More entities, more problems? Individual-based models for infectious disease transmission

As is evident from the current COVID-19 pandemic, infectious diseases pose a significant threat to humanity. As such, the prevention and control of communicable diseases is an important topic for research. As it is not feasible to answer all questions related to this topic through empirical research, it is sometimes necessary to use mathematical models. Individual-based models explicitly track each individual in a population, and can thus simultaneously represent multiple sources of heterogeneity. However, individual-based models are often computationally intensive, and verification, validation, parameterization and calibration can be challenging. The aim of this thesis is to use individual-based models to answer research questions that require the representation of different sources of heterogeneity in a population. This is often important for diseases to which a large fraction of the population is immune, such as measles in Belgium. However, in many regions with a similarly high level of immunity, outbreaks still occur. A possible explanation is the accumulation of pockets of susceptible individuals. Using an individual-based model, we therefore investigate the effect of susceptibility clustering driven by both age and household membership on the risk for measles outbreaks in Belgium. Furthermore, heterogeneity is important for the spread of emerging diseases, such as COVID-19. Most individuals with COVID-19 infect no other, or only one, individual, while a small group of so-called `superspreaders' are responsible for the majority of new infections. However, it is not yet fully understood how different factors contribute to the occurrence of superspreading events, as well as how these impact disease spread. Hence, we use an individual-based model to compare the effects of superspreading driven by heterogeneity in infectiousness and by heterogeneity in contact behavior. Finally, heterogeneous sexual behavior and health-seeking behavior are important for the spread of HIV. Phylogenetic analysis has revealed that the majority of local HIV transmission in Belgium occurs among MSM. However, it is not yet understood why this is the case. We therefore use an individual-based model to examine the impact of different sources of heterogeneity on the spread of HIV in this population. Individual-based models thus allow us to represent the complex interplay of different sources of heterogeneity and their effects on disease spread. On the other hand, the research we conducted in this thesis also confronted us with existing problems related to the use of individual-based models for the spread of infectious disease and highlighted the need for continued research in this area.

Publication year:2023

Accessibility:Embargoed