One health surveillance: linking human and animal rabies surveillance data in Kenya

IntroductionRabies poses a significant public health and economic challenge in Kenya. The Kenya rabies elimination strategy identifies surveillance as a key pillar to achieve the targets of ending human deaths from rabies by 2030. Here we investigated the utility of the national human and animal rab...

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Main Authors: Samuel Kahariri, Lian F. Thomas, Bernard Bett, Marianne Mureithi, Brian Njuguna, Nyamai Mutono, Thumbi Mwangi
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Public Health
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Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1594162/full
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author Samuel Kahariri
Samuel Kahariri
Samuel Kahariri
Samuel Kahariri
Lian F. Thomas
Lian F. Thomas
Bernard Bett
Marianne Mureithi
Brian Njuguna
Nyamai Mutono
Nyamai Mutono
Nyamai Mutono
Thumbi Mwangi
Thumbi Mwangi
Thumbi Mwangi
Thumbi Mwangi
author_facet Samuel Kahariri
Samuel Kahariri
Samuel Kahariri
Samuel Kahariri
Lian F. Thomas
Lian F. Thomas
Bernard Bett
Marianne Mureithi
Brian Njuguna
Nyamai Mutono
Nyamai Mutono
Nyamai Mutono
Thumbi Mwangi
Thumbi Mwangi
Thumbi Mwangi
Thumbi Mwangi
author_sort Samuel Kahariri
collection DOAJ
description IntroductionRabies poses a significant public health and economic challenge in Kenya. The Kenya rabies elimination strategy identifies surveillance as a key pillar to achieve the targets of ending human deaths from rabies by 2030. Here we investigated the utility of the national human and animal rabies surveillance data to provide robust surveillance data to guide the Kenya rabies elimination program.MethodsWe conducted a retrospective analysis of the official rabies data obtained from the national human and animal health surveillance systems between 2017 and 2023. We obtained data on bites, cases, and deaths in dogs and humans due to rabies. We estimated incidences and tested the relationships between rabies variables in human and dogs as a proxy for robust data availability.ResultsOn average, there were 162 cases and 84 deaths in dogs, while in humans, there were 53 cases and 6 deaths. We found positive correlations between dog bites and cases of dog rabies [RR = 1.33, 95% credible interval (CI): 1.16, 1.54], deaths and rabies cases in dogs (RR = 1.09, 95% CI: 1.05, 1.14) and death cases and dog bites (RR = 1.46, 95% CI: 1.06, 1.98). However, relationships between rabies cases and dog bites in humans were not statistically significant (RR = 1.00, 95% CI: 0.98, 1.03), whereas rabies cases in dogs and humans were negatively correlated (RR = 0.82, 95% CI: 0.68, 0.94).DiscussionThe findings indicate that Kenya’s rabies surveillance system effectively captures trends in dog rabies but has gaps in human rabies case reporting. The weak relationship between rabies cases and dog bites in humans and the negative correlation between rabies cases in dogs and humans point to potential underreporting of human cases, that could be possibly driven by misdiagnosis or limited access to healthcare, or effective post-exposure treatment.ConclusionUnderstanding these relationships is critical for improving the surveillance systems that can effectively support the rabies elimination program.
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spelling doaj-art-a26334d00ec24c3884d42f0b5d82586c2025-08-20T03:20:14ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-06-011310.3389/fpubh.2025.15941621594162One health surveillance: linking human and animal rabies surveillance data in KenyaSamuel Kahariri0Samuel Kahariri1Samuel Kahariri2Samuel Kahariri3Lian F. Thomas4Lian F. Thomas5Bernard Bett6Marianne Mureithi7Brian Njuguna8Nyamai Mutono9Nyamai Mutono10Nyamai Mutono11Thumbi Mwangi12Thumbi Mwangi13Thumbi Mwangi14Thumbi Mwangi15Directorate of Livestock Policy, Research and Regulations, Nairobi, KenyaInternational Livestock Research Institute, Nairobi, KenyaCentre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, KenyaFaculty of Health Sciences, Department of Medical Microbiology and Immunology, University of Nairobi, Nairobi, KenyaInternational Livestock Research Institute, Nairobi, KenyaRoyal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United KingdomInternational Livestock Research Institute, Nairobi, KenyaFaculty of Health Sciences, Department of Medical Microbiology and Immunology, University of Nairobi, Nairobi, KenyaCentre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, KenyaCentre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, KenyaPaul G. Allen School for Global Health, Washington State University, Pullman, WA, United StatesFeed the Future Innovation Lab for Animal Health, Washington State University, Pullman, WA, United StatesCentre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, KenyaPaul G. Allen School for Global Health, Washington State University, Pullman, WA, United StatesFeed the Future Innovation Lab for Animal Health, Washington State University, Pullman, WA, United StatesInstitute of Immunology and Infection Research, University of Edinburgh, Edinburg, United KingdomIntroductionRabies poses a significant public health and economic challenge in Kenya. The Kenya rabies elimination strategy identifies surveillance as a key pillar to achieve the targets of ending human deaths from rabies by 2030. Here we investigated the utility of the national human and animal rabies surveillance data to provide robust surveillance data to guide the Kenya rabies elimination program.MethodsWe conducted a retrospective analysis of the official rabies data obtained from the national human and animal health surveillance systems between 2017 and 2023. We obtained data on bites, cases, and deaths in dogs and humans due to rabies. We estimated incidences and tested the relationships between rabies variables in human and dogs as a proxy for robust data availability.ResultsOn average, there were 162 cases and 84 deaths in dogs, while in humans, there were 53 cases and 6 deaths. We found positive correlations between dog bites and cases of dog rabies [RR = 1.33, 95% credible interval (CI): 1.16, 1.54], deaths and rabies cases in dogs (RR = 1.09, 95% CI: 1.05, 1.14) and death cases and dog bites (RR = 1.46, 95% CI: 1.06, 1.98). However, relationships between rabies cases and dog bites in humans were not statistically significant (RR = 1.00, 95% CI: 0.98, 1.03), whereas rabies cases in dogs and humans were negatively correlated (RR = 0.82, 95% CI: 0.68, 0.94).DiscussionThe findings indicate that Kenya’s rabies surveillance system effectively captures trends in dog rabies but has gaps in human rabies case reporting. The weak relationship between rabies cases and dog bites in humans and the negative correlation between rabies cases in dogs and humans point to potential underreporting of human cases, that could be possibly driven by misdiagnosis or limited access to healthcare, or effective post-exposure treatment.ConclusionUnderstanding these relationships is critical for improving the surveillance systems that can effectively support the rabies elimination program.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1594162/fullrabiessurveillanceone healthcorrelationBayesianzoonotic
spellingShingle Samuel Kahariri
Samuel Kahariri
Samuel Kahariri
Samuel Kahariri
Lian F. Thomas
Lian F. Thomas
Bernard Bett
Marianne Mureithi
Brian Njuguna
Nyamai Mutono
Nyamai Mutono
Nyamai Mutono
Thumbi Mwangi
Thumbi Mwangi
Thumbi Mwangi
Thumbi Mwangi
One health surveillance: linking human and animal rabies surveillance data in Kenya
Frontiers in Public Health
rabies
surveillance
one health
correlation
Bayesian
zoonotic
title One health surveillance: linking human and animal rabies surveillance data in Kenya
title_full One health surveillance: linking human and animal rabies surveillance data in Kenya
title_fullStr One health surveillance: linking human and animal rabies surveillance data in Kenya
title_full_unstemmed One health surveillance: linking human and animal rabies surveillance data in Kenya
title_short One health surveillance: linking human and animal rabies surveillance data in Kenya
title_sort one health surveillance linking human and animal rabies surveillance data in kenya
topic rabies
surveillance
one health
correlation
Bayesian
zoonotic
url https://www.frontiersin.org/articles/10.3389/fpubh.2025.1594162/full
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