Role of vector phenotypic plasticity in disease transmission as illustrated by the spread of dengue virus by Aedes albopictus

Brass, Dominic P.; Cobbold, Christina A.; Purse, Bethan V. ORCID: https://orcid.org/0000-0001-5140-2710; Ewing, David A.; Callaghan, Amanda; White, Steven M. ORCID: https://orcid.org/0000-0002-3192-9969. 2024 Role of vector phenotypic plasticity in disease transmission as illustrated by the spread of dengue virus by Aedes albopictus. Nature Communications, 15, 7823. 22, pp. https://doi.org/10.1038/s41467-024-52144-5

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Official URL: http://dx.doi.org/10.1038/s41467-024-52144-5

Abstract/Summary

The incidence of vector-borne disease is on the rise globally, with burdens increasing in endemic countries and outbreaks occurring in new locations. Effective mitigation and intervention strategies require models that accurately predict both spatial and temporal changes in disease dynamics, but this remains challenging due to the complex and interactive relationships between environmental variation and the vector traits that govern the transmission of vector-borne diseases. Predictions of disease risk in the literature typically assume that vector traits vary instantaneously and independently of population density, and therefore do not capture the delayed response of these same traits to past biotic and abiotic environments. We argue here that to produce accurate predictions of disease risk it is necessary to account for environmentally driven and delayed instances of phenotypic plasticity. To show this, we develop a stage and phenotypically structured model for the invasive mosquito vector, Aedes albopictus, and dengue, the second most prevalent human vector-borne disease worldwide. We find that environmental variation drives a dynamic phenotypic structure in the mosquito population, which accurately predicts global patterns of mosquito trait-abundance dynamics. In turn, this interacts with disease transmission to capture historic dengue outbreaks. By comparing the model to a suite of simpler models, we reveal that it is the delayed phenotypic structure that is critical for accurate prediction. Consequently, the incorporation of vector trait relationships into transmission models is critical to improvement of early warning systems that inform mitigation and control strategies.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1038/s41467-024-52144-5
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-)
ISSN:	2041-1723
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	applied mathematics, ecological epidemiology, ecological modelling, population dynamics
NORA Subject Terms:	Ecology and Environment Health Mathematics
Related URLs:	Dataset Dataset Dataset
Date made live:	17 Sep 2024 09:04 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/538029

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1038/s41467-024-52144-5

UKCEH and CEH Sections/Science Areas:

Biodiversity (Science Area 2017-)

ISSN:

2041-1723

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

applied mathematics, ecological epidemiology, ecological modelling, population dynamics