Risk, burden, and trend of infectious disease hospitalisations associated with floods: a multicountry, time-series study

作者：Zhengyu Yang, Wenzhong Huang, Joanne E McKenzie, Rongbin Xu, Pei Yu, Gongbo Chen, Wenhua Yu, Yao Wu, Yanming Liu, Bo Wen, Simon Hales, Eric Lavigne, Tingting Ye, Yiwen Zhang, Micheline de Sousa Zanotti Stagliorio Coelho, Patricia Matus, Kraichat Tantrakarnapa, Wissanupong Kliengchuay, Paulo Hilário Nascimento Saldiva, Shuang Zhou, Zhihu Xu, Ke Ju, Yuxi Zhang, Yuming Guo, Shanshan Li · 发表于：The Lancet Planetary Health · 年份：2026 · DOI：10.1016/j.lanplh.2025.101411 · 被引用次数：5 · 研究领域：Disaster Response and Management、Flood Risk Assessment and Management、Climate Change and Health Impacts

BACKGROUND: Infectious disease outbreak is one of the most concerning issues in the aftermath of floods. However, knowledge gaps exist in the risk, burden, and trend of infectious disease hospitalisation associated with floods. Therefore, we aimed to quantify the risks, burden, and temporal changes of infectious disease hospitalisations associated with flood exposure during 2000-19. METHODS: In this multicountry, time-series study, hospitalisation data for all communities in Australia, Brazil, Canada, Chile, New Zealand, and Thailand from Jan 1, 2000, to Dec 31, 2019, were collected from local authorities of each country. We retrieved flood events data from the Dartmouth Flood Observatory. Meteorological, population, and gross domestic product data were collected from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5, Landscan, and a previous study. Associations between flood exposure and weekly hospitalisation risks were estimated using a two-stage analytical approach. To examine temporal changes in the associations and the corresponding burden, we estimated relative risks (RRs) and excess rates of hospitalisations from infectious diseases that were attributable to floods for the communities in each country in two periods (2000-09 and 2010-19) using the two-stage analytical approach. FINDINGS: 27 million infectious disease hospitalisation records from 709 communities were included in the analysis. Hospitalisation risks of all-cause infectious, foodb...