Evidence map›Paper›PMID 42289705›Full record

ArticleTropical medicine and health2026

Modelling the impacts of meteorological factors on herpangina: a Bayesian spatiotemporal analysis.

Sophearen Ith, Shu Tamano, Yui Tomo, Fangyu Yan, Yu Takizawa, Kanako Otani, Taro Kamigaki, Motoi Suzuki, Daisuke Yoneoka

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In one paragraph

Article in Tropical medicine and health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Sophearen IthDepartment of Epidemiology, National Institute of Infectious Diseases, Japan Institute for Health Security, 1-23-1 Toyama, Shinjuku, Tokyo, 162-8640, Japan.
Shu TamanoDepartment of Epidemiology, National Institute of Infectious Diseases, Japan Institute for Health Security, 1-23-1 Toyama, Shinjuku, Tokyo, 162-8640, Japan.
Yui TomoDepartment of Epidemiology, National Institute of Infectious Diseases, Japan Institute for Health Security, 1-23-1 Toyama, Shinjuku, Tokyo, 162-8640, Japan.
Fangyu YanDepartment of Infectious Disease Surveillance, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo, 162-8640, Japan.
Yu TakizawaDepartment of Infectious Disease Surveillance, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo, 162-8640, Japan.
Kanako OtaniDepartment of Infectious Disease Surveillance, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo, 162-8640, Japan.
Taro KamigakiDepartment of Infectious Disease Surveillance, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo, 162-8640, Japan.
Motoi SuzukiDepartment of Epidemiology, National Institute of Infectious Diseases, Japan Institute for Health Security, 1-23-1 Toyama, Shinjuku, Tokyo, 162-8640, Japan.
Daisuke YoneokaDepartment of Epidemiology, National Institute of Infectious Diseases, Japan Institute for Health Security, 1-23-1 Toyama, Shinjuku, Tokyo, 162-8640, Japan. yoneoka.d@jihs.go.jp.

Funding

Japan Society for the Promotion of Science 24K23711
6 · The paper itself

Abstract

backgroundHerpangina is a common enteroviral illness in young children with recurrent seasonal surges. Although meteorological conditions influence transmission, evidence capturing non-linear and delayed effects across space remains limited. We aimed to quantify the exposure-lag-response associations of temperature, precipitation, and relative humidity with herpangina risk in Japan using a Bayesian spatiotemporal model.

methodsWeekly sentinel surveillance herpangina cases and meteorological variables were obtained for the 47 prefectures from January 2001 to December 2024. We applied a Bayesian hierarchical spatiotemporal model with distributed lag non-linear functions to estimate the associations between meteorological variables and herpangina risk (RR with 95% credible intervals, CrIs).

resultsThe analysis included 2,556,514 herpangina cases. Compared with the overall mean, weekly temperature and relative humidity showed inverted U-shaped associations, with peak risks at approximately 23 °C (RR = 1.57; 95%CrI 1.40-1.75) and 87% (RR = 1.50; 95% CrI 1.40-1.60), respectively. Compared with the minimum-risk level (44 mm), weekly total precipitation exhibited a U-shaped association, with increased risks at both low (2 mm; RR = 1.11; 95% CrI 1.03-1.19) and high levels (106 mm; RR = 1.08; 95% CrI 1.02-1.14).

conclusionsMeteorological conditions were associated with distinct non-linear and lagged effects on herpangina risk. The estimated exposure-lag-response functions provide empirically grounded risk ranges and lead times that can be integrated into routine surveillance to support timely risk communication, paediatric healthcare planning, and targeted prevention in childcare and school settings.

Indexed as

Bayesian spatiotemporal modellingDistributed lag non-linear modelsPrecipitationRelative humidityTemperature

Identifiers

PMID42289705
PMCPMC13487977

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