pathogens of Hand, foot and mouth disease in five regions of China. Front Public Health 2022; 10:970880. [PMID: 36238254 PMCID: PMC9552780 DOI: 10.3389/fpubh.2022.970880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 08/22/2022] [Indexed: 01/25/2023] Open
Abstract
Objectives This study aims to explore the interaction of different pathogens in Hand, foot and mouth disease (HFMD) by using a mathematical epidemiological model and the reported data in five regions of China. Methods A cross-regional dataset of reported HFMD cases was built from four provinces (Fujian Province, Jiangsu province, Hunan Province, and Jilin Province) and one municipality (Chongqing Municipality) in China. The subtypes of the pathogens of HFMD, including Coxsackievirus A16 (CV-A16), enteroviruses A71 (EV-A71), and other enteroviruses (Others), were included in the data. A mathematical model was developed to fit the data. The effective reproduction number (R eff ) was calculated to quantify the transmissibility of the pathogens. Results In total, 3,336,482 HFMD cases were collected in the five regions. In Fujian Province, the R eff between CV-A16 and EV-A71&CV-A16, and between CV-A16 and CV-A16&Others showed statistically significant differences (P < 0.05). In Jiangsu Province, there was a significant difference in R eff (P < 0.05) between the CV-A16 and Total. In Hunan Province, the R eff between CV-A16 and EV-A71&CV-A16, between CV-A16 and Total were significant (P < 0.05). In Chongqing Municipality, we found significant differences of the R eff (P < 0.05) between CV-A16 and CV-A16&Others, and between Others and CV-A16&Others. In Jilin Province, significant differences of the R eff (P < 0.05) were found between EV-A71 and Total, and between Others and Total. Conclusion The major pathogens of HFMD have changed annually, and the incidence of HFMD caused by others and CV-A16 has surpassed that of EV-A71 in recent years. Cross-regional differences were observed in the interactions between the pathogens.
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Affiliation(s)
- Zimei Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Wenjing Ye
- Fujian Center for Disease Control and Prevention, Fuzhou, Fujian, China
| | - Yan Niu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kaiwei Luo
- Hunan Center for Disease Control and Prevention, Changsha, Hunan, China
| | - Bin Deng
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shi Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shanshan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Peihua Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Rui Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Hongjie Wei
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Hesong Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Lijin Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Simiao Zuo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Lexin Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shurui Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Shiting Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Yichao Guo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China
| | - Qinglong Zhao
- Jilin Center for Disease Control and Prevention, Changchun, Jilin, China
| | - Shenggen Wu
- Fujian Center for Disease Control and Prevention, Fuzhou, Fujian, China,Shenggen Wu
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China,Qin Li
| | - Yong Chen
- Department of Stomatology, School of Medicine, Xiamen University, Xiamen, China,Yong Chen
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, China,*Correspondence: Tianmu Chen
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28
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Zhong X, Wang H, Chen C, Zou X, Li T. Epidemiological Characteristics of Hand, Foot and Mouth Disease Reinfection in Guangzhou, Southern China from 2012 to 2017. IRANIAN JOURNAL OF PUBLIC HEALTH 2022; 51:2078-2088. [PMID: 36743381 PMCID: PMC9884378 DOI: 10.18502/ijph.v51i9.10563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 07/11/2021] [Indexed: 11/24/2022]
Abstract
Background Hand, foot and mouth disease (HFMD) reinfection is common because of the limited cross-protection from infections of different enterovirus. We aimed to investigate the epidemiological characteristics and its influential factors of HFMD reinfection in Guangzhou, China. Methods Data on HFMD patients aged ≤5 yr from 2012 to 2017 were extracted from surveillance system. Influential factors of reinfection were assessed using the logistic regression model. Results Of 369,054 HFMD patients, 11,321 patients (3.07%) were classified as reinfection. The reinfection rate in male was higher than in female (χ2=60.11, P<0.001). The reinfection rate in patients ≤1 yr was 3.86%, which showed a downward trend with age (Z=37.37, P trend<0.001). The highest reinfection rate was observed in the scattered children (3.38%), followed by nursery care children and others (χ2=514.75, P<0.001). Besides, higher risk of reinfection was detected among those who were male, lower age group, rural residence and other enteroviruses infection compared with their respective counterparts. Seasonality was illustrated according to the number of reinfections peaked from April to July. Time intervals curves revealed the number of reinfections gradually increased after 13 months from the initial infection. Conclusion Male ≤4 yr, living rural area, especially those lived scattered and infected with other enteroviruses were more likely to be reinfection.
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Affiliation(s)
- Xuan Zhong
- Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518054, China,School of Public Health, Guangdong Pharmaceutical University, Guangzhou 510310, China
| | - Hui Wang
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
| | - Chun Chen
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
| | - Xiaoni Zou
- Guangdong Women and Children Hospital, Guangzhou 510010, China,Corresponding Authors: Emails: ;
| | - Tiegang Li
- Guangzhou Municipal Health Commission, Guangzhou 510062, China,Corresponding Authors: Emails: ;
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29
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Guo W, Xu D, Cong S, Du Z, Li L, Zhang M, Feng C, Bao G, Sun H, Yang Z, Ma S. Co-infection and enterovirus B: post EV-A71 mass vaccination scenario in China. BMC Infect Dis 2022; 22:671. [PMID: 35927711 PMCID: PMC9354358 DOI: 10.1186/s12879-022-07661-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 07/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Hand, foot, and mouth disease (HFMD) is a common child infectious disease caused by more than 20 enterovirus (EV) serotypes. In recent years, enterovirus A71 (EV-A71) has been replaced by Coxsackievirus A6 (CV-A6) to become the predominant serotype. Multiple EV serotypes co-circulate in HFMD epidemics, and this study aimed to investigate the etiological epidemic characteristics of an HFMD outbreak in Kunming, China in 2019. METHODS The clinical samples of 459 EV-associated HFMD patients in 2019 were used to amplify the VP1 gene region by the three sets of primers and identify serotypes using the molecular biology method. Phylogenetic analyses were performed based on the VP1 gene. RESULTS Three hundred and forty-eight cases out of 459 HFMD patients were confirmed as EV infection. Of these 191 (41.61%) were single EV infections and 34.20% had co-infections. The EVs were assigned to 18 EV serotypes, of which CV-A6 was predominant (11.33%), followed by CV-B1 (8.93%), CV-A4 (5.23%), CV-A9 (4.58%), CV-A 16 (3.49%) and CV-A10 and CVA5 both 1.96%. Co-infection of CV-A6 with other EVs was present in 15.25% of these cases, followed by co-infection with CV-A16 and other EVs. The VP1 sequences used in the phylogenetic analyses showed that the CV-A6, CV-B1 and CV-A4 sequences belonged to the sub-genogroup D3 and genogroups F and E, respectively. CONCLUSION Co-circulation and co-infection of multiple serotypes were the etiological characteristic of the HFMD epidemic in Kunming China in 2019 with CV-A-6, CV-B1 and CV-A4 as the predominant serotypes. This is the first report of CV-B1 as a predominant serotype in China and may provide valuable information for the diagnosis, prevention and control of HFMD.
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Affiliation(s)
- Wei Guo
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Danhan Xu
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Shanri Cong
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Zengqing Du
- Department of Infectious Diseases, Kunming Children's Hospital, Kunming, China
| | - Li Li
- Department of Clinical Laboratory, Kunming Maternal and Child Health Hospital, Kunming, 650031, China
| | - Ming Zhang
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Changzeng Feng
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Guohong Bao
- First People's Hospital of Yunnan Province, Kunming, 650032, People's Republic of China
| | - Hao Sun
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Zhaoqing Yang
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China
| | - Shaohui Ma
- Institute of Medical Biology, Chinese Academy of Medical Sciences, and Peking Union Medical College (CAMS & PUMC), 935 Jiao Ling Road, Kunming, 650118, Yunnan Province, People's Republic of China. .,Yunnan Key Laboratory of Vaccine Research Development on Severe Infectious Disease, Kunming, 650118, People's Republic of China.
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30
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Huang L, Wang T, Liu X, Fu Y, Zhang S, Chu Q, Nie T, Tu H, Chen 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; 22:1468. [PMID: 35915424 PMCID: PMC9342842 DOI: 10.1186/s12889-022-13860-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 07/22/2022] [Indexed: 11/25/2022] Open
Abstract
Background The enterovirus 71 (EV-A71) vaccine has been used in Hefei for several years, and the epidemiological significance of vaccination in this area is unclear. We aims to explore the spatial–temporal-demographic and virological changes of hand, foot and mouth disease (HFMD) after vaccination in China. Methods The data for HFMD from 2012 to 2020 were downloaded with the help of HFMD reporting system of Hefei Center for Disease Control and Prevention and combined with the EV-A71 vaccination status in Hefei. The study defined the period between 2012 to 2016 as the pre-vaccination period and explored the effect of vaccination on the incidence of HFMD by comparing the changes of HFMD before and after vaccination in terms of spatial, temporal, demographic and virological aspects. Results During the study period, a higher incidence occurred in urban area and the random distribution changed to a slight cluster after vaccination. HFMD incidence had inconsistent seasonality over years, with one or two incidence peaks in varying years. The morbidity decreased from 215.22/105 in 2012–2016 to 179.81/105 in 2017–2020 (p < 0.001). Boys, 0–4 years old children and Scattered children were more susceptible to HFMD compared with the others, the proportions decreased after vaccination except in Scattered children. The main pathogenic enterovirus gradually changed from EV-A71 to Other Enteroviruses, especially coxsackieviruses A6 (CV-A6) after the implementation of EV-A71 vaccination. Conclusions The EV-A71 vaccine was effective in reducing the incidence of HFMD and changing the spatial, temporal, demographic, and virological characteristic. These changes should be considered during the vaccination implementation to further reduce the disease burden of HFMD. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-13860-z.
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Affiliation(s)
- Li Huang
- Faculty of Clinical Medicine, Anhui Medical College, Hefei, 230601, Anhui, China
| | - Ting Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Xuxiang Liu
- Hefei Center for Disease Control and Prevention, Hefei, 230061, Anhui, China
| | - Yuansheng Fu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Sichen Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Qinshu Chu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Tingyue Nie
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Houmian Tu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Jian Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
| | - Yinguang Fan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
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31
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Kingston NJ, Shegdar M, Snowden JS, Fox H, Groppelli E, Macadam A, Rowlands DJ, Stonehouse NJ. Thermal stabilization of enterovirus A 71 and production of antigenically stabilized empty capsids. J Gen Virol 2022; 103:001771. [PMID: 35997623 PMCID: PMC10019091 DOI: 10.1099/jgv.0.001771] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 05/18/2022] [Indexed: 01/11/2023] Open
Abstract
Enterovirus A71 (EVA71) infection can result in paralysis and may be fatal. In common with other picornaviruses, empty capsids are produced alongside infectious virions during the viral lifecycle. These empty capsids are antigenically indistinguishable from infectious virus, but at moderate temperatures they are converted to an expanded conformation. In the closely related poliovirus, native and expanded antigenic forms of particle have different long-term protective efficacies when used as vaccines. The native form provides long-lived protective immunity, while expanded capsids fail to generate immunological protection. Whether this is true for EVA71 remains to be determined. Here, we selected an antigenically stable EVA71 virus population using successive rounds of heating and passage and characterized the antigenic conversion of both virions and empty capsids. The mutations identified within the heated passaged virus were dispersed across the capsid, including at key sites associated with particle expansion. The data presented here indicate that the mutant sequence may be a useful resource to address the importance of antigenic conformation in EVA71 vaccines.
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Affiliation(s)
- Natalie J. Kingston
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Mona Shegdar
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Joseph S. Snowden
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Helen Fox
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - Elisabetta Groppelli
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
- Present address: Institute for Infection and Immunity, St George’s University of London, Tooting, London, UK
| | - Andrew Macadam
- Division of Virology, National Institute for Biological Standards and Control, Potters Bar, Hertfordshire, UK
| | - David J. Rowlands
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Nicola J. Stonehouse
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
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Xiao J, Zhu Q, Yang F, Zeng S, Zhu Z, Gong D, Li Y, Zhang L, Li B, Zeng W, Li X, Rong Z, Hu J, He G, Sun J, Lu J, Liu T, Ma W, Sun L. The impact of enterovirus A71 vaccination program on hand, foot, and mouth disease in Guangdong, China:a longitudinal surveillance study. J Infect 2022; 85:428-435. [PMID: 35768049 DOI: 10.1016/j.jinf.2022.06.020] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/19/2022] [Accepted: 06/21/2022] [Indexed: 10/17/2022]
Abstract
Enterovirus A71 (EV71) vaccination program was introduced in 2016 in China. Based on a longitudinal surveillance dataset from 2012 to 2019 in Guangdong, China, we estimated the impact of the EV71 vaccination program on hand, foot, and mouth disease (HFMD) incidence, by using a counterfactual prediction made from synthetic control approach integrated with a Bayesian time-series model. We observed a relative reduction of 41.4% for EV71-associated HFMD cases during the post-vaccination period of 2017-2019, corresponding to 26,226 cases averted. The reduction of EV71-associated HFMD cases raised with the elevation of EV71 vaccine coverage by year. We found an indirect effect for the children aged 6-14 years who were less likely to be vaccinated. Whereas, the EV71 vaccine may not protect against non-EV71-associated HFMD. This study provides a template for ongoing public health surveillance of EV71 vaccine effectiveness with a counterfactual study design. Our results show strong evidence of the EV71 vaccination program working on reducing EV71-associated HFMD in real-world settings. The finding will benefit policy-making of EV71 vaccination and the prevention of HFMD.
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Affiliation(s)
- Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Qi Zhu
- Institute of Immunization Program, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Fen Yang
- Institute of Infectious Disease Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Siqing Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Zhihua Zhu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Dexin Gong
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China; World Health Organization Western Pacific Region, 1000 Metro Manila, the Philippines
| | - Yihan Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China; School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Li Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China; School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Bin Li
- Chengde College of Applied Technology, Chengde 067000, Hebei, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Zuhua Rong
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Jiufeng Sun
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Jing Lu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China; Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, Guangdong, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China; Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, Guangdong, China.
| | - Limei Sun
- Institute of Immunization Program, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, Guangdong, China.
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Li P, Rui J, Niu Y, Xie F, Wang Y, Li Z, Liu C, Yu S, Huang J, Luo L, Deng B, Liu W, Yang T, Li Q, Chen T. Analysis of HFMD Transmissibility Among the Whole Population and Age Groups in a Large City of China. Front Public Health 2022; 10:850369. [PMID: 35480581 PMCID: PMC9035867 DOI: 10.3389/fpubh.2022.850369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 03/02/2022] [Indexed: 11/29/2022] Open
Abstract
Background Hand-Foot-and-Mouth-Disease (HFMD) has been widely spread in Asia, and has result in a high disease burden for children in many countries. However, the dissemination characteristics intergroup and between different age groups are still not clear. In this study, we aim to analyze the differences in the transmissibility of HFMD, in the whole population and among age groups in Shenzhen city, by utilizing mathematical models. Methods A database that reports HFMD cases in Shenzhen city from January 2010 to December 2017 was collected. In the first stage, a Susceptive-Infected-Recovered (SIR) model was built to fit data of Shenzhen city and its districts, and Reff was used to assess transmissibility in each district. In the second stage, a cross-age groups SIR model was constructed to calculate the difference in transmissibility of reported cases among three age groups of EV71 virus: 0–3 years, 3–5 years, and over 5 years which was denoted as age group 1, 2, and 3, respectively. Results From 2010 to 2017, 345,807 cases of HFMD were reported in Shenzhen city, with peak incidence in spring and autumn in Shenzhen city and most of its districts each year. Analysis of the EV71 incidence data by age group revealed that age Group 1 have the highest incidence (3.13 ×10−7–2.31 ×10−4) while age group 3 had the lowest incidence (0–3.54 ×10−5). The differences in weekly incidence of EV71 between age groups were statistically significant (t12 = 7.563, P < 0.0001; t23 = 12.420, P < 0.0001; t13 = 16.996, P < 0.0001). The R2 of the SIR model Shenzhen city population-wide HFMD fit for each region was >0.5, and P < 0.001. Reff values were >1 for the vast majority of time and regions, indicating that the HFMD virus has the ability to spread in Shenzhen city over the long-term. Differences in Reff values between regions were judged by using analysis of variance (ANOVA) (F = 0.541, P = 0.744). SiIiRi-SjIjRj models between age groups had R2 over 0.7 for all age groups and P <0.001. The Reff values between groups show that the 0–2 years old group had the strongest transmissibility (median: 2.881, range: 0.017–9.897), followed by the over 5 years old group (median: 1.758, range: 1.005–5.279), while the 3–5 years old group (median: 1.300, range: 0.005–1.005) had the weakest transmissibility of the three groups. Intra-group transmissibility was strongest in the 0–2 years age group (median: 1.787, range: 0–9.146), followed by Group 1 to Group 2 (median: 0.287, range: 0–1.988) and finally Group 1 to Group 3 (median: 0.287, range: 0–1.988). Conclusion The incidence rate of HFMD is high in Shenzhen city. In the data on the incidence of EV71 in each age group, the highest incidence was in the 0–2 years age group, and the lowest incidence was in the over 5 years age group. The differences in weekly incidence rate of EV71 among age groups were statistically significant. Children with the age of 0–2 years had the highest transmissibility.
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Affiliation(s)
- Peihua Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Yan Niu
- Chinese Center for Disease Control and Prevention, Public Health Emergency Center, Beijing, China
| | - Fang Xie
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Yifang Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Zhuoyang Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Shanshan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jiefeng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Li Luo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Bin Deng
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Weikang Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Tianlong Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Qun Li
- Chinese Center for Disease Control and Prevention, Public Health Emergency Center, Beijing, China
- Qun Li
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
- *Correspondence: Tianmu Chen ;
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Transmissibility of hand, foot, and mouth disease in 97 counties of China. Sci Rep 2022; 12:4103. [PMID: 35260706 PMCID: PMC8902910 DOI: 10.1038/s41598-022-07982-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 02/23/2022] [Indexed: 11/18/2022] Open
Abstract
Hand, foot, and mouth disease (HFMD) is a serious disease burden in the Asia–Pacific region, including China. This study calculated the transmissibility of HFMD at county levels in Jiangsu Province, China, analyzed the differences of transmissibility and explored the possible influencing factors of its transmissibility. We built a mathematical model for seasonal characteristics of HFMD, estimated the effective reproduction number (Reff), and compared the incidence rate and transmissibility in different counties using non-parametric tests, rapid cluster analysis and rank-sum ratio in 97 counties in Jiangsu Province from 2015 to 2020. The average daily incidence rate was between 0 and 4 per 100,000 people in Jiangsu Province from 2015–2020. The Quartile of Reff in Jiangsu Province from 2015 to 2020 was 1.54 (0.49, 2.50). Rugao District and Jianhu District had the highest transmissibility according to the rank-sum ratio. Reff generally decreased in 2017 and increased in 2018 in most counties, and the median level of Reff was the lowest in 2017 (P < 0.05). The transmissibility was different in 97 counties in Jiangsu Province. The reasons for the differences may be related to the climate, demographic characteristics, virus subtypes, vaccination, hygiene and other infectious diseases.
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Changing epidemiology of hand, foot, and mouth disease in China, 2013-2019: a population-based study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 20:100370. [PMID: 35036978 PMCID: PMC8743221 DOI: 10.1016/j.lanwpc.2021.100370] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background Hand, foot, and mouth disease (HFMD) is an important public health problem. A monovalent EV-A71 vaccine was launched in China in 2016. Previous studies showed that inactivated monovalent EV-A71 vaccines were highly efficient against HFMD associated with EV-A71 but not against HFMD with other etiologies, leading to a hypothesis that the introduction of EV-A71 vaccines might change the pathogen spectrum and epidemiological trend of HFMD. In this study, we described for the first time the changing epidemiological characteristics of HFMD after the launch of the EV-A71 vaccine. Methods We extracted individual-based epidemiological data on HFMD cases reported to the Chinese Center for Disease Control and Prevention between January 2013 and December 2019. We described the changing epidemiological characteristics of HFMD before and after vaccine launch according to the distribution of diseases characteristics (demographic, temporal, and geographical) and evaluated the potential changes in risk factors of severe patients. All analyses were stratified by the phase before and after vaccine launch, and by enterovirus serotype. Findings During 2013-2019, 15,316,710 probable cases of HFMD were reported. Of these, 787,197 (5·1%) were laboratory confirmed and 76,982 (0·5%) were severe. After the launch of the EV-A71 vaccine, the median age of HFMD patients infected with EV-A71 increased from 2·24 years (IQR:1·43, 3·56) to 2·81 years (IQR:1·58, 4·01). The proportion of patients less than 3 years of age decreased while the proportion of patients 3-5 years of age increased. There was a large decrease (60·7%) in the proportion of severe cases as well as a decline (28·3%) in HFMD patients infected with EV-A71. After the launch of the EV-A71 vaccine, the severe illness rate and mortality rate of HFMD patients in all age groups has decreased sharply, 62·20% and 83·78% respectively. The timing of the HFMD epidemic peak was delayed (1-2 months) . After the launch of EV-A71 vaccine, the risk of becoming a severe case for EV-A71 serotype was decreased, whereas that risk was instead increased for CV-A16 (from 0·17 (95% CI:0·16, 0·18) to 0·23 (95% CI:0·21, 0·25)) and other enterovirus compared to EV-A71 (from 0·38 (95% CI:0·37, 0·39) to 0·58 (95% CI:0·56, 0·61)). The longer the time from onset to diagnosis, the higher was the risk of being a severe case, but the effect size was decreased. Interpretation The introduction of the EV-A71 vaccine has effectively reduced the proportion of severe HFMD cases and mortality, but changes to the dominant serotypes should be closely monitored. Development of multivalent vaccines to avoid an increased case burden due to other enteroviruses is greatly needed. Funding This research was supported by the National Natural Science Foundation of China (81973102, 81773487), Public Health Talents Training Program of Shanghai Municipality (GWV-10.2-XD21), the 5th Three-year Action Program of Shanghai Municipality for Strengthening the Construction of Public Health System (GWV-10.1-XK05), the Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China (2021YFF0306000), 13th Five-Year National Science and Technology Major Project for Infectious Diseases (2018ZX10725-509) and Key projects of the PLA logistics Scientific research Program (BHJ17J013).
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Fong SY, Mori D, Rundi C, Yap JF, Jikal M, Latip ALLBA, Johnny V, Ahmed K. A five-year retrospective study on the epidemiology of hand, foot and mouth disease in Sabah, Malaysia. Sci Rep 2021; 11:17814. [PMID: 34497287 PMCID: PMC8426372 DOI: 10.1038/s41598-021-96083-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 07/27/2021] [Indexed: 11/19/2022] Open
Abstract
Hand, foot, and mouth disease (HFMD) is endemic in Malaysia, with the number of cases increasing. Sabah has experienced several HFMD outbreaks, but information on the epidemiology and molecular characteristics of responsible viruses is scarce. In this study, data of 17,574 reports of HFMD cases in Sabah from 2015 to 2019 were extracted from a public health disease surveillance system and analyzed. Twenty-one swab samples from 13 children were collected from Beaufort, Sabah, during an outbreak in August 2018 for detection and serotyping of causative viruses by semi-nested reverse transcription-polymerase chain reaction (snRT-PCR) of the VP4–VP2 region and consensus degenerate hybrid oligonucleotide primer PCR of the VP1 region, respectively. Nucleotide sequencing and phylogenetic analysis were conducted by the neighbor-joining method. The average annual incidence of HFMD was 94.3 per 100,000 people, with the greatest yearly increase between 2017 and 2018. Swabs from six children were tested positive for enterovirus, of which five were positive for CVA16 and one for EV71. All CVA16 strains belonged to sub-genotype B1a, and the EV71 strain belonged to sub-genotype B5. Phylogenetic analyses indicate that enterovirus genotype shift might be responsible for the increasing trend of HFMD in Sabah, however, further study is needed.
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Affiliation(s)
- Siat Yee Fong
- Borneo Medical and Health Research Centre, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.,Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Daisuke Mori
- Department of Pathology and Microbiology, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Christina Rundi
- Sabah State Health Department, Ministry of Health Malaysia, Jalan Mat Salleh, 88590, Kota Kinabalu, Sabah, Malaysia
| | - Jun Fai Yap
- Sabah State Health Department, Ministry of Health Malaysia, Jalan Mat Salleh, 88590, Kota Kinabalu, Sabah, Malaysia
| | - Muhammad Jikal
- Sabah State Health Department, Ministry of Health Malaysia, Jalan Mat Salleh, 88590, Kota Kinabalu, Sabah, Malaysia
| | - A L Liza Binti Abd Latip
- Beaufort Health Office, Ministry of Health Malaysia, Pekan Beaufort, 89800, Beaufort, Sabah, Malaysia
| | - Victor Johnny
- Sabah State Health Department, Ministry of Health Malaysia, Jalan Mat Salleh, 88590, Kota Kinabalu, Sabah, Malaysia
| | - Kamruddin Ahmed
- Borneo Medical and Health Research Centre, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia. .,Department of Pathology and Microbiology, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
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Yu C, Xu C, Li Y, Yao S, Bai Y, Li J, Wang L, Wu W, Wang Y. Time Series Analysis and Forecasting of the Hand-Foot-Mouth Disease Morbidity in China Using An Advanced Exponential Smoothing State Space TBATS Model. Infect Drug Resist 2021; 14:2809-2821. [PMID: 34321897 PMCID: PMC8312251 DOI: 10.2147/idr.s304652] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 04/26/2021] [Indexed: 12/11/2022] Open
Abstract
Objective The high morbidity, complex seasonality, and recurring risk of hand-foot-and-mouth disease (HFMD) exert a major burden in China. Forecasting its epidemic trends is greatly instrumental in informing vaccine and targeted interventions. This study sets out to investigate the usefulness of an advanced exponential smoothing state space framework by combining Box-Cox transformations, Fourier representations with time-varying coefficients and autoregressive moving average (ARMA) error correction (TBATS) method to assess the temporal trends of HFMD in China. Methods Data from January 2009 to December 2019 were drawn, and then they were split into two segments comprising the in-sample training data and out-of-sample testing data to develop and validate the TBATS model, and its fitting and forecasting abilities were compared with the most frequently used seasonal autoregressive integrated moving average (SARIMA) method. Results Following the modelling procedures of the SARIMA and TBATS methods, the SARIMA (1,0,1)(0,1,1)12 and TBATS (0.024, {1,1}, 0.855, {<12,4>}) specifications were recognized as being the optimal models, respectively, for the 12-step ahead forecasting, along with the SARIMA (1,0,1)(0,1,1)12 and TBATS (0.062, {1,3}, 0.86, {<12,4>}) models as being the optimal models, respectively, for the 24-step ahead forecasting. Among them, the optimal TBATS models produced lower error rates in both 12-step and 24-step ahead forecasting aspects compared to the preferred SARIMA models. Descriptive analysis of the data showed a significantly high level and a marked dual seasonal pattern in the HFMD morbidity. Conclusion The TBATS model has the capacity to outperform the most frequently used SARIMA model in forecasting the HFMD incidence in China, and it can be recommended as a flexible and useful tool in the decision-making process of HFMD prevention and control in China.
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Affiliation(s)
- Chongchong Yu
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, People's Republic of China
| | - Chunjie Xu
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Yuhong Li
- National Center for Tuberculosis Control and Prevention, China Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Sanqiao Yao
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, People's Republic of China
| | - Yichun Bai
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, People's Republic of China
| | - Jizhen Li
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, People's Republic of China
| | - Lei Wang
- Center for Musculoskeletal Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Weidong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, People's Republic of China
| | - Yongbin Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, People's Republic of China
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The changes in the epidemiology of hand, foot, and mouth disease after the introduction of the EV-A71 vaccine. Vaccine 2021; 39:3319-3323. [PMID: 33994239 DOI: 10.1016/j.vaccine.2021.05.009] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 04/25/2021] [Accepted: 05/03/2021] [Indexed: 12/22/2022]
Abstract
Three inactive monovalent EV-A71 vaccines have been launched in China since 2016, which may change the HFMD pathogen spectrum and epidemiological trend. Using notifications from the national surveillance system, we analyzed the epidemiological character profiles and the possible pathogen replacement. The proportion of HFMD cases aged 0-12 months decreased from 23.0% to 15.3% between 2013-2015 and 2017-2019 (p < 0.01). EV-A71 among laboratory-confirmed severe cases in 2013-2015 (62.8%) transformed to other EVs (67.2%) in 2017-2019. The age distribution of EV-A71 infection shifted to the older. The cumulative coverage of the EV-A71 vaccine for children aged six months to five years in Guangxi has increased, while in severe cases, the positive rate declined. After gradually expanded vaccination, EV-A71 associated incidence rate, case-severity rate has decreased, and other serotypes are becoming dominant. Thus, bivalent even polyvalent vaccines are urgently needed to control HFMD.
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Jiang H, Zhang Z, Rao Q, Wang X, Wang M, Du T, Tang J, Long S, Zhang J, Luo J, Pan Y, Chen J, Ma J, Liu X, Fan M, Zhang T, Sun Q. The epidemiological characteristics of enterovirus infection before and after the use of enterovirus 71 inactivated vaccine in Kunming, China. Emerg Microbes Infect 2021; 10:619-628. [PMID: 33682641 PMCID: PMC8018479 DOI: 10.1080/22221751.2021.1899772] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Enterovirus A71 (EV-A71) inactivated vaccines have been widely inoculated among children in Kunming City after it was approved. However, there was a large-scale outbreak of Enteroviruses (EVs) infection in Kunming, 2018. The epidemiological characteristics of HFMD and EVs were analysed during 2008–2018, which are before and three years after EV-A71 vaccine starting to use. The changes in infection spectrum were also investigated, especially for severe HFMD in 2018. The incidence of EV-A71 decreased dramatically after the EV-A71 vaccine starting use. The proportion of non-CV-A16/EV-A71 EVs positive patients raised to 77.17–85.82%, while, EV-A71 and CV-A16 only accounted for 3.41–7.24% and 6.94–19.42% in 2017 and 2018, respectively. CV-A6 was the most important causative agent in all clinical symptoms (severe HFMD, HFMD, Herpangina and fever), accounting from 42.13% to 62.33%. EV-A71 only account for 0.36–2.05%. In severe HFMD, CV-A6 (62.33%), CV-A10 (11.64%), and CV-A16 (10.96%) were the major causative agent in 2018. EV-A71 inactivated vaccine has a good protective effect against EV-A71 and induced EVs infection spectrum changefully. EV-A71 vaccine has no or insignificant cross-protection effect on CV-A6, CV-A10, and CV-A16. Herein, developing 4-valent combined vaccines is urgently needed.
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Affiliation(s)
- Hongchao Jiang
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Zhen Zhang
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Qing Rao
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China.,State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Xiaodan Wang
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, People's Republic of China
| | - Meifen Wang
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Tingyi Du
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Jiaolian Tang
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Shuying Long
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Juan Zhang
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, People's Republic of China
| | - Jia Luo
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, People's Republic of China
| | - Yue Pan
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, People's Republic of China
| | - Junying Chen
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, People's Republic of China
| | - Jing Ma
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Xiaomei Liu
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Mao Fan
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Tiesong Zhang
- Kunming Children's Hospital, The Affiliated Children's Hospital of Kunming Medical University; Institute of Pediatric Disease Research in Yunnan, Kunming, People's Republic of China.,Yunnan Key Laboratory of Children's Major Disease Research, Kunming, People's Republic of China
| | - Qiangming Sun
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, People's Republic of China.,Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, People's Republic of China
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Katris C. A time series-based statistical approach for outbreak spread forecasting: Application of COVID-19 in Greece. EXPERT SYSTEMS WITH APPLICATIONS 2021; 166:114077. [PMID: 33041528 PMCID: PMC7531284 DOI: 10.1016/j.eswa.2020.114077] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 09/06/2020] [Accepted: 09/29/2020] [Indexed: 05/22/2023]
Abstract
The aim of this paper is the generation of a time-series based statistical data-driven procedure in order to track an outbreak. At first are used univariate time series models in order to predict the evolution of the reported cases. Moreover, are considered combinations of the models in order to provide more accurate and robust results. Additionally, statistical probability distributions are considered in order to generate future scenarios. Final step is the build and use of an epidemiological model (tSIR) and the calculation of an epidemiological ratio (R0) for estimating the termination of the outbreak. The time series models include Exponential Smoothing and ARIMA approaches from the classical models, also Feed-Forward Artificial Neural Networks and Multivariate Adaptive Regression Splines from the machine learning toolbox. Combinations include simple mean, Newbolt-Granger and Bates-Granger approaches. Finally, the tSIR model and the R0 ratio are used for estimating the spread and the reversion of the pandemic. The suggested procedure is used to track the COVID-19 epidemic in Greece. This epidemic has appeared in China in December 2019 and has been widespread since then to all over the world. Greece is the center of this empirical study as is considered an early successful paradigm of resistance against the virus.
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Affiliation(s)
- Christos Katris
- Athens University of Economics and Business, Department of Accounting and Finance, Greece
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Verma S, Razzaque MA, Sangtongdee U, Arpnikanondt C, Tassaneetrithep B, Arthan D, Paratthakonkun C, Soonthornworasiri N. Hand, Foot, and Mouth Disease in Thailand: A Comprehensive Modelling of Epidemic Dynamics. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2021; 2021:6697522. [PMID: 33747118 PMCID: PMC7954635 DOI: 10.1155/2021/6697522] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 02/05/2021] [Accepted: 02/20/2021] [Indexed: 01/16/2023]
Abstract
Hand, foot, and mouth disease (HFMD) is a highly contagious disease with several outbreaks in Asian-Pacific countries, including Thailand. With such epidemic characteristics and potential economic impact, HFMD is a significant public health issue in Thailand. Generally, contagious/infectious diseases' transmission dynamics vary across geolocations due to different socioeconomic situations, demography, and lifestyles. Hence, a nationwide comprehensive model of the disease's epidemic dynamics can provide information to understand better and predict a potential outbreak of this disease and efficiently and effectively manage its impact. However, there is no nationwide and comprehensive (i.e., the inclusion of reinfections in the model) model of HFDM dynamics for Thailand. This paper has endeavoured to promote nationwide comprehensive modelling of HFMD's epidemic dynamics and comprehend the reinfection cases. We have formulated the SEIRS epidemiological model with dynamic vitals, including reinfections, to explore this disease's prevalence. We also introduced periodic seasonality to reproduce the seasonal effect. The pattern of spread of this disease is uneven across the provinces in Thailand, so we used K-means clustering algorithm to cluster those provinces into three groups (i.e., highly, moderately, and least affected levels). We also analysed health records collected from district hospitals, which suggest significant reinfection cases. For example, we found that 11% (approximately) of infectious patients return for repeat treatment within the study period. We also performed sensitivity analysis which indicates that the basic reproduction number (R 0) is sensitive to the rate of transmission (β) and the rate at which infected people recover (γ). By fitting the model with HFMD confirmed data for the provinces in each cluster, the basic reproduction number (R 0) was estimated to be 2.643, 1.91, and 3.246 which are greater than 1. Based on this high R 0, this study recommends that this disease will persist in the coming years under identical cultural and environmental conditions.
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Affiliation(s)
- Suraj Verma
- School of Computing, Engineering & Digital Technologies, Teesside University, Southfield Rd, Middlesbrough, UK
| | - M. A. Razzaque
- School of Computing, Engineering & Digital Technologies, Teesside University, Southfield Rd, Middlesbrough, UK
| | - U. Sangtongdee
- School of Computing, Engineering & Digital Technologies, Teesside University, Southfield Rd, Middlesbrough, UK
| | - C. Arpnikanondt
- King Mongkut's University of Technology Thonburi, Bangkok, Thailand
| | - B. Tassaneetrithep
- Center of Research Excellence in Immunoregulation, Research Department, Faculty of Medicine Siriraj Hospital, Bangkok, Thailand
| | - D. Arthan
- Department of Tropical Nutrition and Food Science, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - C. Paratthakonkun
- College of Sports Science and Technology, Mahidol University, Nakhon Pathom, Thailand
| | - N. Soonthornworasiri
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
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42
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Rui J, Luo K, Chen Q, Zhang D, Zhao Q, Zhang Y, Zhai X, Zhao Z, Zhang S, Liao Y, Hu S, Gao L, Lei Z, Wang M, Wang Y, Liu X, Yu S, Xie F, Li J, Liu R, Chiang YC, Zhao B, Su Y, Zhang XS, Chen T. Early warning of hand, foot, and mouth disease transmission: A modeling study in mainland, China. PLoS Negl Trop Dis 2021; 15:e0009233. [PMID: 33760810 PMCID: PMC8021164 DOI: 10.1371/journal.pntd.0009233] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 04/05/2021] [Accepted: 02/11/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Hand, foot, and mouth disease (HFMD) is a global infectious disease; particularly, it has a high disease burden in China. This study was aimed to explore the temporal and spatial distribution of the disease by analyzing its epidemiological characteristics, and to calculate the early warning signals of HFMD by using a logistic differential equation (LDE) model. METHODS This study included datasets of HFMD cases reported in seven regions in Mainland China. The early warning time (week) was calculated using the LDE model with the key parameters estimated by fitting with the data. Two key time points, "epidemic acceleration week (EAW)" and "recommended warning week (RWW)", were calculated to show the early warning time. RESULTS The mean annual incidence of HFMD cases per 100,000 per year was 218, 360, 223, 124, and 359 in Hunan Province, Shenzhen City, Xiamen City, Chuxiong Prefecture, Yunxiao County across the southern regions, respectively and 60 and 34 in Jilin Province and Longde County across the northern regions, respectively. The LDE model fitted well with the reported data (R2 > 0.65, P < 0.001). Distinct temporal patterns were found across geographical regions: two early warning signals emerged in spring and autumn every year across southern regions while one early warning signals in summer every year across northern regions. CONCLUSIONS The disease burden of HFMD in China is still high, with more cases occurring in the southern regions. The early warning of HFMD across the seven regions is heterogeneous. In the northern regions, it has a high incidence during summer and peaks in June every year; in the southern regions, it has two waves every year with the first wave during spring spreading faster than the second wave during autumn. Our findings can help predict and prepare for active periods of HFMD.
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Affiliation(s)
- Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Kaiwei Luo
- Hunan Provincial Center for Disease Control and Prevention, Changsha City, Hunan Province, People’s Republic of China
| | - Qiuping Chen
- Université de Montpellier, Montpellier, France; CIRAD, Intertryp, Montpellier, France; IES, Université de Montpellier-CNRS, Montpellier, France
- Medical Insurance Office, Xiang’an Hospital of Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Dexing Zhang
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, People’s Republic of China
| | - Qinglong Zhao
- Jilin Provincial Center for Disease Control and Prevention, Changchun City, Jilin Province, People’s Republic of China
| | - Yanhong Zhang
- Yunxiao County Center for Disease Control, Zhangzhou City, Fujian Province, People’s Republic of China
| | - Xiongjie Zhai
- Longde County Center for Disease Control, Guyuan City, the Ningxia Hui Autonomous Region, People’s Republic of China
| | - Zeyu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Siyu Zhang
- Hunan Provincial Center for Disease Control and Prevention, Changsha City, Hunan Province, People’s Republic of China
| | - Yuxue Liao
- Shenzhen Centers for Disease Control and Prevention, Shenzhen City, Guangdong Province, People’s Republic of China
| | - Shixiong Hu
- Hunan Provincial Center for Disease Control and Prevention, Changsha City, Hunan Province, People’s Republic of China
| | - Lidong Gao
- Hunan Provincial Center for Disease Control and Prevention, Changsha City, Hunan Province, People’s Republic of China
| | - Zhao Lei
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Mingzhai Wang
- Xiamen City Center for Disease Control and Prevention, Shenzhen City, Fujian Province, People’s Republic of China
| | - Yao Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Xingchun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Shanshan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Fang Xie
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Jia Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Ruoyun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Benhua Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | - Yanhua Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
| | | | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People’s Republic of China
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Min N, Ong YHB, Han AX, Ho SX, Yen EWP, Ban KHK, Maurer-Stroh S, Chong CY, Chu JJH. An epidemiological surveillance of hand foot and mouth disease in paediatric patients and in community: A Singapore retrospective cohort study, 2013-2018. PLoS Negl Trop Dis 2021; 15:e0008885. [PMID: 33566802 PMCID: PMC7901731 DOI: 10.1371/journal.pntd.0008885] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Revised: 02/23/2021] [Accepted: 10/13/2020] [Indexed: 11/30/2022] Open
Abstract
Background While hand, foot and mouth disease (HFMD) is primarily self-resolving—soaring incidence rate of symptomatic HFMD effectuates economic burden in the Asia-Pacific region. Singapore has seen a conspicuous rise in the number of HFMD cases from 2010s. Here, we aims to identify the serology and genotypes responsible for such outbreaks in hospitals and childcare facilities. Methods We studied symptomatic paediatric HFMD cases from 2013 to 2018 in Singapore. Surveillance for subclinical enterovirus infections was also performed in childcares at the same time period. Results Genotyping 101 symptomatic HFMD samples revealed CV-A6 as the major etiological agent for recent outbreaks. We detected infections with CV-A6 (41.0%), EV-A71 (7%), CV-A16 (3.0%), coxsackievirus A2, CV-A2 (1.0%) and coxsackievirus A10, CV-A10 (1.0%). Phylogenetic analysis of local CV-A6 strains revealed a high level of heterogeneity compared against others worldwide, dissimilar to other HFMD causative enteroviruses for which the dominant strains and genotypes are highly region specific. We detected sub-clinical enterovirus infections in childcare centres; 17.1% (n = 245) tested positive for enterovirus in saliva, without HFMD indicative symptoms at the point of sample collection. Conclusions CV-A6 remained as the dominant HFMD causative strain in Singapore. Silent subclinical enteroviral infections were detected and warrant further investigations. In most cases, Hand Foot and Mouth Disease or HFMD typically manifest in mild fever along with sore throat and rashes on the body. From 2010 onwards, Singapore has seen a steady increase in the case number of HFMD reaching tens of thousands in recent years. HFMD is caused by intestinal viruses and in this study, we established with molecular surveillance methods that one of the causative serotypes, CV-A6 is the major etiological agent for HFMD in Singapore for the current decade. We discovered that circulating enterovirus, CV-A6 in Singapore share similarities in genetic make-up to those currently circulating strains found worldwide and found to be especially close to the ones in neighbouring countries. HFMD spreads from person to person, especially in high-risk areas such as childcare centers where children congregate. Therefore, we conducted saliva collections routinely from childcare centers across Singapore and found that subclinical enterovirus infections have also been prevailing in clusters, occurring silently and unnoticed.
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Affiliation(s)
- Nyo Min
- Laboratory of Molecular RNA Virology and Antiviral Strategies, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yasmin Hui Binn Ong
- Laboratory of Molecular RNA Virology and Antiviral Strategies, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Alvin X. Han
- Protein Sequence Analysis Group, Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Si Xian Ho
- Laboratory of Molecular RNA Virology and Antiviral Strategies, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Emmerie Wong Phaik Yen
- Infectious Disease Service, Department of Pediatrics, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Kenneth Hon Kim Ban
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sebastian Maurer-Stroh
- Protein Sequence Analysis Group, Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Department of Biological Sciences (DBS), National University of Singapore (NUS), Singapore, Singapore, Singapore
| | - Chia Yin Chong
- Infectious Disease Service, Department of Pediatrics, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Justin Jang Hann Chu
- Laboratory of Molecular RNA Virology and Antiviral Strategies, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Collaborative and Translation Unit for HFMD, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- * E-mail:
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Yu G, Feng H, Feng S, Zhao J, Xu J. Forecasting hand-foot-and-mouth disease cases using wavelet-based SARIMA-NNAR hybrid model. PLoS One 2021; 16:e0246673. [PMID: 33544752 PMCID: PMC7864434 DOI: 10.1371/journal.pone.0246673] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 01/23/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Hand-foot-and-mouth disease_(HFMD) is one of the most typical diseases in children that is associated with high morbidity. Reliable forecasting is crucial for prevention and control. Recently, hybrid models have become popular, and wavelet analysis has been widely performed. Better prediction accuracy may be achieved using wavelet-based hybrid models. Thus, our aim is to forecast number of HFMD cases with wavelet-based hybrid models. MATERIALS AND METHODS We fitted a wavelet-based seasonal autoregressive integrated moving average (SARIMA)-neural network nonlinear autoregressive (NNAR) hybrid model with HFMD weekly cases from 2009 to 2016 in Zhengzhou, China. Additionally, a single SARIMA model, simplex NNAR model, and pure SARIMA-NNAR hybrid model were established for comparison and estimation. RESULTS The wavelet-based SARIMA-NNAR hybrid model demonstrates excellent performance whether in fitting or forecasting compared with other models. Its fitted and forecasting time series are similar to the actual observed time series. CONCLUSIONS The wavelet-based SARIMA-NNAR hybrid model fitted in this study is suitable for forecasting the number of HFMD cases. Hence, it will facilitate the prevention and control of HFMD.
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Affiliation(s)
- Gongchao Yu
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Huifen Feng
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
- * E-mail:
| | - Shuang Feng
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Jing Zhao
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Jing Xu
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
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Wo X, Yuan Y, Xu Y, Chen Y, Wang Y, Zhao S, Lin L, Zhong X, Wang Y, Zhong Z, Zhao W. TAR DNA-Binding Protein 43 is Cleaved by the Protease 3C of Enterovirus A71. Virol Sin 2021; 36:95-103. [PMID: 32696397 PMCID: PMC7973337 DOI: 10.1007/s12250-020-00262-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 06/01/2020] [Indexed: 12/13/2022] Open
Abstract
Enterovirus A71 (EV-A71) is one of the etiological pathogens leading to hand, foot, and mouth disease (HFMD), which can cause severe neurological complications. The neuropathogenesis of EV-A71 infection is not well understood. The mislocalization and aggregation of TAR DNA-binding protein 43 (TDP-43) is the pathological hallmark of amyotrophic lateral sclerosis (ALS). However, whether TDP-43 was impacted by EV-A71 infection is unknown. This study demonstrated that TDP-43 was cleaved during EV-A71 infection. The cleavage of TDP-43 requires EV-A71 replication rather than the activated caspases due to viral infection. TDP-43 is cleaved by viral protease 3C between the residues 331Q and 332S, while mutated TDP-43 (Q331A) was not cleaved. In addition, mutated 3C which lacks the protease activity failed to induce TDP-43 cleavage. We also found that TDP-43 was translocated from the nucleus to the cytoplasm, and the mislocalization of TDP-43 was induced by viral protease 2A rather than 3C. Taken together, we demonstrated that TDP-43 was cleaved by viral protease and translocated to the cytoplasm during EV-A71 infection, implicating the possible involvement of TDP-43 in the pathogenesis of EV-A71infection.
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Affiliation(s)
- Xiaoman Wo
- Department of Cell Biology, Harbin Medical University, Harbin, 150081, China
| | - Yuan Yuan
- Department of Cell Biology, Harbin Medical University, Harbin, 150081, China
| | - Yong Xu
- Department of Cell Biology, Harbin Medical University, Harbin, 150081, China
| | - Yang Chen
- Department of Microbiology, Harbin Medical University, Harbin, 150081, China
| | - Yao Wang
- Department of Cell Biology, Harbin Medical University, Harbin, 150081, China
| | - Shuoxuan Zhao
- Department of Cell Biology, Harbin Medical University, Harbin, 150081, China
| | - Lexun Lin
- Department of Microbiology, Harbin Medical University, Harbin, 150081, China
| | - Xiaoyan Zhong
- Department of Microbiology, Harbin Medical University, Harbin, 150081, China
| | - Yan Wang
- Department of Microbiology, Harbin Medical University, Harbin, 150081, China
| | - Zhaohua Zhong
- Department of Microbiology, Harbin Medical University, Harbin, 150081, China.
| | - Wenran Zhao
- Department of Cell Biology, Harbin Medical University, Harbin, 150081, China.
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46
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Nguyet LA, Thanh TT, Nhan LNT, Hong NTT, Nhu LNT, Van HMT, Ny NTH, Anh NT, Han DDK, Tuan HM, Huy VQ, Viet HL, Cuong HQ, Thao NTT, Viet DC, Khanh TH, Thwaites L, Clapham H, Hung NT, Chau NVV, Thwaites G, Ha DQ, van Doorn HR, Tan LV. Neutralizing Antibodies against Enteroviruses in Patients with Hand, Foot and Mouth Disease. Emerg Infect Dis 2021; 26:298-306. [PMID: 31961293 PMCID: PMC6986819 DOI: 10.3201/eid2602.190721] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Hand, foot and mouth disease (HFMD) is an emerging infection with pandemic potential. Knowledge of neutralizing antibody responses among its pathogens is essential to inform vaccine development and epidemiologic research. We used 120 paired-plasma samples collected at enrollment and >7 days after the onset of illness from HFMD patients infected with enterovirus A71 (EV-A71), coxsackievirus A (CVA) 6, CVA10, and CVA16 to study cross neutralization. For homotypic viruses, seropositivity increased from <60% at enrollment to 97%-100% at follow-up, corresponding to seroconversion rates of 57%-93%. Seroconversion for heterotypic viruses was recorded in only 3%-23% of patients. All plasma samples from patients infected with EV-A71 subgenogroup B5 could neutralize the emerging EV-A71 subgenogroup C4. Collectively, our results support previous reports about the potential benefit of EV-A71 vaccine but highlight the necessity of multivalent vaccines to control HFMD.
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Head JR, Collender PA, Lewnard JA, Skaff NK, Li L, Cheng Q, Baker JM, Li C, Chen D, Ohringer A, Liang S, Yang C, Hubbard A, Lopman B, Remais JV. Early Evidence of Inactivated Enterovirus 71 Vaccine Impact Against Hand, Foot, and Mouth Disease in a Major Center of Ongoing Transmission in China, 2011-2018: A Longitudinal Surveillance Study. Clin Infect Dis 2020; 71:3088-3095. [PMID: 31879754 PMCID: PMC7819528 DOI: 10.1093/cid/ciz1188] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 12/11/2019] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Enterovirus 71 (EV71) is a major causative agent of hand, foot, and mouth disease (HFMD), associated with severe manifestations of the disease. Pediatric immunization with inactivated EV71 vaccine was initiated in 2016 in the Asia-Pacific region, including China. We analyzed a time series of HFMD cases attributable to EV71, coxsackievirus A16 (CA16), and other enteroviruses in Chengdu, a major transmission center in China, to assess early impacts of immunization. METHODS Reported HFMD cases were obtained from China's notifiable disease surveillance system. We compared observed postvaccination incidence rates during 2017-2018 with counterfactual predictions made from a negative binomial regression and a random forest model fitted to prevaccine years (2011-2015). We fit a change point model to the full time series to evaluate whether the trend of EV71 HFMD changed following vaccination. RESULTS Between 2011 and 2018, 279 352 HFMD cases were reported in the study region. The average incidence rate of EV71 HFMD in 2017-2018 was 60% (95% prediction interval [PI], 41%-72%) lower than predicted in the absence of immunization, corresponding to an estimated 6911 (95% PI, 3246-11 542) EV71 cases averted over 2 years. There were 52% (95% PI, 42%-60%) fewer severe HFMD cases than predicted. However, the incidence rate of non-CA16 and non-EV71 HFMD was elevated in 2018. We identified a significant decline in the trend of EV71 HFMD 4 months into the postvaccine period. CONCLUSIONS We provide the first real-world evidence that programmatic vaccination against EV71 is effective against childhood HFMD and present an approach to detect early vaccine impact or intended consequences from surveillance data.
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Affiliation(s)
- Jennifer R Head
- Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Philip A Collender
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Joseph A Lewnard
- Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, California, USA
- Center for Computational Biology, College of Engineering, University of California, Berkeley, Berkeley, California, USA
| | - Nicholas K Skaff
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Ling Li
- Institute for Public Health Information, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Qu Cheng
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Julia M Baker
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Charles Li
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Dehao Chen
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA
| | - Alison Ohringer
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Song Liang
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA
| | - Changhong Yang
- Institute for Public Health Information, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Alan Hubbard
- Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Benjamin Lopman
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Justin V Remais
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
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48
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Zhang Z, Liu Y, Liu F, Ren M, Nie T, Cui J, Chang Z, Li Z. Basic Reproduction Number of Enterovirus 71 Coxsackievirus A16 and A6: Evidence from Outbreaks of Hand, Foot and Mouth Disease in China between 2011 and 2018. Clin Infect Dis 2020; 73:e2552-e2559. [PMID: 33320199 DOI: 10.1093/cid/ciaa1853] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Enterovirus 71 (EV-A71), Coxsackievirus A16 (CV-A16) and Coxsackievirus A6 (CV-A6) are common serotypes causing hand, foot, and mouth disease (HFMD). Analyses on the basic reproduction number (R0) of common pathogens causing HFMD are limited and there are no related studies using field data from outbreaks in mainland China. METHODS We estimated the pathogen-specific basic reproduction number based on laboratory-confirmed HFMD outbreaks (clusters of ≥10 HFMD cases) reported to the national surveillance system between 2011 and 2018. The reproduction numbers were calculated using a mathematical model and the cumulative cases during the initial growth periods. RESULTS This study included 539 outbreaks, of which 198 were caused by EV-A71, 316 by CV-A16, and 25 by CV-A6. All 10417 cases involved were children. Assuming the outbreaks occurred in closed systems and the incubation period is 5 days, the median R0s of EV-A71, CV-A16, and CV-A6 were 5.06 [2.81, 10.20], 4.84 [3.00, 9.00] and 5.94 [3.27, 10.00] (Median [IQR]). After adjusting for seroprevalences, the R0s for EV-A71, CV-A16 (optimistic and conservative scenarios), and CV-A6 were 12.60 [IQR: 7.35, 25.40], 9.29 [IQR: 6.01, 19.20], 15.50 [IQR: 9.77, 30.40], and 25.80 [IQR: 14.20, 43.50], respectively. We did not observe changes in the R0s of EV-A71 after vaccine licensure (p-value = 0.67). CONCLUSIONS HFMD is highly transmissible when caused by the three most common serotypes. In mainland China, it primarily affects young children. Although a vaccine became available in 2016, we have not yet observed any related changes in the disease dynamics.
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Affiliation(s)
- Zhong Zhang
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China.,Chinese Field Epidemiology Training Program (CFETP), Beijing, China
| | - Yang Liu
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Beijing, China
| | - Fengfeng Liu
- Division of Infectious disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Minrui Ren
- Division of Infectious disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Taoran Nie
- Division of Infectious disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jinzhao Cui
- Division of Infectious disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaorui Chang
- Division of Infectious disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhongjie Li
- Division of Infectious disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
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49
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Han Z, Song Y, Xiao J, Jiang L, Huang W, Wei H, Li J, Zeng H, Yu Q, Li J, Yu D, Zhang Y, Li C, Zhan Z, Shi Y, Xiong Y, Wang X, Ji T, Yang Q, Zhu S, Yan D, Xu W, Zhang Y. Genomic epidemiology of coxsackievirus A16 in mainland of China, 2000-18. Virus Evol 2020; 6:veaa084. [PMID: 33343924 PMCID: PMC7733612 DOI: 10.1093/ve/veaa084] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Hand, foot, and mouth disease (HFMD), which is a frequently reported and concerning disease worldwide, is a severe burden on societies globally, especially in the countries of East and Southeast Asia. Coxsackievirus A16 (CV-A16) is one of the most important causes of HFMD and a severe threat to human health, especially in children under 5 years of age. To investigate the epidemiological characteristics, spread dynamics, recombinant forms (RFs), and other features of CV-A16, we leveraged the continuous surveillance data of CV-A16-related HFMD cases collected over an 18-year period. With the advent of the EV-A71 vaccine since 2016, which targeted the EV-A71-related HFMD cases, EV-A71-related HFMD cases decreased dramatically, whereas the CV-A16-related HFMD cases showed an upward trend from 2017 to October 2019. The CV-A16 strains observed in this study were genetically related and widely distributed in the mainland of China. Our results show that three clusters (B1a-B1c) existed in the mainland of China and that the cluster of B1b dominates the diffusion of CV-A16 in China. We found that eastern China played a decisive role in seeding the diffusion of CV-A16 in China, with a more complex and variant transmission trend. Although EV-A71 vaccine was launched in China in 2016, it did not affect the genetic diversity of CV-A16, and its genetic diversity did not decline, which confirmed the epidemiological surveillance trend of CV-A16. Two discontinuous clusters (2000-13 and 2014-18) were observed in the full-length genome and arranged along the time gradient, which revealed the reason why the relative genetic diversity of CV-A16 increased and experienced more complex fluctuation model after 2014. In addition, the switch from RFs B (RF-B) and RF-C co-circulation to RF-D contributes to the prevalence of B1b cluster in China after 2008. The correlation between genotype and RFs partially explained the current prevalence of B1b. This study provides unprecedented full-length genomic sequences of CV-A16 in China, with a wider geographic distribution and a long-term time scale. The study presents valuable information about CV-A16, aimed at developing effective control strategies, as well as a call for a more robust surveillance system, especially in the Asia-Pacific region.
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Affiliation(s)
- Zhenzhi Han
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Yang Song
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Jinbo Xiao
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Lili Jiang
- Yunnan Center for Disease Control and Prevention, Kunming, Yunnan Province, People's Republic of China
| | - Wei Huang
- Chongqing Center for Disease Control and Prevention, Chongqing City, People's Republic of China
| | - Haiyan Wei
- Henan Center for Disease Control and Prevention, Zhengzhou, Henan Province, People's Republic of China
| | - Jie Li
- Beijing Center for Disease Control and Prevention, Beijing City, People's Republic of China
| | - Hanri Zeng
- Guangdong Center for Disease Control and Prevention, Guangzhou, Guangdong Province, People's Republic of China
| | - Qiuli Yu
- Hebei Center for Disease Control and Prevention, Shijiazhuang, Hebei Province, People's Republic of China
| | - Jiameng Li
- Tianjin Center for Disease Control and Prevention, Tianjin City, People's Republic of China
| | - Deshan Yu
- Gansu Center for Disease Control and Prevention, Lanzhou, Gansu Province, People's Republic of China
| | - Yanjun Zhang
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China
| | - Chonghai Li
- Qinghai Center for Disease Control and Prevention, Xining, Qinghai Province, People's Republic of China
| | - Zhifei Zhan
- Hunan Center for Disease Control and Prevention, Changsha, Hunan Province, People's Republic of China
| | - Yonglin Shi
- Anhui Center for Disease Control and Prevention, Hefei, Anhui Province, People's Republic of China
| | - Ying Xiong
- Jiangxi Center for Disease Control and Prevention, Nanchang, Jiangxi Province, People's Republic of China
| | - Xianjun Wang
- Shandong Center for Disease Control and Prevention, Jinan, Shandong Province, People's Republic of China
| | - Tianjiao Ji
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Qian Yang
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Shuangli Zhu
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Dongmei Yan
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China
| | - Wenbo Xu
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China.,Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, Hubei Province, People's Republic of China
| | - Yong Zhang
- WHO WPRO Regional Polio Reference Laboratory and National Laboratory for Poliomyelitis, NHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping District, Beijing, 102206, People's Republic of China.,Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, Hubei Province, People's Republic of China
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50
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Wei X, Yang J, Gao L, Wang L, Liao Q, Qiu Q, Luo K, Yu S, Zhou Y, Liu F, Chen Q, Zhang J, Dai B, Yang H, Zhou J, Xing W, Chen X, He M, Ren L, Guo J, Luo L, Wu P, Chen Z, van Doorn HR, Cauchemez S, Cowling BJ, Yu H. The transfer and decay of maternal antibodies against enterovirus A71, and dynamics of antibodies due to later natural infections in Chinese infants: a longitudinal, paired mother-neonate cohort study. THE LANCET. INFECTIOUS DISEASES 2020; 21:418-426. [PMID: 33031750 DOI: 10.1016/s1473-3099(20)30480-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/29/2020] [Accepted: 05/06/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Since 1997, epidemics of hand, foot, and mouth disease associated with enterovirus A71 (EV-A71) have affected children younger than 5 years in the Asia-Pacific region, including mainland China. EV-A71 vaccines have been licensed for use in children aged 6-71 months in China, but not for infants younger than 6 months. We aimed to assess the dynamics of maternal EV-A71 antibodies to inform choice of potential vaccination strategies to protect infants younger than 6 months, because they have a substantial burden of disease. METHODS We did a longitudinal cohort study with mother-neonate pairs in local hospitals in southern China during 2013-18. We collected cord blood from neonates and venous blood from mothers at delivery. We followed up and collected blood samples from the children at ages 2, 4, 6, 12, 24, and 36 months and tested for the presence of neutralising antibodies against EV-A71 with virus neutralisation assays. Seropositivity, or protective titre, was defined as a neutralisation antibody titre of 16 or higher. We estimated the seroprevalence, geometric mean titre (GMT), and transfer ratio of maternal antibodies. We used a binomial distribution to derive the 95% CIs of seroprevalence. Seropositivity between mothers and neonates was compared by use of an agreement (κ), while GMTs were compared by use of paired Student's t tests. FINDINGS Between Sept 20, 2013, and Oct 14, 2015, 1054 mothers with 1066 neonates were enrolled. The EV-A71 GMT was similar among pairs of neonates (22·7, 95% CI 20·8-24·9) and mothers (22·1, 95% CI 20·2-24·1; p=0·20). The mean transfer ratio of maternal antibodies was 1·03 (95% CI 0·98-1·08). Although 705 (66%) of 1066 neonates acquired protective concentrations of EV-A71 antibodies from mothers, these declined rapidly, with a half-life of 42 days (95% CI 40-44). The time to loss of protective immunity was extended to 5 months in neonates with mothers who had titres of 128 or higher. By age 30 months, 28% of children had become seropositive because of natural infection. INTERPRETATION EV-A71 maternal antibodies were efficiently transferred to neonates, but declined quickly to below the protective threshold, particularly among those whose mothers had low antibody titres. Our findings suggest that maternal vaccination could be explored to provide neonatal protection against EV-A71 through maternal antibodies. Catch-up vaccination between ages 6 months to 5 years could provide protection to the approximately 30-90% of children that have not had natural EV-A71 infection by that age. FUNDING National Science Fund for Distinguished Young Scholars, National Natural Science Foundation of China.
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Affiliation(s)
- Xianglin Wei
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lidong Gao
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Lili Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Institut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai, China
| | - Qiaohong Liao
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qi Qiu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Kaiwei Luo
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Shuanbao Yu
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yonghong Zhou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Fengfeng Liu
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qi Chen
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China; Hubei Provincial Center for Disease Control and Prevention, Wuhan, China
| | - Juanjuan Zhang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Bingbing Dai
- Anhua County Center for Disease Control and Prevention, Yiyang, China
| | - Hao Yang
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Jiaxin Zhou
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Weijia Xing
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China
| | - Xinhua Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Min He
- Anhua County Center for Disease Control and Prevention, Yiyang, China
| | - Lingshuang Ren
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jinxin Guo
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Li Luo
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Zhiyong Chen
- Anhua County Center for Disease Control and Prevention, Yiyang, China
| | - H Rogier van Doorn
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam; Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, Centre National de la Recherche Scientifique, Paris, France
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
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