ArticleEpidemiology and infection2017
Association between meteorological factors and reported cases of hand, foot, and mouth disease from 2000 to 2015 in Japan.
Article in Epidemiology and infection, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 37 citations in OpenAlex.
- Pathogens Associated with Domestic Cats (Pathogens (Basel, Switzerland) · 2026Review
- Modelling the impacts of meteorological factors on herpangina: a Bayesian spatiotemporal analysis.Tropical medicine and health · 2026Article
- Dynamic network entropy for pinpointing the pre-outbreak stage of infectious disease.Journal of the Royal Society, Interface · 2025Article
- Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China.BMC infectious diseases · 2023Article
- Epidemiological characteristics, spatial clusters and monthly incidence prediction of hand, foot and mouth disease from 2017 to 2022 in Shanxi Province, China.Epidemiology and infection · 2023Article
- Exploring the influence of COVID-19 on the spread of hand, foot, and mouth disease with an automatic machine learning prediction model.Environmental science and pollution research international · 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
- Article
- The spatial-temporal distribution and etiological characteristics of hand-foot-and-mouth disease before and after EV‑A71 vaccination in Kunming, China, 2017-2020.Scientific reports · 2022Article
- Spatial-temporal-demographic and virological changes of hand, foot and mouth disease incidence after vaccination in a vulnerable region of China.BMC public health · 2022Article
- Effects of temperature and PMEnvironmental science and pollution research international · 2022Article
- Prediction of hand, foot, and mouth disease epidemics in Japan using a long short-term memory approach.PloS one · 2022Article
- Effects of Meteorological Factors and Atmospheric Pollution on Hand, Foot, and Mouth Disease in Urumqi Region.Frontiers in public health · 2022Article
- Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China.International journal of environmental research and public health · 2021Article
- Associations between Meteorological Factors and Reported Mumps Cases from 1999 to 2020 in Japan.Epidemiologia (Basel, Switzerland) · 2021Article
- Spatial-temporal mapping and risk factors for hand foot and mouth disease in northwestern inland China.PLoS neglected tropical diseases · 2021Article
- Identifying pre-outbreak signals of hand, foot and mouth disease based on landscape dynamic network marker.BMC infectious diseases · 2021Article
- Article
- Short-term effects of meteorological factors, air pollution, and sunspot on childhood hand, foot, and mouth disease in Tianjin, China: a new time series regression, 2014-2018.Environmental science and pollution research international · 2020Article
- Using a Bayesian spatiotemporal model to identify the influencing factors and high-risk areas of hand, foot and mouth disease (HFMD) in Shenzhen.PLoS neglected tropical diseases · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to clarify the association between hand, foot, and mouth disease (HFMD) epidemics and meteorological conditions. We used HFMD surveillance data of all 47 prefectures in Japan from January 2000 to December 2015. Spectral analysis was performed using the maximum entropy method (MEM) for temperature-, relative humidity-, and total rainfall-dependent incidence data. Using MEM-estimated periods, long-term oscillatory trends were calculated using the least squares fitting (LSF) method. The temperature and relative humidity thresholds of HFMD data were estimated from the LSF curves. The average temperature data indicated a lower threshold at 12 °C and a higher threshold at 30 °C for risk of HFMD infection. Maximum and minimum temperature data indicated a lower threshold at 6 °C and a higher threshold at 35 °C, suggesting a need for HFMD control measures at temperatures between 6 and 35 °C. Based on our findings, we recommend the use of maximum and minimum temperatures rather than the average temperature, to estimate the temperature threshold of HFMD infections. The results obtained might aid in the prediction of epidemics and preparation for the effect of climatic changes on HFMD epidemiology.
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