Eco-epidemiological dynamics in populations with demographic and spatial structure

Abstract

The epidemiology of an infectious disease is inherently intertwined with the spatial and demographic structure of the population of individuals it infects. Disease spread is facilitated by the contact of individuals and the way in which individuals contact one another is heavily influenced by space and demography. For instance, a person is often more likely to contact another individual from their own household than from their community. Alternatively, individuals of similar age groups and social backgrounds may share a greater number of contacts than contrasting groups.

In this thesis, we focus on investigating the epidemiology at a household or similar scale. In human populations, transmission within the household is typically stronger than in the wider community since household contacts can be more frequent. Consequently, it can be desirable to aim control strategies at the household unit. Household modelling frameworks can be utilised to describe the household infection status over time as a continuous time Markov process, which can be written as a system of ordinary differential equations (the Master Equation). In most cases we consider a metapopulation of households connected via the movement of individuals. We use Markov and branching process theory to construct key model quantities such as the household basic reproduction number and the probability of a large outbreak in the total population and supplement our analytical work with stochastic simulation.

While directly transmitted infections are shaped by human-to-human interactions, vector-borne diseases introduce further complexity in the contact structure, as they involve interactions between hosts and vectors governed by spatial and behavioural patterns. Further, the vector population dynamics themselves are often influenced by human activity at a household scale. For example, the Aedes aegypti mosquito, is known to favour urban environments, living in and around the same dwellings as the people they bite. Similarly, Ixodes scapularis ticks and their hosts forage in and around residential lawns near woodland areas. Therefore, their population dynamics unfold in these smaller, spatially separated populations, and will be subject to stochastic effects. In this thesis, we develop and subsequently analyse modelling frameworks for vector population dynamics which account for such effects. We consider vector control strategies at a household or residential patch scale and use a range of analytical and numerical methods, such as ordinary differential equations, Markov process theory, Gillespie's stochastic simulation algorithm and hybrid modelling to capture the vector ecological dynamics.

Date of Award	25 Mar 2026
Original language	English
Awarding Institution	University of Bath
Supervisor	Ben Adams (Supervisor) & Sarah Penington (Supervisor)