ArticleJournal of the Royal Society, Interface2023
Towards a leptospirosis early warning system in northeastern Argentina.
Article in Journal of the Royal Society, Interface, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- [Floods in Rio Grande do Sul State, Brazil, in 2024 and their effects on the epidemiology of leptospirosis].Cadernos de saude publica · 2026Article
- Modelling the impact of climate and the environment on the spatiotemporal dynamics of Lyme borreliosis in Germany.EBioMedicine · 2025Article
- Spatio-temporal risk prediction of leptospirosis: A machine-learning-based approach.PLoS neglected tropical diseases · 2025Article
- Towards a leptospirosis early warning system in northeastern Argentina.Journal of the Royal Society, Interface · 2023Article
- Quantifying the relationship between climatic indicators and leptospirosis incidence in Fiji: A modelling study.PLOS global public health · 2023Article
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 4 countries.
Funding
Abstract
Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.