Research On Influencing Factors Of Hand,Foot And Mouth Disease Based On Bayesian Spatiotemporal Model

Hand,foot,and mouth disease(HFMD)is an epidemic infectious disease caused by enterovirus,which is common in children under 5 years old.The virus is transmitted through fecal-oral,droplet,direct contact,etc.Clinical symptoms include fever and rash,and serious complications may occur in a few cases.Since it was included in the monitoring and management system in 2008,the cumulative number of cases of HFMD reported in China has exceeded 20 million,and its annual incidence is at the forefront of various infectious diseases.The transmission mechanism of HFMD is complex,and its epidemic dynamics is not only affected by human immunity,but also closely related to various factors such as climate and meteorology,social economy,and population mobility.The prevention and control measures during the corona virus disease 2019(COVID-19)epidemic also had a synergistic intervention effect on it.Therefore,it is of great significance to reasonably quantify the risk-driven effects of various influencing factors and finely evaluate the intervention effect to improve the prevention and control of HFMD.Taking Xi’an as an example,this study started from the collection and integration of multi-source data and carried out three parts of research content around influencing factors of HFMD.(1)The comprehensive epidemiological characteristics of HFMD were extracted using multiple methods from the perspectives of population,time and space.(2)A Bayesian spatiotemporal mapping model was developed,including spatiotemporal effect structure selection,smoothing function and spatially varying coefficient modeling,etc.Based on the model results,the impact mechanism of natural environment and socioeconomic factors on the risk of HFMD was analyzed,and its possible causes were further discussed.(3)Firstly,the seasonal and trend change points of the time series of HFMD cases during the COVID-19 epidemic were detected.Secondly,based on the Bayesian structural time series model,the "counterfactual number of cases" was predicted and the change in the number of cases caused by the intervention was calculated.Finally,combined with the interrupted regression design and dynamic regression coefficients,the type and size of the intervention effect of the COVID-19 prevention and control measures were estimated,and the relationship between HFMD and influencing factors was analyzed during the process.The research results showed that the relationship between meteorological conditions and the risk of HFMD fluctuated,and the increase in the concentration of air pollutants would increase the risk of HFMD to a certain extent.The impact of population density on HFMD is uneven in time and space.The number of primary schools and kindergartens has a more significant impact on HFMD,and the risk of HFMD increases first and then decreases and stabilizes in the process of urbanization.During the COVID-19 epidemic,the seasonal pattern of HFMD in Xi’an switched between bimodal and unimodal.Strict prevention and control measures in 2020 reduced the number of HFMD cases by 4974(91% relatively),and there was a rebound in the normalized prevention and control stage.The intervention effect mainly manifests as changes in the level and trend of case numbers and alters its correlation with influencing factors.This study contributes to strengthening the prevention and control measures of HFMD and reducing the health burden of the disease,and also promotes the better integration of epidemiology and spatial statistics.