The Role of Vaccine Status Homophily in the COVID-19 Pandemic: A Cross-Sectional Survey with Modeling (preprint)

Background: Vaccine homophily describes non-heterogeneous vaccine uptake within contact networks. This study was performed to determine observable patterns of vaccine homophily, associations between vaccine homophily, self-reported vaccination, COVID-19 prevention behaviours, contact network size, and self-reported COVID-19, as well as the impact of vaccine homophily on disease transmission within and between vaccination groups under conditions of high and low vaccine efficacy. Methods: Residents of British Columbia, Canada, aged [≥]16 years, were recruited via online advertisements between February and March 2022, and provided information about vaccination status, perceived vaccination status of household and non-household contacts, compliance with COVID-19 prevention guidelines, and history of COVID-19. A deterministic mathematical model was used to assess transmission dynamics between vaccine status groups under conditions of high and low vaccine efficacy. Results: Vaccine homophily was observed among the 1304 respondents, but was lower among those with fewer doses (p<0.0001). Unvaccinated individuals had larger contact networks (p<0.0001), were more likely to report prior COVID-19 (p<0.0001), and reported lower compliance with COVID-19 prevention guidelines (p<0.0001). Mathematical modelling showed that vaccine homophily plays a considerable role in epidemic growth under conditions of high and low vaccine efficacy. Further, vaccine homophily contributes to a high force of infection among unvaccinated individuals under conditions of high vaccine efficacy, as well as elevated force of infection from unvaccinated to vaccinated individuals under conditions of low vaccine efficacy. Interpretation: The uneven uptake of COVID-19 vaccines and the nature of the contact network in the population play important roles in shaping COVID-19 transmission dynamics.

Projected spread of COVID-19's second wave in South Africa under different levels of lockdown (preprint)

South Africa is currently experiencing a second wave of resurgence in COVID-19 infection. In this modelling study, we use a Bayesian compartmental model to project possible spread of the second wave of COVID-19 in South Africa under various levels of lockdown restrictions. Our model suggests that strict lockdown restrictions will have to be in place up to the end of March 2021 before cases can drop to levels observed, in September to early November 2020, after the first wave. On the one hand, extended lockdown restrictions have negative consequences -- albeit effective, they are not sustainable over extended periods. On the other hand, short lockdown restrictions over a few weeks will not have a lasting effect on the spread of the disease. Lockdown restrictions need to be supplemented with increased rapid testing, palliative support for the vulnerable, and implementations of other non-pharmaceutical interventions (NPIs) such as mask mandate. These multifaceted approaches could help keep cases under control until vaccines are widely available.