Evidence map›Paper›PMID 42108242›Full record

ArticleScientific reports2026

Modelling the impact of climate on cholera: a case study of Kolkata.

Debbie Shackleton, Shanta Dutta, Suman Kanungo, Alok Deb, Theo Economou

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Debbie ShackletonCentre for Water Systems, University of Exeter, Exeter, United Kingdom. dmshackleton@gmail.com.
Shanta DuttaICMR - National Institute for Research in Bacterial Infections, Kolkata, India.
Suman KanungoICMR - National Institute for Research in Bacterial Infections, Kolkata, India.
Alok DebICMR - National Institute for Research in Bacterial Infections, Kolkata, India.
Theo EconomouCentre for Water Systems, University of Exeter, Exeter, United Kingdom.

Funding

EPSRC EP/L016214/1
6 · The paper itself

Abstract

Cholera is highly climate sensitive, however previous attempts to model its future under climate change have been limited to statistical analyses. Mechanistic models are an essential addition because they permit a deeper understanding of the complex feedback loops involved in infectious disease transmission, allowing for better modelling of potential scenarios such as interventions or changes in pathogen dynamics. We compare four mathematical models with differing assumptions of climate sensitivity and fit them to a cholera dataset from Kolkata, India using MCMC. We then use bias-corrected climate projections of temperature and rainfall from 10 independent global climate models to produce climate-based cholera projections for the period 2080-2099. Using both temperature and rainfall as inputs, the best performing model recreates seasonal patterns highly effectively. Future projections suggest an average increase in cholera cases ranging from 81% - 150% due to climate change by 2080-2099 with earlier peaks in the infection cycle likely due to heightened transmission rates earlier in the year. Sensitivity analysis reveals that uncertainties in parameters related to the contact rate and water dynamics have the greatest impact on model projections, suggesting that these factors are critical for refining future predictions. While our mechanistic model demonstrates the potential to project cholera dynamics under future climate scenarios, projections remain sensitive to key knowledge gaps including epidemiological parameters and effects of temperature on bacterial growth. Addressing these limitations through improved environmental observations and more detailed process representation will be essential for refining future climate-cholera projections and informing long-term control strategies.

Indexed as

CholeraClimateClimate ChangeModels, TheoreticalHumansIndiaRainSeasonsTemperature

Identifiers

PMID42108242
PMCPMC13346884

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.