Mapping suitability for Buruli ulcer at fine spatial scales across Africa: a modelling study [article]

Hope Simpson, Earnest Njih Tabah, Richard O Richard Phillips, Michael Frimpong, Issaka Maman, Joseph Timothy, Paul Saunderson, Rachel L Pullan, Jorge Cano
2020 biorxiv/medrxiv   pre-print
Buruli ulcer (BU) is a disabling and stigmatising neglected tropical disease (NTD). Its distribution and burden are unknown because of underdiagnosis and underreporting. It is caused by Mycobacterium ulcerans, an environmental pathogen whose environmental niche and transmission routes are not fully understood. Active BU case searches can limit morbidity by identifying cases and linking them to treatment, but these are mostly restricted to well-known endemic areas. A better understanding of
more » ... onmental suitability for environmental reservoirs of M. ulcerans and BU disease would advance understanding of the ecology and burden of BU, and could inform targeted surveillance. Methodology/Principal Findings We used previously compiled point-level datasets of BU and M. ulcerans occurrence, evidence for BU occurrence within national and sub-national areas, and diverse environmental datasets. We fitted relationships between BU and M. ulcerans occurrence and environmental predictors by applying regression and machine learning based algorithms, combined in an ensemble model to characterise the optimal ecological niche for the disease and bacterium across Africa at a resolution of 5km x 5km. Climate and atmospheric variables were the strongest predictors of both distributions, while indicators of human disturbance including damming and deforestation, drove local variation in suitability. We identified patchy foci of suitability throughout West and Central Africa, including areas with no previous evidence of the disease. Predicted suitability for M. ulcerans was wider but overlapping with that of BU. The estimated population living in areas predicted suitable for the bacterium and disease was 29.1 million. Conclusions/Significance These maps could be used to inform burden estimations and case searches which would generate a more complete understanding of the spatial distribution of BU in Africa, and may guide control programmes to identify cases beyond the well-known endemic areas.
doi:10.1101/2020.04.20.20072348 fatcat:pkdpqzx6anacdbsgmix44reqkq