Streptococcus pneumoniae, the pneumococcus, is a leading cause of pneumonia, meningitis and sepsis globally, and is hence a pathogen of major public health interest. The spread of antibiotic resistance and the emergence vaccine-escape variants pose particular challenges to public health interventions. The maintenance of antibiotic resistance at stable, intermediate frequencies, and patterns of post-vaccine strain replacement are indicative of complex interactions and competition. Mathematical models can provide key insights into the mechanisms which maintain diversity in multistrain pathogens such as the pneumococcus. Coinfection has been identified as an important mechansism behind the coexistence of drug-sensitive and drug-resistant phenotypes. Our analysis of compartmental models with coinfection highlight how subtle changes in the dynamics of secondary infections can have significant impacts on model dynamics and, in particular, in the ability of these models to generate multistrain coexistence. Often, the assumptions these models make regarding coinfection dynamics are difficult to justify and parameterize. We argue that in order to study key ecological patterns in the pneumococcus, a different modelling approach is necessary. To that end, we develop an agent-based nested model with explicit dynamics on both within-host and between-host scales. This modelling approach allows us to explore how within-host competition shapes long-term population-level patterns, as well as vaccine-induced dynamics. We furthermore show how modelling can be used to assess pandemic intervention strategies. Throughout the COVID-19 pandemic, modelling played an important role. In late 2020, as the first vaccines against COVID-19 began to be disseminated, the province of British Columbia initially proposed an age-based rollout strategy. We sought to evaluate the relative effectiveness of different vaccine rollout strategies by comparing age-based strategies to those which exploit contact structure by targeting so-called essential workers. Using an age-and work-structured dynamic transmission model for COVID-19, we show that in many jurisdictions there are benefits to targeting essential workers earlier than they would be using an age-based only strategy.
Copyright is held by the author(s).
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Member of collection