A stochastic household model for vector-borne diseases

TL;DR

This paper presents a stochastic household model for vector-borne diseases like Zika and dengue, capturing local vector dynamics and host mixing to analyze outbreak potential and control strategies.

Contribution

It introduces a novel stochastic model combining household vector dynamics with host mixing, enabling efficient calculation of key epidemiological metrics.

Findings

Model accurately estimates reproductive numbers and outbreak probabilities.

Spraying reduces vector populations effectively.

Social distancing impacts transmission dynamics significantly.

Abstract

We introduce a stochastic household model for vector-borne diseases, in particular as relevant to prominent vectors belonging to the Aedes genus and hence the Zika, chikungunya, and dengue viruses. In this model, vectors remain local to each household, while hosts mix for a proportion of their time in their household and the remaining proportion in the population at random. This is approximated with a two-type branching process, allowing us to efficiently calculate a number of useful epidemiological characteristics, such as reproductive numbers, early growth rates and household-type proportions, offspring distributions, probabilities of a major outbreak, and within-household final size distributions. We compare control interventions of spraying -- reducing the number of vectors in each household -- and social-distancing -- having individuals spend more time at home -- in terms of these characteristics.