ArticlePloS one2012
Determinants of the incidence of hand, foot and mouth disease in China using geographically weighted regression models.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.
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Who cites it
62 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Small-scale spatiotemporal epidemiology of notifiable infectious diseases in China: a systematic review.BMC infectious diseases · 2022Pooled it
- Seroprevalence of Enterovirus 71 Antibody Among Children in China: A Systematic Review and Meta-analysis.The Pediatric infectious disease journal · 2015Pooled it
- From Global to Local: A Multiscale Geographically Weighted Regression Analysis of Bovine Brucellosis Risk Factors.Transboundary and emerging diseases · 2026Article
- Impact of meteorological factors on the incidence of hand, foot, and mouth disease caused by major enterovirus pathogens: a distributed lag nonlinear analysis in Fujian Province, China.BMC infectious diseases · 2025Article
- Epidemiological, etiological, and serological characteristics of hand, foot, and mouth disease in Guizhou Province, Southwest China, from 2008 to 2023.PLoS neglected tropical diseases · 2025Article
- Spatiotemporal Distribution of Hand, Foot, and Mouth Disease and the Influence of Air Pollutants and Socioeconomic Factors on Incidence in Fujian, China.Tropical medicine and infectious disease · 2025Article
- Spatiotemporal Changes and Influencing Factors of Hand, Foot, and Mouth Disease in Guangzhou, China, From 2013 to 2022: Retrospective Analysis.JMIR public health and surveillance · 2024Article
- Integration of Moran's I, geographically weighted regression (GWR), and ordinary least square (OLS) models in spatiotemporal modeling of COVID-19 outbreak in Qom and Mazandaran Provinces, Iran.Modeling earth systems and environment · 2023Article
- Health-Based Geographic Information Systems for Mapping and Risk Modeling of Infectious Diseases and COVID-19 to Support Spatial Decision-Making.Advances in experimental medicine and biology · 2022Review
- Changes in notifiable infectious disease incidence in China during the COVID-19 pandemic.Nature communications · 2021Article
- 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
- Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost.PloS one · 2021Article
- Assessment of Temperature-Hand, Foot, and Mouth Disease Association and Its Variability across Urban and Rural Populations in Wuxi, China: A Distributed Lag Nonlinear Analysis.The American journal of tropical medicine and hygiene · 2020Article
- Integration of a Kalman filter in the geographically weighted regression for modeling the transmission of hand, foot and mouth disease.BMC public health · 2020Article
- Transmission center and driving factors of hand, foot, and mouth disease in China: A combined analysis.PLoS neglected tropical diseases · 2020Article
- Transmission and serotype features of hand foot mouth disease in household contacts in Dong Thap, Vietnam.BMC infectious diseases · 2019Article
- Health impact of climate change in cities of middle-income countries: the case of China.British medical bulletin · 2019Review
- Real-Time Forecasting of Hand-Foot-and-Mouth Disease Outbreaks using the Integrating Compartment Model and Assimilation Filtering.Scientific reports · 2019Article
- Space-time heterogeneity of hand, foot and mouth disease in children and its potential driving factors in Henan, China.BMC infectious diseases · 2018Article
- Exploration of potential risks of Hand, Foot, and Mouth Disease in Inner Mongolia Autonomous Region, China Using Geographically Weighted Regression Model.Scientific reports · 2018Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOver the past two decades, major epidemics of hand, foot, and mouth disease (HFMD) have occurred throughout most of the West-Pacific Region countries, causing thousands of deaths among children. However, few studies have examined potential determinants of the incidence of HFMD.
methodsReported HFMD cases from 2912 counties in China were obtained for May 2008. The monthly HFMD cumulative incidence was calculated for children aged 9 years and younger. Child population density (CPD) and six climate factors (average-temperature [AT], average-minimum-temperature [AT(min)], average-maximum-temperature [AT(max)], average-temperature-difference [AT(diff)], average-relative-humidity [ARH], and monthly precipitation [MP]) were selected as potential explanatory variables for the study. Geographically weighted regression (GWR) models were used to explore the associations between the selected factors and HFMD incidence at county level.
resultsThere were 176,111 HFMD cases reported in the studied counties. The adjusted monthly cumulative incidence by county ranged from 0.26 cases per 100,000 children to 2549.00 per 100,000 children. For local univariate GWR models, the percentage of counties with statistical significance (p<0.05) between HFMD incidence and each of the seven factors were: CPD 84.3%, AT(max) 54.9%, AT 57.8%, AT(min) 61.2%, ARH 54.4%, MP 50.3%, and AT(diff) 51.6%. The R(2) for the seven factors' univariate GWR models are CPD 0.56, AT(max) 0.53, AT 0.52, MP 0.51, AT(min) 0.52, ARH 0.51, and AT(diff) 0.51, respectively. CPD, MP, AT, ARH and AT(diff) were further included in the multivariate GWR model, with R(2) 0.62, and all counties show statistically significant relationship.
conclusionChild population density and climate factors are potential determinants of the HFMD incidence in most areas in China. The strength and direction of association between these factors and the incidence of HFDM is spatially heterogeneous at the local geographic level, and child population density has a greater influence on the incidence of HFMD than the climate factors.
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