Predicted spatial distribution of the primary Lassa virus reservoir, the multimammate mouse, in Africa
4 affiliations
- 1Department of Pathobiology and Integrative Biomedical Sciences, College of Veterinary Medicine, University of Missouri
- 2Department of Ecology and Evolutionary Biology and Biodiversity Institute, University of Kansas
- 3Department of Public Health, College of Health Sciences, University of Missouri
- 4MU Institute for Data Science and Informatics, University of Missouri
Abstract
Objective: This study predicts the potential spatial distribution of the multimammate mouse ( Mastomys natalensis ), the primary host of Lassa virus, a major public health concern across West Africa.
Methods: Correlative maximum entropy models were constructed with occurrence records of M. natalensis from Global Biodiversity Information Facility, using long-term bioclimatic variables at ~1 km resolution as predictors. Candidate models were evaluated and best models were selected based on statistical significance, predictive ability, and model fitting and complexity. Models were projected to the African continent.
Results: Median predictions from the best-supported models indicated extensive areas of moderate to high suitability across sub-Saharan Africa, with suitability concentrated within the tropical and subtropical belts of West, Central, and East Africa. Suitability declined sharply across arid regions, particularly the Sahara and parts of the Horn of Africa. Within Nigeria, a focal area of the study, the predicted suitability was broadly high across southern and central regions, with a gradual decline toward Sahel-adjacent northern areas. Sub-national projections for Lagos, Oyo, Edo, Kano, and the Federal Capital Territory revealed spatial heterogeneity in suitability, consistent with underlying climatic gradients in temperature and precipitation that shape habitat conditions for M. natalensis .
Conclusion: These findings provide a spatial framework for prioritizing rodent surveillance and supporting targeted Lassa fever preparedness and control strategies.
Related
- Probabilistic uncertainty in virtual spatial transcriptomics from histology is largely redundant with the predicted mean
- Alien Vascular Plants of Kazakhstan: The First National Checklist and Spatial Distribution Patterns
- Distribution Patterns and Intraspecific Spatial Associations of Different Size Classes in Krascheninnikovia ceratoides (L.) Gueldenst. Populations Within the Tibetan Antelope Breeding Grounds of the West Kunlun Mountains
- Spatial proteomic profiling of cardiac stromal populations and microenvironments in systemic sclerosis-associated primary myocardial involvement
- Spatial distribution of blood-brain barrier membrane proteins is controlled by sorting motifs and physiological signals in vivo
BibTeX
@article{lateef2026predicted,
title = {{Predicted spatial distribution of the primary Lassa virus reservoir, the multimammate mouse, in Africa}},
author = {Adeola Mariam Lateef and Marlon E. Cobos and Victor Ibukun Agbajelola and Ram K. Raghavan},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1916488},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1916488/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Predicted spatial distribution of the primary Lassa virus reservoir, the multimammate mouse, in Africa
AU - Adeola Mariam Lateef
AU - Marlon E. Cobos
AU - Victor Ibukun Agbajelola
AU - Ram K. Raghavan
PY - 2026
DA - 2026/10/13
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1916488
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1916488/full
AB - Objective: This study predicts the potential spatial distribution of the multimammate mouse ( Mastomys natalensis ), the primary host of Lassa virus, a major public health concern across West Africa. Methods: Correlative maximum entropy models were constructed with occurrence records of M. natalensis from Global Biodiversity Information Facility, using long-term bioclimatic variables at ~1 km resolution as predictors. Candidate models were evaluated and best models were selected based on statistical significance, predictive ability, and model fitting and complexity. Models were projected to the African continent. Results: Median predictions from the best-supported models indicated extensive areas of moderate to high suitability across sub-Saharan Africa, with suitability concentrated within the tropical and subtropical belts of West, Central, and East Africa. Suitability declined sharply across arid regions, particularly the Sahara and parts of the Horn of Africa. Within Nigeria, a focal area of the study, the predicted suitability was broadly high across southern and central regions, with a gradual decline toward Sahel-adjacent northern areas. Sub-national projections for Lagos, Oyo, Edo, Kano, and the Federal Capital Territory revealed spatial heterogeneity in suitability, consistent with underlying climatic gradients in temperature and precipitation that shape habitat conditions for M. natalensis . Conclusion: These findings provide a spatial framework for prioritizing rodent surveillance and supporting targeted Lassa fever preparedness and control strategies.
SN - 2296-2565
ER -