Evidence map›Paper›PMID 40126047›Full record

ArticleTransactions of the Royal Society of Tropical Medicine and Hygiene2025

Spatio-temporal pattern and risk factors associated with cholera outbreaks in selected high-risk areas of Kenya.

Lydia M Mageto, Nyamai Mutono, Gabriel Aboge, Peter Gathura, Emmanuel Okunga, Annastacia Muange, Cecilia Kathure Mbae, Samuel M Thumbi, Samuel Kariuki

Abstract read
In one paragraph

Article in Transactions of the Royal Society of Tropical Medicine and Hygiene, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Recent epidemiological and management approaches for cholera in India.Proceedings (Baylor University. Medical Center) · 2026
    Review
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

9 authors.

Lydia M MagetoDepartment of Public Health, Pharmacology and Toxicology, Faculty of Veterinary Medicine, University of Nairobi, P.O. Box 29053, 00625 Nairobi, Kenya.ORCID 0000-0002-7076-3674
Nyamai MutonoCentre for Epidemiological Modelling and Analysis, University of Nairobi, P.O. Box 19676-00202 Nairobi, Kenya.
Gabriel AbogeDepartment of Public Health, Pharmacology and Toxicology, Faculty of Veterinary Medicine, University of Nairobi, P.O. Box 29053, 00625 Nairobi, Kenya.
Peter GathuraDepartment of Public Health, Pharmacology and Toxicology, Faculty of Veterinary Medicine, University of Nairobi, P.O. Box 29053, 00625 Nairobi, Kenya.
Emmanuel OkungaDivision of Disease Surveillance and Response, Ministry of Health, Kenya P.O. Box 30016-00100 Nairobi, Kenya.
Annastacia MuangeDivision of Disease Surveillance and Response, Ministry of Health, Kenya P.O. Box 30016-00100 Nairobi, Kenya.
Cecilia Kathure MbaeCentre for Microbiology Research, Kenya Medical Research Institute, P.O. Box 54840-0020, Nairobi, Kenya.
Samuel M ThumbiCentre for Epidemiological Modelling and Analysis, University of Nairobi, P.O. Box 19676-00202 Nairobi, Kenya.
Samuel KariukiCentre for Microbiology Research, Kenya Medical Research Institute, P.O. Box 54840-0020, Nairobi, Kenya.

Funding

Zoonotic and Emerging Infectious Diseases Training ProgramD43TW011519 · FIC · WASHINGTON STATE UNIVERSITY · PI Walter Godfrey Jaoko, Thumbi Mwangi · 2020 to 2026
$1.2M
FIC NIH HHS D43 TW011519Foreign, Commonwealth and Development Office 215675/Z/19/ZInstitute of Allergy and Infectious DiseasesNIH HHS D43TW011519WellcomeWellcome Trust
6 · The paper itself

Abstract

backgroundCholera is a public health challenge in Kenya. This study aimed at identifying the spatio-temporal pattern of cholera and its associated risk factors in high-risk areas to optimize resource use for targeted control.

methodsThe study was conducted in Mukuru, an informal settlement, Dadaab refugee camp and counties bordering Lake Victoria. Cholera line list data from 32 subcounties (2013-2022) was sourced from Kenya's Ministry of Health. Population and water, sanitation and hygiene data came from the 2019 census. Space-time scan statistic (SaTScan) were used to carry out spatio-temporal analysis and a zero-inflated negative binomial regression model evaluated cholera risk factors.

resultsA total of 7316 cholera cases were reported across 22 (69%) subcounties, the highest numbers in 2015, 2016 and 2022 affecting 21, 12 and 3 subcounties, respectively, and none in 2014. Five high-risk space-time clusters encompassing 15 subcounties were identified, with Dadaab and Fafi showing persistent outbreaks. Improved sanitation was the only variable that suggested significant protective effects to cholera control (relative risk 0.9445, p=0.001).

conclusionsDadaab and Fafi subcounties were extremely high-risk and improved sanitation significantly reduced cholera outbreaks. These data inform cholera intervention policies in vulnerable regions.

Indexed as

CholeraDisease OutbreaksSanitationHumansHygieneKenyaRisk FactorsSpatio-Temporal AnalysischoleraKenyapublic healthspatial analysis

Identifiers

PMID40126047
PMCPMC12212228

What OpenQuestion holds

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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.