When vector abundance constrains vector-borne transmission: inside epidemic dynamics within a prescribed population

Abstract

The global burden of vector-borne diseases continues to rise, presenting escalating challenges to public health and agricultural systems. Their expanding geographic range and associated impacts underscore the need for tools to project disease dynamics and evaluate interventions. Mechanistic compartmental host--vector models provide such a framework by explicitly representing transmission processes. However, while these models often couple vector population dynamics with infection spread, the inherent complexity of vector demographic processes calls for a more modular approach. In this study, we consider the setting in which the total vector abundance is an externally-prescribed input to a general vector-mediated transmission model. Our objectives are threefold: (i) to provide theoretical guarantees for ensuring consistency between the prescribed total vector abundance and the dynamics of the model compartments, (ii) to characterize model properties related to the local reproduction index (informing extinction or emergence near the time of introduction) and the inter-seasonal propagation, and (iii) to derive insights for diseases transmitted by Aedes albopictus in mainland France. We apply this framework by feeding the epidemiological model with vector-abundance data obtained either from entomological surveillance systems or from an external detailed population dynamic model. Moreover, epidemiological national surveillance data are used to estimate the transmission parameter. Based on this, we derive conditions for emergence and extinction, and show how the extent of the epidemic depends on introduction timing, transmission rate, and susceptible population density. Taken together, these results highlight the value of generating and leveraging entomological surveillance data as well as their model-based counterparts when observations are unavailable (which is particularly relevant in the context of global warming and for the evaluation of vector-control strategies). Overall, we establish a refined framework integrating such data or forecast into compartmental models, with strong potential for a wide range of applications in animal, human or plant health.