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. 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. 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. 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. 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).

Background: The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around the world. To effectively prevent and control the epidemic, researchers have widely employed dynamic models to predict and simulate the epidemic’s development, understand the spread rule, evaluate the effects of intervention measures, inform vaccination strategies, and assist in the formulation of prevention and control measures. In this review, we aimed to sort out the compartmental structures used in COVID-19 dynamic models and provide reference for the dynamic modeling for COVID-19 and other infectious diseases in the future. Main text: A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted. Conclusion: There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases. Graphical "Image missing"

Hand, foot, and mouth disease (HFMD) has become an emerging infectious disease in China in the last decade. There has been evidence that meteorological factors can influence the HFMD incidence, and understanding the mechanisms can help prevent and control HFMD. HFMD incidence data and meteorological data in Minhang District, Shanghai were obtained for the period between 2009 and 2015. Distributed lag non-linear models (DLNMs) were utilized to investigate the impact of meteorological factors on HFMD incidence after adjusting for potential confounders of long time trend, weekdays and holidays. There was a non-linear relationship between temperature and HFMD incidence, the RR of 5th percentile compared to the median is 0.836 (95% CI: 0.671–1.042) and the RR of 95th percentile is 2.225 (95% CI: 1.774–2.792), and the effect of temperature varied across age groups. HFMD incidence increased with increasing average relative humidity (%) (RR = 1.009, 95% CI: 1.005–1.015) and wind speed (m/s) (RR = 1.197, 95% CI: 1.118–1.282), and with decreasing daily rainfall (mm) (RR = 0.992, 95% CI: 0.987–0.997) and sunshine hours (h) (RR = 0.966, 95% CI: 0.951–0.980). There were significant relationships between meteorological factors and childhood HFMD incidence in Minhang District, Shanghai. This information can help local health agencies develop strategies for the control and prevention of HFMD under specific climatic conditions.