Population disruption: estimating changes in population distribution in the UK during the COVID-19 pandemic (preprint)

Mobility data have demonstrated major changes in human movement patterns in response to COVID-19 and associated interventions in many countries. This can involve sub-national redistribution, short-term relocations as well as international migration. In this paper, we combine detailed location data from Facebook measuring the location of approximately 6 million daily active Facebook users in 5km2 tiles in the UK with census-derived population estimates to measure population mobility and redistribution. We provide time-varying population estimates and assess spatial population changes with respect to population density and four key reference dates in 2020 (First lockdown, End of term, Beginning of term, Christmas). We also show how the timing and magnitude of observed population changes can impact the size of epidemics using a deterministic model of COVID-19 transmission. We estimate that between March 2020 and March 2021, the total population of the UK has declined and we identify important spatial variations in this population change, showing that low-density areas have experienced lower population decreases than urban areas. We estimate that, for the top 10% highest population tiles, the population has decreased by 6.6%. Further, we provide evidence that geographic redistributions of population within the UK coincide with dates of non-pharmaceutical interventions including lockdowns and movement restrictions, as well as seasonal patterns of migration around holiday dates. The methods used in this study reveal significant changes in population distribution at high spatial and temporal resolutions that have not previously been quantified by available demographic surveys in the UK. We found early indicators of potential longer-term changes in the population distribution of the UK although it is not clear how these changes may persist after the COVID-19 pandemic.

How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology (preprint)

We hypothesised that cross-protection from seasonal epidemics of human coronaviruses (HCoVs) could have affected SARS-CoV-2 transmission, including generating reduced susceptibility in children. To determine what the pre-pandemic distribution of immunity to HCoVs was, we fitted a mathematical model to 6 years of seasonal coronavirus surveillance data from England and Wales. We estimated a duration of immunity to seasonal HCoVs of 7.3 years (95%CI 6.8 - 7.9) and show that, while cross-protection between HCoV and SARS-CoV-2 may contribute to the age distribution, it is insufficient to explain the age pattern of SARS-CoV-2 infections in the first wave of the pandemic in England and Wales. Projections from our model illustrate how different strengths of cross-protection between circulating coronaviruses could determine the frequency and magnitude of SARS-CoV-2 epidemics over the coming decade, as well as the potential impact of cross-protection on future seasonal coronavirus transmission.