ABSTRACT
BackgroundTransmission chains within small urban areas (accommodating[~]30% of the European population) greatly contribute to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of SARS-CoV-2 transmission in a European urban area, Basel-City (Switzerland). Methodology. We combined detailed epidemiological, intra-city mobility, and socioeconomic data-sets with whole-genome-sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44% of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60% of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare-system burden (intensive-care-unit occupancy). Principal Findings. Transmissions were driven by socioeconomically weaker and highly mobile population groups with mostly cryptic transmissions, whereas amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90% transmission reduction, and 70-90% reduction of severe cases showed that prioritizing mobile, socioeconomically weaker populations for vaccination would effectively reduce case numbers. However, long-term intensive-care-unit occupation would also be effectively reduced if senior population groups were prioritized, provided there were no changes in testing and prevention strategies. Conclusions. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area. Author summaryWe examined SARS-CoV-2 transmission patterns within a European city (Basel, Switzerland) to infer drivers of the transmission during the first wave in spring 2020. The combination of diverse data (serological, genomic, transportation, socioeconomic) allowed us to combine phylogenetic analysis with mathematical modelling on related cases that were mapped to a residential address. As a result we could evaluate population groups driving SARS-CoV-2 transmission and quantify their effect on the transmission dynamics. We found traceable transmission chains in wealthier or more senior population groups and cryptic transmissions in the mobile, young or socioeconomic weaker population groups - these were identified as transmission drivers of the first wave. Based on this insight, we simulated vaccination scenarios for various vaccine efficacies to reflect different approaches undertaken to handle the epidemic. We conclude that vaccination of the mobile inherently younger population group would be most effective to handle following waves.
