Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Reproducibility between counts of airborne allergenic pollen from two cities in the East Midlands, UK

Historically in the East Midlands, UK, airborne pollen has been monitored in two cities, Derby and Leicester, situated 41 km (25 miles) apart. The aim of the present study was to compare aerobiological data from both sites to determine if a forecast based on data from one site would be sufficient for both, and to address the wider issue of reproducibility between geographically separated sites. Pollen types recorded could be split into two groups according to annual abundance, maximum daily concentration and the number of high count days. Six taxa made up the abundant group; ash, birch, grass, oak, nettle-type and yew-type, representing 90 and 88% of the total air spora for Derby and Leicester, respectively. Three consecutive years of grass and nettle pollen data are presented, supported by one year of abundant tree pollen data. There were highly significant positive correlations between the counts obtained. Line charts showing the average number of pollen grains m−3 air day−1 show similar trends, and Bland–Altman plots show little discrepancy between the amounts of pollen counted on any given day. Each day was classified according to the UK accepted threshold levels for grass. Weighted kappa statistics showed substantial or almost perfect agreement between the forecast classifications. With the caveat that this would not apply in a region with restrictions to air flow such as a mountain range or with extreme fluctuations such as a coastline site, this study suggests that data from a single site is suitable for forecasting a distance of up to 41 km