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Omitting age-dependent mosquito mortality in malaria models underestimates the effectiveness of insecticide-treated nets

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Abstract

Mathematical models of vector-borne infections, including malaria, often assume age-independent mortality rates of vectors, despite evidence that many insects senesce. In this study we present survival data on insecticide-resistant Anopheles gambiae s.l. from experiments in Côte d’Ivoire. We fit a constant mortality function and two age-dependent functions (logistic and Gompertz) to the data from mosquitoes exposed (treated) and not exposed (control) to insecticide-treated nets (ITNs), to establish biologically realistic survival functions. This enables us to explore the effects of insecticide exposure on mosquito mortality rates, and the extent to which insecticide resistance might impact the effectiveness of ITNs. We investigate this by calculating the expected number of infectious bites a mosquito will take in its lifetime, and by extension the vectorial capacity. Our results show that the predicted vectorial capacity is substantially lower in mosquitoes exposed to ITNs, despite the mosquitoes in the experiment being highly insecticide-resistant. The more realistic age-dependent functions provide a better fit to the experimental data compared to a constant mortality function and, hence, influence the predicted impact of ITNs on malaria transmission potential. In models with age-independent mortality, there is a great reduction for the vectorial capacity under exposure compared to no exposure. However, the two age-dependent functions predicted an even larger reduction due to exposure, highlighting the impact of incorporating age in the mortality rates. These results further show that multiple exposures to ITNs had a considerable effect on the vectorial capacity. Overall, the study highlights the importance of including age dependency in mathematical models of vector-borne disease transmission and in fully understanding the impact of interventions.

Item Type: Journal Article
Subjects: Q Science > QR Microbiology
R Medicine > RA Public aspects of medicine
S Agriculture > SB Plant culture
Divisions: Faculty of Science, Engineering and Medicine > Science > Mathematics
Faculty of Science, Engineering and Medicine > Science > Statistics
Library of Congress Subject Headings (LCSH): Malaria -- Mathematical models, Malaria -- Prevention, Malaria -- Research, Insecticides, Mosquitoes -- Insecticide resistance
Journal or Publication Title: PLoS Computational Biology
Publisher: Public Library of Science
ISSN: 1553-7358
Official Date: 19 September 2022
Dates:
Date
Event
19 September 2022
Published
8 August 2022
Accepted
Volume: 18
Number: 9
Article Number: e1009540
DOI: 10.1371/journal.pcbi.1009540
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons open licence)
RIOXX Funder/Project Grant:
Project/Grant ID
RIOXX Funder Name
Funder ID
EP/S022244/1
[EPSRC] Engineering and Physical Sciences Research Council
OPP1131603
Bill and Melinda Gates Foundation
Persistent URL: https://wrap.warwick.ac.uk/169615/

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