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Spatial modelling and prediction of Loa loa risk: decision making under uncertainty.

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Spatial modelling and prediction of Loa loa risk: decision making under uncertainty. / Diggle, Peter J.; Thomson, M. C.; Christensen, O. F. et al.
In: Annals of Tropical Medicine and Parasitology, Vol. 101, No. 6, 2007, p. 499-509.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Diggle, PJ, Thomson, MC, Christensen, OF, Rowlingson, B, Obsomer, V, Gardon, J, Wanji, S, Takougang, I, Enyong, P, Kamgno, J, Remme, H, Boussinesq, M & Molyneux, DH 2007, 'Spatial modelling and prediction of Loa loa risk: decision making under uncertainty.', Annals of Tropical Medicine and Parasitology, vol. 101, no. 6, pp. 499-509. https://doi.org/10.1179/136485907X229121

APA

Diggle, P. J., Thomson, M. C., Christensen, O. F., Rowlingson, B., Obsomer, V., Gardon, J., Wanji, S., Takougang, I., Enyong, P., Kamgno, J., Remme, H., Boussinesq, M., & Molyneux, D. H. (2007). Spatial modelling and prediction of Loa loa risk: decision making under uncertainty. Annals of Tropical Medicine and Parasitology, 101(6), 499-509. https://doi.org/10.1179/136485907X229121

Vancouver

Diggle PJ, Thomson MC, Christensen OF, Rowlingson B, Obsomer V, Gardon J et al. Spatial modelling and prediction of Loa loa risk: decision making under uncertainty. Annals of Tropical Medicine and Parasitology. 2007;101(6):499-509. doi: 10.1179/136485907X229121

Author

Diggle, Peter J. ; Thomson, M. C. ; Christensen, O. F. et al. / Spatial modelling and prediction of Loa loa risk: decision making under uncertainty. In: Annals of Tropical Medicine and Parasitology. 2007 ; Vol. 101, No. 6. pp. 499-509.

Bibtex

@article{680e5490dead4895a13d264b37c91856,
title = "Spatial modelling and prediction of Loa loa risk: decision making under uncertainty.",
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.",
author = "Diggle, {Peter J.} and Thomson, {M. C.} and Christensen, {O. F.} and B. Rowlingson and V. Obsomer and J. Gardon and S. Wanji and I. Takougang and P. Enyong and J. Kamgno and H. Remme and M. Boussinesq and Molyneux, {D. H.}",
year = "2007",
doi = "10.1179/136485907X229121",
language = "English",
volume = "101",
pages = "499--509",
journal = "Annals of Tropical Medicine and Parasitology",
issn = "1364-8594",
publisher = "Maney Publishing",
number = "6",

}

RIS

TY - JOUR

T1 - Spatial modelling and prediction of Loa loa risk: decision making under uncertainty.

AU - Diggle, Peter J.

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, H.

AU - Boussinesq, M.

AU - Molyneux, D. H.

PY - 2007

Y1 - 2007

N2 - 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.

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.

U2 - 10.1179/136485907X229121

DO - 10.1179/136485907X229121

M3 - Journal article

VL - 101

SP - 499

EP - 509

JO - Annals of Tropical Medicine and Parasitology

JF - Annals of Tropical Medicine and Parasitology

SN - 1364-8594

IS - 6

ER -