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

  • 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 Hilario Nascimento Saldiva
  • , Shuang Zhou
  • Zhihu Xu, Ke Ju, Yuxi Zhang, Yuming Guo*, Shanshan Li*
*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.MethodsIn 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.Findings27 million infectious disease hospitalisation records from 709 communities were included in the analysis. Hospitalisation risks of all-cause infectious, foodborne and waterborne diseases, airborne diseases, skin and mucous-membrane infections, and sexually transmitted infections increased for up to 26 weeks following flood exposure. For each 1-week flood exposure, the associated RR (mean across 26 weeks) after flood exposure was 1·006 (95% CI 1·002–1·009) for all-cause infectious diseases, 1·008 (1·003–1·012) for foodborne and waterborne diseases, 1·004 (1·001–1·008) for airborne diseases, 1·010 (1·005–1·015) for skin and mucous-membrane infections, and 1·032 (1·025–1·039) for sexually transmitted infections. Changes in RRs were observed between 2000–09 and 2010–19 across countries. In 2010–19, the excess rate of all-cause infectious disease hospitalisations was the highest in Australia, which was 150·0 (95% empirical CI 115·8–183·2) admissions per million person-years.InterpretationFlood exposure was associated with increased hospitalisation risks for foodborne and waterborne diseases, airborne diseases, skin and mucous-membrane infections, and sexually transmitted infections, lasting for up to 26 weeks after flooding. With the projected increases in severity, duration, and frequency of floods under climate change, greater efforts are warranted to review and improve the current adaptation strategies, disaster response protocols, health system resilience, and disease surveillance systems.FundingAustralian Research Council, Australian National Health and Medical Research Council, National Research Council of Thailand.

Original languageEnglish
Article number101411
Pages (from-to)101411
JournalThe Lancet Planetary Health
Volume10
Issue number1
DOIs
StatePublished - Jan 2026

Bibliographical note

Publisher Copyright:
© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Humans
  • Floods/statistics & numerical data
  • Hospitalization/statistics & numerical data
  • Communicable Diseases/epidemiology
  • Australia/epidemiology
  • New Zealand/epidemiology
  • Chile/epidemiology
  • Canada/epidemiology
  • Brazil/epidemiology
  • Thailand/epidemiology

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