An Agent-Based Modelling Approach to Investigate the Impact of Sex and Gender on Tuberculosis Transmission: A Case Study of Kampala, Uganda

Source abstract

Abstract Tuberculosis (TB) is an airborne disease caused by the pathogen Mycobacterium tuberculosis . In 2023, it returned to being the leading cause of death from an infectious agent globally, replacing COVID-19. More than 10 million people are diagnosed with TB every year. The majority of cases in adults occur in males (62.5% of all global adult cases in 2023, compared to 37.5% in females). The main reasons for males suffering from a higher burden of global TB cases, compared to females, may be in large part due to population-scale factors, such as employment type, the quantity and type of social contacts they make, and their health-seeking behaviours. To investigate which population-scale factors are most important in determining this higher TB burden in males, we have developed an age- and sex/gender-stratified, spatially heterogeneous epidemiological agent-based model. We have focused specifically on Kampala, the capital of Uganda, which is a high-burden TB country. We considered counterfactual scenarios to elucidate the impact of sex and gender on the epidemiology of TB, in order to deduce which factors have greater explanatory power in producing the observed differences between sexes/genders. Within-host parameters had the largest effect on overall case numbers among the scenarios considered. On the other hand, behavioural factors (particularly assortative mixing and gender-specific contact patterns) appear important in explaining the elevated male-to-female case ratio. We also found that super-spreaders appear to cause a majority of infections, with males and individuals with cavitary TB causing more infections on average. Our model provides a proof-of-concept framework that could help support public health policy after further validation.