ArticlePLoS neglected tropical diseases2020
Using a Bayesian spatiotemporal model to identify the influencing factors and high-risk areas of hand, foot and mouth disease (HFMD) in Shenzhen.
Article in PLoS neglected tropical diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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16 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Pooled it
- Spatiotemporal Analysis of the Primary Factors and Risk Quantification of Human Brucellosis Prevention and Control in Zhejiang Province of China.Zoonoses and public health · 2026Article
- Epidemiological characteristics and spatiotemporal analysis of hand-foot-mouth disease in Shandong Province, China.International health · 2026Article
- Dynamic changes of hand, foot, and mouth disease epidemic crossing three periods in Jiangxi Province, China: a long-term epidemiology retrospective study from 2009 to 2022.BMC infectious diseases · 2026Article
- Bayesian joint spatiotemporal modelling of primary infection and reinfection of HFMD at county level in Jiangsu, China, 2009-2023.BMC public health · 2025Article
- Hand, Foot, and Mouth Disease Risk Prediction in Southern China: Time Series Study Integrating Web-Based Search and Epidemiological Surveillance Data.JMIR infodemiology · 2025Article
- Spatiotemporal Distribution Characteristic and Influencing Factors of African Swine Fever Outbreaks (2018/8-2019/12) in China.Veterinary medicine international · 2025Article
- Effect of EV71 Vaccination on Transmission Dynamics of Hand, Foot, and Mouth Disease and Its Epidemic Prevention Threshold.Vaccines · 2024Article
- The Distribution and Associated Factors of HIV/AIDS Among Youths in Guangxi, China, From 2014 to 2021: Bayesian Spatiotemporal Analysis.JMIR public health and surveillance · 2024Article
- The non-stationary and spatially varying associations between hand, foot and mouth disease and multiple environmental factors: A Bayesian spatiotemporal mapping model study.Infectious Disease Modelling · 2024Article
- Article
- Spatiotemporal patterns and risk mapping of provincial hand, foot, and mouth disease in mainland China, 2014-2017.Frontiers in public health · 2024Article
- Associations between ambient air pollutants and childhood hand, foot, and mouth disease in Sichuan, China: a spatiotemporal study.Scientific reports · 2023Article
- Effects of temperature and PMEnvironmental science and pollution research international · 2022Article
- Analysis of HFMD Transmissibility Among the Whole Population and Age Groups in a Large City of China.Frontiers in public health · 2022Article
- Study on the interaction between different pathogens of Hand, foot and mouth disease in five regions of China.Frontiers in public health · 2022Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsThis 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.
resultsThe 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.
conclusionsStudies 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.
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