ArticlePloS one2012
An age-structured extension to the vectorial capacity model.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimizing malaria vector control in the Greater Mekong Subregion: a systematic review and mathematical modelling study to identify desirable intervention characteristics.Parasites & vectors · 2024Pooled it
- Estimating the effects of temperature on transmission of the human malaria parasite, Plasmodium falciparum.Nature communications · 2024Article
- Omitting age-dependent mosquito mortality in malaria models underestimates the effectiveness of insecticide-treated nets.PLoS computational biology · 2022Article
- A New Test of a Theory about Old Mosquitoes.Trends in parasitology · 2021Review
- Modeling schistosomiasis transmission: the importance of snail population structure.Parasites & vectors · 2021Article
- The Role of Vector Trait Variation in Vector-Borne Disease Dynamics.Frontiers in ecology and evolution · 2020Article
- Age-structured vectorial capacity reveals timing, not magnitude of within-mosquito dynamics is critical for arbovirus fitness assessment.Parasites & vectors · 2020Article
- Article
- Quantifying the effects of temperature on mosquito and parasite traits that determine the transmission potential of human malaria.PLoS biology · 2017Article
- A dynamic model for estimating adult female mortality from ovarian dissection data for the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe.PLoS neglected tropical diseases · 2017Article
- Abscisic acid induces a transient shift in signaling that enhances NF-κB-mediated parasite killing in the midgut of Anopheles stephensi without reducing lifespan or fecundity.Parasites & vectors · 2017Article
- Transmission dynamics: critical questions and challenges.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Review
- Projection of Climate Change Influences on U.S. West Nile Virus Vectors.Earth interactions · 2015Article
- Mortality estimates from ovarian age distributions of the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe suggest the need for new analytical approaches.Bulletin of entomological research · 2015Article
- Chikungunya viral fitness measures within the vector and subsequent transmission potential.PloS one · 2014Article
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6 authors.
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Abstract
backgroundVectorial capacity and the basic reproductive number (R(0)) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention. METHODOLOGY/PRINCIPAL
findingsBased on survival analysis we derived new equations for vectorial capacity and R(0) that are valid for any pattern of age-dependent (or age-independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies. CONCLUSIONS/SIGNIFICANCE: Accounting for age-dependent vector mortality in estimates of vectorial capacity and R(0) was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R(0) is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R(0) ∼ 1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field.
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