Spatiotemporal patterns of antimicrobial resistance in shared human-animal waterpoints in the Maasai Mara Ecosystem, Kenya
9 affiliations
- 1Department of Environmental Studies, Geography and Planning, Maasai Mara University, Narok, Kenya
- 2Kenya National Commission for UNESCO, Nairobi, Kenya
- 3Baruk Yadiym Ecosphere, Nairobi, Kenya
- 4Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
- 5World Health Organization, Kampala, Uganda
- 6Department of Animal and Wildlife Sciences, Midlands State University, Gweru, Zimbabwe
- 7Paul G. Allen School for Global Health, Washington State University, Washington, United States of America
- 8Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom
- 9Department of Forestry and Wildlife Management, Maasai Mara University, Narok, Kenya
Abstract
Antimicrobial resistance (AMR) presents an existential One Health threat. The spread of AMR in arid and semi-arid landscapes is modulated by ecological interactions and exacerbated by endemicity of livestock diseases and poor sanitation in shared human-animal systems leading to misuse of antibiotics. This study characterized the prevalence, resistance patterns, and spatiotemporal variations of AMR in surface water sources in the Maasai Mara Ecosystem (MME), a rapidly changing water-stressed socio-ecological landscape. Employing cross-sectional study design, water samples were collected from 28 water points between April 2024 and May 2025. Cultured Escherichia coli isolates were evaluated for resistance to eight antibiotics, following CLSI susceptibility testing protocols. AMR prevalence was calculated as proportions, with associations between sampling sites and seasons assessed using chi-square. Local clustering of resistant isolates was evaluated using spatial multinomial modelling, while cost-distance analysis against water points identified the proportion of the MME population with limited access to potable water. E. coli was detected in 92.9% water sources, with all isolates resistant to at least one antibiotic. High resistance rates were observed for Penicillin (100%), Amoxicillin (92.6%), Nitrofurantoin (78.6%), and Ceftazidime (52.9%). River samples exhibited higher resistance (51.4%) than open water pans (40.4%). AMR peaked during short-wet and short-dry seasons (51.3%; 51.5% respectively), with seasonal variations being significant (p = 0.04). Multi-drug-resistant isolates (MDR: resistant to ≥3 antibiotic classes) were detected across all seasons, peaking in the short-wet season. MDR relationship between water sources was insignificant across all sampling sites and seasons (p > 0.05). Spatial analysis (p > 0.05) identified two exploratory clusters: Cluster 1 near dense human areas (RR = 0.78) while Cluster 2 in human-livestock-wildlife zones (RR = 1.26). Cost-distance analysis (p < 0.05) revealed one-third of the MME population is at risk of AMR due to limited access to potable water. Our findings reveal widespread distribution of AMR isolates in shared waterpoints, necessitating targeted One Health Quadripartite interventions.
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BibTeX
@article{waswalaolewe2026spatiotemporal,
title = {{Spatiotemporal patterns of antimicrobial resistance in shared human-animal waterpoints in the Maasai Mara Ecosystem, Kenya}},
author = {Brian Marvis Waswala-Olewe and George Paul Omondi and Monica Adhiambo Olewe and Brian Njuguna and Yvonne Nyararai and Nyamai Mutono and Mwangi Thumbi and Paul W. Webala and Romulus Abila},
journal = {PLOS Global Public Health},
year = {2026},
month = oct,
doi = {10.1371/journal.pgph.0007393},
url = {https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0007393},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Spatiotemporal patterns of antimicrobial resistance in shared human-animal waterpoints in the Maasai Mara Ecosystem, Kenya
AU - Brian Marvis Waswala-Olewe
AU - George Paul Omondi
AU - Monica Adhiambo Olewe
AU - Brian Njuguna
AU - Yvonne Nyararai
AU - Nyamai Mutono
AU - Mwangi Thumbi
AU - Paul W. Webala
AU - Romulus Abila
PY - 2026
DA - 2026/10/07
JO - PLOS Global Public Health
DO - 10.1371/journal.pgph.0007393
UR - https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0007393
AB - Antimicrobial resistance (AMR) presents an existential One Health threat. The spread of AMR in arid and semi-arid landscapes is modulated by ecological interactions and exacerbated by endemicity of livestock diseases and poor sanitation in shared human-animal systems leading to misuse of antibiotics. This study characterized the prevalence, resistance patterns, and spatiotemporal variations of AMR in surface water sources in the Maasai Mara Ecosystem (MME), a rapidly changing water-stressed socio-ecological landscape. Employing cross-sectional study design, water samples were collected from 28 water points between April 2024 and May 2025. Cultured Escherichia coli isolates were evaluated for resistance to eight antibiotics, following CLSI susceptibility testing protocols. AMR prevalence was calculated as proportions, with associations between sampling sites and seasons assessed using chi-square. Local clustering of resistant isolates was evaluated using spatial multinomial modelling, while cost-distance analysis against water points identified the proportion of the MME population with limited access to potable water. E. coli was detected in 92.9% water sources, with all isolates resistant to at least one antibiotic. High resistance rates were observed for Penicillin (100%), Amoxicillin (92.6%), Nitrofurantoin (78.6%), and Ceftazidime (52.9%). River samples exhibited higher resistance (51.4%) than open water pans (40.4%). AMR peaked during short-wet and short-dry seasons (51.3%; 51.5% respectively), with seasonal variations being significant (p = 0.04). Multi-drug-resistant isolates (MDR: resistant to ≥3 antibiotic classes) were detected across all seasons, peaking in the short-wet season. MDR relationship between water sources was insignificant across all sampling sites and seasons (p > 0.05). Spatial analysis (p > 0.05) identified two exploratory clusters: Cluster 1 near dense human areas (RR = 0.78) while Cluster 2 in human-livestock-wildlife zones (RR = 1.26). Cost-distance analysis (p < 0.05) revealed one-third of the MME population is at risk of AMR due to limited access to potable water. Our findings reveal widespread distribution of AMR isolates in shared waterpoints, necessitating targeted One Health Quadripartite interventions.
SN - 2767-3375
ER -