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Review
. 2024 May 5;12(1):e46.
doi: 10.22037/aaem.v12i1.2284. eCollection 2024.

Infectious Diarrhea Risks as a Public Health Emergency in Floods; a Systematic Review and Meta-Analysis

Mohammad Shirmohammadi Yazdi  1 , Mohammad Afshar Ardalan  2   3 , Mohsen Hosseini  4 , Mojtaba Yousefi Zoshk  5 , Zahra Hami  6 , Reza Heidari  1   7 , Reza Mosaed  8   9 , Mohsen Chamanara  6   9
Affiliations
Review

Infectious Diarrhea Risks as a Public Health Emergency in Floods; a Systematic Review and Meta-Analysis

Mohammad Shirmohammadi Yazdi et al. Arch Acad Emerg Med. .

Abstract

Introduction: Infectious diarrhea, a significant global health challenge, is exacerbated by flooding, a consequence of climate change and environmental disruption. This comprehensive study aims to quantify the association between flooding events and the incidence of infectious diarrhea, considering diverse demographic, environmental, and pathogen-specific factors.

Methods: In this systematic review and meta-analysis, adhering to PROSPERO protocol (CRD42024498899), we evaluated observational studies from January 2000 to December 2023. The analysis incorporated global data from PubMed, Scopus, Embase, Web of Science, and ProQuest, focusing on the relative risk (RR) of diarrhea post-flooding. The study encompassed diverse variables like age, sex, pathogen type, environmental context, and statistical modeling approaches.

Results: The meta-analysis, involving 42 high-quality studies, revealed a substantial increase (RR = 1.40, 95% CI [1.29-1.52]) in the incidence of diarrhea following floods. Notably, bacterial and parasitic diarrheas demonstrated higher RRs (1.82 and 1.35, respectively) compared to viral etiologies (RR = 1.15). A significant sex disparity was observed, with women exhibiting a higher susceptibility (RR = 1.55) than men (RR = 1.35). Adults (over 15 years) faced a greater risk than younger individuals, highlighting age-dependent vulnerability.

Conclusion: This extensive analysis confirms a significant correlation between flood events and increased infectious diarrhea risk, varying across pathogens and demographic groups. The findings highlight an urgent need for tailored public health interventions in flood-prone areas, focusing on enhanced sanitation, disease surveillance, and targeted education to mitigate this elevated risk. Our study underscores the critical importance of integrating flood-related health risks into global public health planning and climate change adaptation strategies.

Keywords: Climate change; Diarrhea; Disease transmission; Floods; Public health; Risk factor; infectious.

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Conflict of interest statement

The authors declare that they have no competing interests

Figures

Figure 1
Figure 1
Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) flow diagram for the selection of studies on flood-related infectious diarrhea.
Figure 2
Figure 2
Funnel plot for relative risk (RR) of A) overall diarrhea B) pathogenic and non-pathogenic diarrhea C) bacterial diarrhea D) viral diarrhea E) sex-specific diarrhea and F) age-specific diarrhea.
Figure 3
Figure 3
Forest plot depicting the relationship between flood exposure and risk ratio of infectious diarrhea, calculated using a random effects model. CI: confidence interval.
Figure 4
Figure 4
Forest plot depicting risk ratios for infectious versus non-infectious diarrhea in flood scenarios, analyzed using a random effects model. CI: confidence interval.
Figure 5
Figure 5
A forest plot representation of the sex-specific risk ratios for infectious diarrhea associated with flooding, evaluated with a random effects model. CI: confidence interval.
Figure 6
Figure 6
A forest plot presenting age-specific risk ratios for diarrhea in the aftermath of flooding, as determined through a random effects model. CI: confidence interval.
Figure 7
Figure 7
A forest plot showing the comparative risk ratios for various bacterial diarrheal infections following flooding, calculated through a random effects model. CI: confidence interval.
Figure 8
Figure 8
A forest plot detailing risk ratios for viral pathogens causing diarrhea after flooding, synthesized via a random effects model. CI: confidence interval.
Figure 9
Figure 9
A forest plot summarizing the risk ratios for post-flood diarrheal illness caused by parasites, compiled using a random effects model. CI: confidence interval.
Figure S1
Figure S1
Forest plot for the sensitivity analysis
See this image and copyright information in PMC

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References

    1. Angmor GDM. Climate Change Flooding And Diseases In Sub Sahara Africa: Trends And Adaptions Strategies (A Review) Korean J Physiol Pharmacol. 2024;28(1):8–21.
    1. Qian W, Lin X, Zhu Y, Xu Y, Fu J. Climatic regime shift and decadal anomalous events in China. Climatic Change. 2007;84:167–89.
    1. Montgomery R. The Bangladesh floods of 1984 in historical context. Disasters. 1985;9(3):163–72.
    1. Tang CS-k. Trajectory of traumatic stress symptoms in the aftermath of extreme natural disaster: A study of adult Thai survivors of the 2004 Southeast Asian earthquake and tsunami. J Nerv Ment Dis. 2007;195(1):54–9. - PubMed
    1. Brown L, Murray V. Examining the relationship between infectious diseases and flooding in Europe: A systematic literature review and summary of possible public health interventions. Disaster Health. 2013;1(2):117–27. - PMC - PubMed

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