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Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors

The relative risk of disease transmission caused by the potential release of transgenic vectors, such as through sterile insect technique or gene drive systems, is assessed with comparison with wild-type vectors. The probabilistic risk framework is demonstrated with an assessment of the relative ris...

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Autores principales: Hosack, Geoffrey R., Ickowicz, Adrien, Hayes, Keith R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074930/
https://www.ncbi.nlm.nih.gov/pubmed/33959322
http://dx.doi.org/10.1098/rsos.201525
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author Hosack, Geoffrey R.
Ickowicz, Adrien
Hayes, Keith R.
author_facet Hosack, Geoffrey R.
Ickowicz, Adrien
Hayes, Keith R.
author_sort Hosack, Geoffrey R.
collection PubMed
description The relative risk of disease transmission caused by the potential release of transgenic vectors, such as through sterile insect technique or gene drive systems, is assessed with comparison with wild-type vectors. The probabilistic risk framework is demonstrated with an assessment of the relative risk of lymphatic filariasis, malaria and o'nyong'nyong arbovirus transmission by mosquito vectors to human hosts given a released transgenic strain of Anopheles coluzzii carrying a dominant sterile male gene construct. Harm is quantified by a logarithmic loss function that depends on the causal risk ratio, which is a quotient of basic reproduction numbers derived from mathematical models of disease transmission. The basic reproduction numbers are predicted to depend on the number of generations in an insectary colony and the number of backcrosses between the transgenic and wild-type lineages. Analogous causal risk ratios for short-term exposure to a single cohort release are also derived. These causal risk ratios were parametrized by probabilistic elicitations, and updated with experimental data for adult vector mortality. For the wild-type, high numbers of insectary generations were predicted to reduce the number of infectious human cases compared with uncolonized wild-type. Transgenic strains were predicted to produce fewer infectious cases compared with the uncolonized wild-type.
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spelling pubmed-80749302021-05-05 Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors Hosack, Geoffrey R. Ickowicz, Adrien Hayes, Keith R. R Soc Open Sci Mathematics The relative risk of disease transmission caused by the potential release of transgenic vectors, such as through sterile insect technique or gene drive systems, is assessed with comparison with wild-type vectors. The probabilistic risk framework is demonstrated with an assessment of the relative risk of lymphatic filariasis, malaria and o'nyong'nyong arbovirus transmission by mosquito vectors to human hosts given a released transgenic strain of Anopheles coluzzii carrying a dominant sterile male gene construct. Harm is quantified by a logarithmic loss function that depends on the causal risk ratio, which is a quotient of basic reproduction numbers derived from mathematical models of disease transmission. The basic reproduction numbers are predicted to depend on the number of generations in an insectary colony and the number of backcrosses between the transgenic and wild-type lineages. Analogous causal risk ratios for short-term exposure to a single cohort release are also derived. These causal risk ratios were parametrized by probabilistic elicitations, and updated with experimental data for adult vector mortality. For the wild-type, high numbers of insectary generations were predicted to reduce the number of infectious human cases compared with uncolonized wild-type. Transgenic strains were predicted to produce fewer infectious cases compared with the uncolonized wild-type. The Royal Society 2021-03-03 /pmc/articles/PMC8074930/ /pubmed/33959322 http://dx.doi.org/10.1098/rsos.201525 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Mathematics
Hosack, Geoffrey R.
Ickowicz, Adrien
Hayes, Keith R.
Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
title Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
title_full Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
title_fullStr Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
title_full_unstemmed Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
title_short Quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
title_sort quantifying the risk of vector-borne disease transmission attributable to genetically modified vectors
topic Mathematics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074930/
https://www.ncbi.nlm.nih.gov/pubmed/33959322
http://dx.doi.org/10.1098/rsos.201525
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