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

P. J. 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, D. H. Molyneux

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

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 pre-defined high-risk threshold for which a change in strategy for the delivery of the antihelmintic ivermectin is required.

Original languageEnglish (US)
Pages (from-to)499-509
Number of pages11
JournalAnnals of Tropical Medicine and Parasitology
Volume101
Issue number6
DOIs
StatePublished - Sep 2007
Externally publishedYes

ASJC Scopus subject areas

  • Parasitology
  • Infectious Diseases
  • Immunology

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