Rainfall and Human Leptospirosis Incidence: A Systematic Review of Ecological Temporal Studies

<ns5:p>Background Leptospirosis is a zoonotic disease influenced by climatic and environmental conditions. Rainfall is an important environmental factor in leptospirosis transmission; however, the strength, temporal patterns, and characteristics of this association vary across studies. This systematic review aimed to synthesize evidence on the association between rainfall and human leptospirosis occurrence and to identify the temporal characteristics of this relationship. Methods This systematic review was conducted in accordance with the PRISMA 2020 guidelines, and the protocol was registered in PROSPERO (CRD420261330699). Literature searches were performed in PubMed, Scopus, ScienceDirect, and Google Scholar. Studies evaluating the association between rainfall and human leptospirosis occurrence were included. Risk of bias was assessed using the Navigation Guide Systematic Review Methodology. Due to heterogeneity across studies, findings were synthesized narratively without meta-analysis. Results Twenty-two studies met the inclusion criteria. Synthesized evidence indicated that increased rainfall was generally associated with increased leptospirosis occurrence across diverse geographical and epidemiological settings. Positive associations were reported for total rainfall, extreme rainfall, cumulative rainfall, rainfall anomalies, and wetter-than-normal hydrometeorological conditions. Temporal lag patterns between rainfall exposure and leptospirosis occurrence ranged from several weeks to several months. Risk-of-bias assessment identified confounding as the most frequent source of bias. Conclusions Rainfall appears to be an important environmental factor associated with leptospirosis occurrence. This relationship is influenced by rainfall characteristics, temporal dynamics, and local contextual factors. Consideration of rainfall indicators and lag patterns may support the development of leptospirosis surveillance and early warning systems.</ns5:p>