Modelling the effects of adult emergence on the surveillance and age distribution of medically important mosquitoes
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Entomological surveillance is an important component of mosquito-borne disease control. Mosquito abundance, infection prevalence and the entomological inoculation rate are the most widely reported entomological metrics, although these data are notoriously noisy and difficult to interpret. For many infections, only older mosquitoes are infectious, which is why, in part, vector control tools that reduce mosquito life expectancy have been so successful. The age structure of wild mosquitoes has been proposed as a metric to assess the effectiveness of interventions that kill adult mosquitoes, and age grading tools are becoming increasingly advanced. Mosquito populations show seasonal dynamics with temporal fluctuations. How seasonal changes in adult mosquito emergence and vector control could affect the mosquito age distribution or other important metrics is unclear. We develop stochastic mathematical models of mosquito population dynamics to show how variability in mosquito emergence causes substantial heterogeneity in the mosquito age distribution, with low frequency, positively autocorrelated changes in emergence being the most important driver of this variability. Fitting a population model to mosquito abundance data collected in experimental hut trials indicates these dynamics are likely to exist in wild Anopheles gambiae populations. Incorporating age structuring into an established compartmental model of mosquito dynamics and vector control, indicates that the use of mosquito age as a metric to assess the efficacy of vector-control tools will require an understanding of underlying variability in mosquito ages, with the mean age and other entomological metrics affected by short-term and seasonal fluctuations in mosquito emergence.
Editor(s)
Pepin, Kimberly M
Date Issued
2025-08-18
Date Acceptance
2025-07-24
Citation
PLoS Computational Biology, 2025, 21 (8)
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Journal / Book Title
PLoS Computational Biology
Volume
21
Issue
8
Copyright Statement
© 2025 Stopard et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40825044
PII: PCOMPBIOL-D-25-00674
Subjects
ABUNDANCE
Biochemical Research Methods
Biochemistry & Molecular Biology
COLOR
DYNAMICS
Life Sciences & Biomedicine
MALARIA TRANSMISSION
Mathematical & Computational Biology
PARAMETERS
PLASMODIUM-FALCIPARUM
RATES
Science & Technology
SEASONAL-VARIATIONS
Publication Status
Published
Coverage Spatial
United States
Article Number
e1013035
Date Publish Online
2025-08-18