Exploring the impact of interventions on the transmission dynamics of infectious diseases: antimicrobial resistant foodborne disease and COVID-19

Abstract

Antimicrobial resistance (AMR) and coronavirus disease 2019 (COVID-19) currently represent two of the most important threats to human health, with both AMR and COVID-19 resulting in millions of deaths worldwide and severe socioeconomic disruption. It is therefore critical to understand how interventions can be used to mitigate the impact of these two threats to human health. However, there are large gaps in research exploring the range of impacts following the introduction of interventions on the transmission dynamics of AMR and COVID-19. In particular, the influence of livestock antibiotic stewardship on AMR in human populations is poorly understood. This includes antimicrobial resistant foodborne disease caused by human pathogens such as Salmonella. Additionally, during the initial stages of the COVID-19 pandemic in 2020, there was a need to understand the feasibility of so-called “optimal” strategies to best mitigate the impact of outbreaks. In this thesis, I aimed to explore the impact of interventions on the transmission dynamics of AMR and COVID-19. A systematic scoping review identified the literature base for the modelling of AMR transmission/dissemination between livestock/human populations. Mathematical models were also developed to explore the impacts of livestock antibiotic curtailment on antimicrobial resistant human foodborne disease and to optimise the timing, strength and duration of non-pharmaceutical interventions (NPIs) to mitigate COVID-19 outbreaks. Large literature gaps in AMR modelling were identified, with existing models exploring a narrow subset of model structures, interventions, settings, and a general lack of model validation in identified studies. Livestock antibiotic curtailment resulted in increases in the daily incidence of foodborne disease, as well as a decrease in the proportion of antibiotic-resistant human infections. However, increases in foodborne disease could be mitigated by strengthening biosecurity along the farm-to-fork pathway. The efficacy of livestock antibiotic curtailment to control human antibiotic-resistant foodborne disease was disrupted when the influence of AMR contamination on imported food products was also modelled. This was attributable to an increase in antibiotic-sensitive/resistant foodborne disease from imported sources, unalterable through local antibiotic curtailment strategies. Additionally, while optimal NPIs to minimise the attack rate and epidemic peak were identified, they were found to be fragile, with robust, but suboptimal interventions over a broader parameter space for the timing, strength and duration of NPIs being more practical and less prone to implementation error. This work presented in this thesis adds to a growing evidence base quantifying the intended and unintended impacts of interventions on the transmission dynamics of AMR at the one-health interface and COVID-19. This thesis also provides modelling frameworks that can be expanded to explore future AMR and COVID-19 research questions.