Sub-national estimates of visceral leishmaniasis and optimisation of geographical accessibility to treatment centres in Kenya
Abstract
Background: Visceral leishmaniasis (VL) remains a major public health challenge in Kenya, disproportionately affecting populations with limited access to timely diagnosis and treatment. National case totals mask local heterogeneity in risk and access. Here we estimate sub-national VL incidence, identify its determinants and optimise geographical placement of treatment centres.
Methods: We analysed nine years (October 2016-September 2025) of ward-level VL surveillance data from health facilities, with WorldPop population denominators. Bayesian small-area models related case occurrence and counts to environmental, socioeconomic and accessibility covariates. Travel time to the 46 existing treatment centres was computed over a motorised friction surface, and additional sites prioritised to maximise population coverage.
Results: We record 11,985 cases, an estimated incidence of 10 per 100,000 population per year, with marked seasonality and epidemic periods. Burden is highly focal: five northern counties account for 86% of cases, with further clustering at sub-county and ward levels and predicted incidence exceeding 100 per 100,000 person-years in several wards in Turkana and West Pokot. Higher temperature, poverty, and poor housing are associated with greater probability of occurrence and higher case counts; higher precipitation is inversely associated. Only 45% of the population in need can reach a treatment centre within 120 minutes of motorised travel. Five optimally sited additions increase this 120-minute coverage to 76%, with diminishing gains from further expansion.
Conclusion: Integrating small-area disease modelling with geospatial accessibility analysis reveals hidden inequities in VL burden and supports equitable, efficient deployment of treatment services towards elimination.
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BibTeX
@article{mutono2026subnational,
title = {{Sub-national estimates of visceral leishmaniasis and optimisation of geographical accessibility to treatment centres in Kenya}},
author = {Nyamai Mutono and Brian Njuguna and Daniel Mwiti and Paul Kibati and George P. Omondi and Wyckliff Omondi and Joy K. Nthiwa and Duncan Ochol and Lenson Kariuki and Michael Ofire and Joseph Oundo and Loise Ndung’u and Gerald Gakuo and Jafar Oyugi and Francis Lowana and Emmanuel Okunga and Daniel Langat and Josphat Martin Muchangi and Kennedy Senagi and Penina Safari and Maureen Nzilani and James Gathirwa and Daniel Masiga and Damaris Matoke-Muhia and SM Thumbi},
journal = {Communications Medicine},
year = {2026},
month = oct,
doi = {10.1038/s43856-026-01958-z},
url = {https://www.nature.com/articles/s43856-026-01958-z},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Sub-national estimates of visceral leishmaniasis and optimisation of geographical accessibility to treatment centres in Kenya
AU - Nyamai Mutono
AU - Brian Njuguna
AU - Daniel Mwiti
AU - Paul Kibati
AU - George P. Omondi
AU - Wyckliff Omondi
AU - Joy K. Nthiwa
AU - Duncan Ochol
AU - Lenson Kariuki
AU - Michael Ofire
AU - Joseph Oundo
AU - Loise Ndung’u
AU - Gerald Gakuo
AU - Jafar Oyugi
AU - Francis Lowana
AU - Emmanuel Okunga
AU - Daniel Langat
AU - Josphat Martin Muchangi
AU - Kennedy Senagi
AU - Penina Safari
AU - Maureen Nzilani
AU - James Gathirwa
AU - Daniel Masiga
AU - Damaris Matoke-Muhia
AU - SM Thumbi
PY - 2026
DA - 2026/10/09
JO - Communications Medicine
DO - 10.1038/s43856-026-01958-z
UR - https://www.nature.com/articles/s43856-026-01958-z
AB - Background: Visceral leishmaniasis (VL) remains a major public health challenge in Kenya, disproportionately affecting populations with limited access to timely diagnosis and treatment. National case totals mask local heterogeneity in risk and access. Here we estimate sub-national VL incidence, identify its determinants and optimise geographical placement of treatment centres. Methods: We analysed nine years (October 2016-September 2025) of ward-level VL surveillance data from health facilities, with WorldPop population denominators. Bayesian small-area models related case occurrence and counts to environmental, socioeconomic and accessibility covariates. Travel time to the 46 existing treatment centres was computed over a motorised friction surface, and additional sites prioritised to maximise population coverage. Results: We record 11,985 cases, an estimated incidence of 10 per 100,000 population per year, with marked seasonality and epidemic periods. Burden is highly focal: five northern counties account for 86% of cases, with further clustering at sub-county and ward levels and predicted incidence exceeding 100 per 100,000 person-years in several wards in Turkana and West Pokot. Higher temperature, poverty, and poor housing are associated with greater probability of occurrence and higher case counts; higher precipitation is inversely associated. Only 45% of the population in need can reach a treatment centre within 120 minutes of motorised travel. Five optimally sited additions increase this 120-minute coverage to 76%, with diminishing gains from further expansion. Conclusion: Integrating small-area disease modelling with geospatial accessibility analysis reveals hidden inequities in VL burden and supports equitable, efficient deployment of treatment services towards elimination.
SN - 2730-664X
ER -