Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning

Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning · SciRah

^aDepartment of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, Washington, United States of America
^bInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
^cGlobalHealth Infectious Disease, University of South Florida, Tampa, Florida, United States of America
^dLondon Centre for Neglected Tropical Disease Research (LCNTDR), Imperial College London, London, United Kingdom
^eMRC Centre for Global Infectious Disease Analysis (MRC-GIDA), Imperial College London, London, United Kingdom
^fNeglected Tropical Diseases Support Center, Task Force for Global Health, Decatur, Georgia, United States of America
^gPopulation Health Sciences, King's College London, London, England
^hCentre of Excellence for Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
ⁱDepartment of Global Health, Stellenbosch University, Cape Town, South Africa
^jDepartment of Dermatology, Mayo Clinic, Rochester, Minnesota, United States of America
^kEndocrinology and Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Iran
^lInfectious and Tropical Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
^mAustralian Center for Precision Health, University of South Australia, Adelaide, South Australia, Australia
ⁿDepartment of Epidemiology, Jimma University, Jimma, Ethiopia
^oDepartment of Epidemiology and Biostatistics, University of Gondar, Gondar, Ethiopia
^pClinical Epidemiology Center, Department of Veterans Affairs, St Louis, Montana, United States of America
^qJohn T. Milliken Department of Internal Medicine, Washington University in St. Louis, St. Louis, Montana, United States of America
^rImam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
^sHealth Information Management and Technology Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
^tHealth Economics Department, Iran University of Medical Sciences, Tehran, Iran
^uHealth Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
^vCardiology Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
^wRazi Vaccine and Serum Research Institute, Agricultural Research, Education, and Extension Organization (AREEO), Tehran, Iran
^xResearch Center for Evidence Based Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
^yDepartment of Public Health, Debre Berhan University, Debre Berhan, Ethiopia
^zDepartment of Parasitology, Iranshahr University of Medical Sciences, Iranshahr, Iran
^aaDepartment of Parasitology, Mazandaran University of Medical Sciences, Sari, Iran
^abCenter for International Health, Ludwig Maximilians University, Munich, Germany
^acDepartment of Sociology and Social Work, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
^adDepartment of Ophthalmology, University of California San Francisco, San Francisco, California, United States of America
^aeDepartment of Statistics and Econometrics, Bucharest University of Economic Studies, Bucharest, Romania
^afSchool of Business, University of Leicester, Leicester, United Kingdom
^agDepartment of Health Policy Planning and Management, University of Health and Allied Sciences, Ho, Ghana
✉Corresponding author

Abstract

Recent evidence suggests that, in some foci, elimination of onchocerciasis from Africa may be feasible with mass drug administration (MDA) of ivermectin. To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. In order to classify IUs that include locations that are environmentally suitable, we used receiver operating characteristic (ROC) analysis to identify an optimal threshold for suitability concordant with locations where onchocerciasis has been previously detected. This threshold value was then used to classify IUs (more suitable or less suitable) based on the location within the IU with the largest mean prediction. Mean estimates of environmental suitability suggest large areas across West and Central Africa, as well as focal areas of East Africa, are suitable for onchocerciasis transmission, consistent with the presence of current control and elimination of transmission efforts. The ROC analysis identified a mean environmental suitability index of 0·71 as a threshold to classify based on the location with the largest mean prediction within the IU. Of the IUs considered for mapping surveys, 50·2% exceed this threshold for suitability in at least one 5 × 5-km location. The formidable scale of data collection required to map onchocerciasis endemicity across the African continent presents an opportunity to use spatial data to identify areas likely to be suitable for onchocerciasis transmission. National onchocerciasis elimination programmes may wish to consider prioritising these IUs for mapping surveys as human resources, laboratory capacity, and programmatic schedules may constrain survey implementation, and possibly delaying MDA initiation in areas that would ultimately qualify.

TL;DREstimates of environmental suitability suggest large areas across West and Central Africa, as well as focal areas of East Africa, are suitable for onchocerciasis transmission, consistent with the presence of current control and elimination of transmission efforts. (Semantic Scholar)

Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning

Abstract

Plain-language summary

Discussion