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An Eco-Evolutionary Modelling Framework for Mosquito Host Specialisation

Aug 2026 · bioRxiv · 0 citations · 34 references
Biology

TL;DR

An eco-evolutionary modelling framework that links genetically determined mosquito traits with spatially structured host environments and yields testable predictions regarding when specialisation emerges, persists, or collapses, with direct implications for predicting vector-borne disease risk in changing environments.

Abstract

Host preference varies widely across mosquitoes, with many species feeding opportunistically on diverse vertebrate hosts, while others show strong fidelity to specific hosts. Anthropophilia, the behavioural preference for feeding on humans, is a defining characteristic of some mosquito species responsible for the transmission of major human diseases, including malaria, dengue, and yellow fever. The evolution of anthropophilia therefore has profound epidemiological implications because increased human biting elevates vectorial capacity and disease transmission potential. However, the ecological and evolutionary mechanisms driving this extreme specialisation has not yet been fully elucidated and remain difficult to unify across laboratory and field studies. Here we present an eco-evolutionary modelling framework that links genetically determined mosquito traits with spatially structured host environments. Our framework integrates innate olfactory sensitivity, blood meal-derived fitness benefits, and spatio-temporal host accessibility. Two complementary indices are introduced: a local specialisation index, capturing short-term ecological feeding strategies, and a co-evolutionary index, capturing long-term genetic coupling between host detection and resource utilisation. Our results demonstrate that host specialisation is not a default evolutionary outcome but an environmentally gated process, which is favoured in resource-poor or temporally varying habitats and strongly filtered by seasonality. The framework yields testable predictions regarding when specialisation emerges, persists, or collapses, with direct implications for predicting vector-borne disease risk in changing environments.

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