Using a Bayesian spatiotemporal model to identify the influencing factors and high-risk areas of hand, foot and mouth disease (HFMD) in Shenzhen

Background: The epidemic of hand, foot, and mouth disease (HFMD) has become a severe public health problem in the world and has also brought a high economic and health burden. Furthermore, the prevalence of HFMD varies significantly among different locations. However, there have been few investigations of the effects of socioeconomic factors and air pollution factors on the incidence of HFMD. Methods: This study collected data on HFMD in Shenzhen, China, from 2012 to 2015. We selected eleven factors as potential risk factors for HFMD. A Bayesian spatiotemporal model was used to quantify the influence of the factors on HFMD and to identify the relative risks in different districts. Results: The risk factors of HFMD were the population, population density, concentration of SO2, and concentration of NO2. The relative risks (RRs) were 1.00473 (95% CI: 1.00059–1.00761), 1.00010 (95% CI: 1.00002–1.00016), 1.00215 (95% CI: 1.00170–1.00232) and 1.00058 (95% CI: 1.00028–1.00078), respectively. The protective factors against HFMD were the per capita GDP, the number of public kindergartens, the concentration of PM10, and the concentration of O3. The RRs were 0.98840 (95% CI: 0.98660–0.99026), 0.97686 (95% CI: 0.96946–0.98403), 0.99108 (95% CI: 0.98551–0.99840) and 0.99587 (95% CI: 0.99534–0.99610), respectively. The risk of incidence in Longgang district and Pingshan district decreased, while the risk of incidence in Baoan district increased. Conclusions: Studies have confirmed that socioeconomic factors and air pollution factors have an impact on the incidence of HFMD in Shenzhen, China. The results will be of great practical significance to local authorities, which is conducive to accurate prevention and can be used to formulate HFMD early warning systems. Author summary: This study used Bayesian spatiotemporal modelling to analyze the factors that influence the incidence of hand, foot, and mouth disease (HFMD)in Shenzhen, including socioeconomic factors and air pollution factors. A total of 171,210 HFMD cases and socioeconomic and air pollution data from 2012–2015 were included in the analysis. Studies have confirmed that socioeconomic factors and air pollution factors affect the risk of HFMD in Shenzhen, China. By testing the optimal model, the relative risk map of each area was drawn to identify the high-risk areas of HFMD and the future trends of the disease. The results will be of great practical significance to local authorities, which is conducive to accurate prevention and can be used to formulate targeted disease intervention measures.