Bayesian joint spatiotemporal modelling of primary infection and reinfection of HFMD at county level in Jiangsu, China, 2009–2023

Over the past decade, multiple outbreaks of hand, foot, and mouth disease (HFMD) have occurred in East Asia, especially in China. It is crucial to understand the distribution pattern and risk factors of HFMD while also studying the corresponding characteristics of reinfections. This paper aims to jointly analyze the spatiotemporal distribution and influential factors of primary infection and reinfection of HFMD in Jiangsu province, China, under the Bayesian framework. Using county-level monthly HFMD counts from 2009 to 2023, we proposed four spatiotemporal hierarchical models with latent effects shared in the reinfection sub-model to evaluate the influence of air pollution, meteorological factors, and demographic characteristics on primary infection and reinfection of HFMD. The integrated nested Laplace approximation (INLA) approach estimated model parameters and quantified the spatial and temporal random effects. The optimal model with spatial, temporal, and spatiotemporal interaction effects indicated a significant positive influence of NO[Formula: see text], wind speed, relative humidity, and solar radiation, as well as a significant negative effect of PM[Formula: see text], O[Formula: see text], temperature above 27 °C, precipitation, and COVID-19, on both infections. Scattered status and critical primary infection have a significant positive effect on primary infection and reinfection. Positive sharing coefficients revealed similar spatiotemporal patterns of both types of infection. Beyond these fixed effects, non-linear analyses further highlighted comparable exposure-response patterns for primary infection and reinfection, with notable thresholds around 50-70 [Formula: see text]g/m[Formula: see text] for PM[Formula: see text], 90 [Formula: see text]g/m[Formula: see text] for O[Formula: see text], 80 [Formula: see text]g/m[Formula: see text] for NO[Formula: see text], 20 °C for temperature, and 55% for relative humidity. Our findings reveal distinct drivers of primary infection and reinfection but also similar spatiotemporal patterns, suggesting the need for both targeted protection of vulnerable groups and integrated surveillance strategies.

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Publication Details

Journal
BMC Public Health
Published
2025-10-28
DOI
https://doi.org/10.1186/s12889-025-24931-2
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00

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Bayesian joint spatiotemporal modelling of primary infection and reinfection of HFMD at county level in Jiangsu, China, 2009–2023

Chengxiu Ling, Changjun Bao, Kai You Wang, Liguo Zhu et al.
BMC Public Health
COVID-19 epidemiological studies
article

Bayesian joint spatiotemporal modelling of primary infection and reinfection of HFMD at county level in Jiangsu, China, 2009–2023

Chengxiu Ling, Changjun Bao, Kai You Wang, Liguo Zhu, Wendong Liu, Hongfei Zhu, Yifan Tang, Hong Ji, Weijia Wang, Ying Wang
article en

Abstract

Over the past decade, multiple outbreaks of hand, foot, and mouth disease (HFMD) have occurred in East Asia, especially in China. It is crucial to understand the distribution pattern and risk factors of HFMD while also studying the corresponding characteristics of reinfections. This paper aims to jointly analyze the spatiotemporal distribution and influential factors of primary infection and reinfection of HFMD in Jiangsu province, China, under the Bayesian framework. Using county-level monthly HFMD counts from 2009 to 2023, we proposed four spatiotemporal hierarchical models with latent effects shared in the reinfection sub-model to evaluate the influence of air pollution, meteorological factors, and demographic characteristics on primary infection and reinfection of HFMD. The integrated nested Laplace approximation (INLA) approach estimated model parameters and quantified the spatial and temporal random effects. The optimal model with spatial, temporal, and spatiotemporal interaction effects indicated a significant positive influence of NO[Formula: see text], wind speed, relative humidity, and solar radiation, as well as a significant negative effect of PM[Formula: see text], O[Formula: see text], temperature above 27 °C, precipitation, and COVID-19, on both infections. Scattered status and critical primary infection have a significant positive effect on primary infection and reinfection. Positive sharing coefficients revealed similar spatiotemporal patterns of both types of infection. Beyond these fixed effects, non-linear analyses further highlighted comparable exposure-response patterns for primary infection and reinfection, with notable thresholds around 50-70 [Formula: see text]g/m[Formula: see text] for PM[Formula: see text], 90 [Formula: see text]g/m[Formula: see text] for O[Formula: see text], 80 [Formula: see text]g/m[Formula: see text] for NO[Formula: see text], 20 °C for temperature, and 55% for relative humidity. Our findings reveal distinct drivers of primary infection and reinfection but also similar spatiotemporal patterns, suggesting the need for both targeted protection of vulnerable groups and integrated surveillance strategies.

BMC Public HealthVol. 25(1)
University of Liverpool (GB), Hochschule Bielefeld (DE), Fudan University (CN), Soochow University (CN), Shanghai Public Health Clinical Center (CN), Jiangsu Provincial Center for Disease Control and Prevention (CN), Xi’an Jiaotong-Liverpool University (CN), Nanjing Medical University (CN)
Government of Jiangsu Province
Openalex Percentile: Top 65%
COVID-19 epidemiological studies
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