ArticleInternational journal of environmental research and public health2018
Risk Assessment and Mapping of Hand, Foot, and Mouth Disease at the County Level in Mainland China Using Spatiotemporal Zero-Inflated Bayesian Hierarchical Models.
Article in International journal of environmental research and public health, 2018. 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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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Small-scale spatiotemporal epidemiology of notifiable infectious diseases in China: a systematic review.BMC infectious diseases · 2022Pooled it
- Systematic prediction of spatiotemporal transmission of potential respiratory pandemics in China.Infectious Disease Modelling · 2026Article
- Spatiotemporal trends and ecological determinants of human brucellosis among 31 provinces in mainland China, 2004-2021: a Bayesian spatiotemporal modeling study.BMC public health · 2025Article
- Bayesian joint spatiotemporal modelling of primary infection and reinfection of HFMD at county level in Jiangsu, China, 2009-2023.BMC public health · 2025Article
- Article
- Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Spatio-temporal pattern and associate factors of intestinal infectious diseases in Zhejiang Province, China, 2008-2021: a Bayesian modeling study.BMC public health · 2023Article
- Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China.BMC infectious diseases · 2023Article
- Impact of meteorological factors on the incidence of hand-foot-mouth disease in Yangzhou from 2017 to 2022: a time series study.Frontiers in public health · 2023Article
- Analysis of HFMD Transmissibility Among the Whole Population and Age Groups in a Large City of China.Frontiers in public health · 2022Article
- Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Their Influencing Factors in Urumqi, China.International journal of environmental research and public health · 2021Article
- Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Its Response to Climate Factors in the Ili River Valley Region of China.International journal of environmental research and public health · 2021Article
- Effect of climate factors on the incidence of hand, foot, and mouth disease in Malaysia: A generalized additive mixed model.Infectious Disease Modelling · 2021Article
- Spatial and Temporal Impacts of Socioeconomic and Environmental Factors on Healthcare Resources: A County-Level Bayesian Local Spatiotemporal Regression Modeling Study of Hospital Beds in Southwest China.International journal of environmental research and public health · 2020Article
- Spatial-temporal heterogeneity of hand, foot and mouth disease and impact of meteorological factors in arid/ semi-arid regions: a case study in Ningxia, China.BMC public health · 2019Article
- Spatio-Temporal Analysis of Infectious Diseases.International journal of environmental research and public health · 2019Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hand, foot, and mouth disease (HFMD) is a worldwide infectious disease, prominent in China. China's HFMD data are sparse with a large number of observed zeros across locations and over time. However, no previous studies have considered such a zero-inflated problem on HFMD's spatiotemporal risk analysis and mapping, not to mention for the entire Mainland China at county level. Monthly county-level HFMD cases data combined with related climate and socioeconomic variables were collected. We developed four models, including spatiotemporal Poisson, negative binomial, zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models under the Bayesian hierarchical modeling framework to explore disease spatiotemporal patterns. The results showed that the spatiotemporal ZINB model performed best. Both climate and socioeconomic variables were identified as significant risk factors for increasing HFMD incidence. The relative risk (
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