Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha

Abstract

SARS-CoV-2 variants of concern (VOCs) circulated cryptically before being identified as a threat, delaying interventions. Understanding the drivers of such silent spread and its epidemic impact is critical to inform future response planning. Here, we integrated spatio-temporal records of international mobility, local epidemic growth and genomic surveillance into a Bayesian framework to reconstruct the early dissemination of Alpha out of the UK in the first three months after emergence. We found that silent circulation lasted from days to months and was logarithmically associated with sequencing coverage. Social restrictions in certain countries likely slowed down the seeding of local transmission by weeks, mitigating the negative consequences of late detection. Revisiting the initial spread of Alpha supports local mitigation at the destination in case of emerging events.

Integrating dynamical modeling and phylogeographic inference to characterize global influenza circulation

“…The recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has illustrated the importance of combining epidemiological and mobility data, genomic sequences and metadata to provide insights into viral emergence and spread. 22–27 Phylogeographic inference in particular has been widely applied to elucidate SARS-CoV-2 genomic epidemiology, including origins, introductions, routes of dispersal, and drivers associated with variant dissemination, contributing to the effectiveness of systematic genomic surveillance. 24–27 However, the development of integrated tools is still relatively limited and opportunities remain to fulfill the full potential of phylodynamic approaches.…”