Bayesian Joint Spatiotemporal Modelling of Primary and Recurrent Infections of HFMD at County Level in Jiangsu, China, 2009–2023

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 recurrent infections. This paper aims to jointly analyze the spatiotemporal distribution and influential factors of primary and recurrent 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 HFMD on primary and recurrent HFMD infections. The integrated nested Laplace approximation (INLA) approach estimates model parameters and quantifies the spatial and temporal random effects. The optimal model with spatial, temporal, and spatiotemporal interaction effect indicates a significant positive influence of NO2, wind speed, relative humidity, and solar radiation, as well as a significant negative effect of PM2.5, O3, temperature above 27 °C, precipitation and COVID-19, on both infections. Scattered status and critical primary infection significantly positively affect both primary and recurrent incidence. Positive sharing coefficients reveal similar spatiotemporal patterns of primary and recurrent incidence. Non-linear analysis further demonstrates the influence of air pollution and meteorological factors. Our findings deepen the understanding of primary and recurrent HFMD infections and are expected to contribute to developing more effective disease control guidelines. Competing Interest Statement The authors have declared no competing interest. Funding Statement This research was supported by the Jiangsu Province 333 project, National Key R&D Program of China (2024YFC2310403), and the Top Talent Awards Project Fund (RDF-TP-0023, RDF-TP-0030) and Post-graduate Research Fund (PGRS2112022) at Xi'an Jiaotong-Liverpool University. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of Xi'an Jiaotong-Liverpool University gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present study are available upon reasonable request to the authors and with permission of the Jiangsu Provincial Center for Disease Control and Prevention.