Spatial modelling and the prediction of Loa loa risk: Decision making under uncertainty

Peter Diggle; M. C. Thomson; O. F. Christensen; B. Rowlingson; V. Obsomer; J. Gardon; S. Wanji; I. Takougang; P. Enyong; J. Kamgno; J. H. Remme; M. Boussinesq; David Molyneux

doi:10.1179/136485913x13789813917463

Spatial modelling and the prediction of Loa loa risk: Decision making under uncertainty

Peter Diggle, M. C. Thomson, O. F. Christensen, B. Rowlingson, V. Obsomer, J. Gardon, S. Wanji, I. Takougang, P. Enyong, J. Kamgno, J. H. Remme, M. Boussinesq, David Molyneux

Tropical Disease Biology

Research output: Contribution to journal › Article › peer-review

89 Citations (Scopus)

Abstract

Health decision-makers working in Africa often need to act for millions of people over large geographical areas on little and uncertain information. Spatial statistical modelling and Bayesian inference have now been used to quantify the uncertainty in the predictions of a regional, environmental risk map for Loa loa ( a map that is currently being used as an essential decision tool by the African Programme for Onchocerciasis Control). The methodology allows the expression of the probability that, given the data, a particular location does or does not exceed a predefined high-risk threshold for which a change in strategy for the delivery of the antihelmintic ivermectin is required.

Original language	English
Pages (from-to)	499-509
Number of pages	11
Journal	Pathogens and Global Health
Volume	101
Issue number	6
DOIs	https://doi.org/10.1179/136485913x13789813917463
Publication status	Published - 1 Sept 2007

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Diggle, P., Thomson, M. C., Christensen, O. F., Rowlingson, B., Obsomer, V., Gardon, J., Wanji, S., Takougang, I., Enyong, P., Kamgno, J., Remme, J. H., Boussinesq, M., & Molyneux, D. (2007). Spatial modelling and the prediction of Loa loa risk: Decision making under uncertainty. Pathogens and Global Health, 101(6), 499-509. https://doi.org/10.1179/136485913x13789813917463

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AU - Thomson, M. C.

AU - Christensen, O. F.

AU - Rowlingson, B.

AU - Obsomer, V.

AU - Gardon, J.

AU - Wanji, S.

AU - Takougang, I.

AU - Enyong, P.

AU - Kamgno, J.

AU - Remme, J. H.

AU - Boussinesq, M.

AU - Molyneux, David

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AB - Health decision-makers working in Africa often need to act for millions of people over large geographical areas on little and uncertain information. Spatial statistical modelling and Bayesian inference have now been used to quantify the uncertainty in the predictions of a regional, environmental risk map for Loa loa ( a map that is currently being used as an essential decision tool by the African Programme for Onchocerciasis Control). The methodology allows the expression of the probability that, given the data, a particular location does or does not exceed a predefined high-risk threshold for which a change in strategy for the delivery of the antihelmintic ivermectin is required.

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DO - 10.1179/136485913x13789813917463

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SP - 499

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JO - Pathogens and Global Health

JF - Pathogens and Global Health

IS - 6

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Spatial modelling and the prediction of Loa loa risk: Decision making under uncertainty

Abstract

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