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A Model Framework to Estimate Impact and Cost of Genetics-Based Sterile Insect Methods for Dengue Vector Control

Overview of attention for article published in PLOS ONE, October 2011
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Title
A Model Framework to Estimate Impact and Cost of Genetics-Based Sterile Insect Methods for Dengue Vector Control
Published in
PLOS ONE, October 2011
DOI 10.1371/journal.pone.0025384
Pubmed ID
Authors

Nina Alphey, Luke Alphey, Michael B. Bonsall

Abstract

Vector-borne diseases impose enormous health and economic burdens and additional methods to control vector populations are clearly needed. The Sterile Insect Technique (SIT) has been successful against agricultural pests, but is not in large-scale use for suppressing or eliminating mosquito populations. Genetic RIDL technology (Release of Insects carrying a Dominant Lethal) is a proposed modification that involves releasing insects that are homozygous for a repressible dominant lethal genetic construct rather than being sterilized by irradiation, and could potentially overcome some technical difficulties with the conventional SIT technology. Using the arboviral disease dengue as an example, we combine vector population dynamics and epidemiological models to explore the effect of a program of RIDL releases on disease transmission. We use these to derive a preliminary estimate of the potential cost-effectiveness of vector control by applying estimates of the costs of SIT. We predict that this genetic control strategy could eliminate dengue rapidly from a human community, and at lower expense (approximately US$ 2~30 per case averted) than the direct and indirect costs of disease (mean US$ 86-190 per case of dengue). The theoretical framework has wider potential use; by appropriately adapting or replacing each component of the framework (entomological, epidemiological, vector control bio-economics and health economics), it could be applied to other vector-borne diseases or vector control strategies and extended to include other health interventions.

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Geographical breakdown

Country Count As %
United Kingdom 4 2%
United States 4 2%
Brazil 2 <1%
Indonesia 2 <1%
Hong Kong 1 <1%
Australia 1 <1%
Portugal 1 <1%
India 1 <1%
French Polynesia 1 <1%
Other 2 <1%
Unknown 210 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 26%
Student > Ph. D. Student 37 16%
Student > Master 31 14%
Student > Bachelor 24 10%
Other 18 8%
Other 29 13%
Unknown 30 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 88 38%
Medicine and Dentistry 29 13%
Biochemistry, Genetics and Molecular Biology 19 8%
Environmental Science 13 6%
Social Sciences 11 5%
Other 32 14%
Unknown 37 16%