Back

High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report

Riley, S.; Ainslie, K. E. C.; Eales, O.; Walters, C. E.; Wang, H.; Atchison, C. J.; Fronterre, C.; Diggle, P. J.; Ashby, D.; Donnelly, C. A.; Cooke, G.; Barclay, W.; Ward, H.; Darzi, A.; Elliott, P.

2020-10-14 infectious diseases
10.1101/2020.10.12.20211227 medRxiv
Show abstract

BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report. MethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models. Results175,000 volunteers tested across England between 18th September and 5th October. Findings show a national prevalence of 0.60% (95% confidence interval 0.55%, 0.71%) and doubling of the virus every 29 (17, 84) days in England corresponding to an estimated national R of 1.16 (1.05, 1.27). These results correspond to 1 in 170 people currently swab-positive for the virus and approximately 45,000 new infections each day. At regional level, the highest prevalence is in the North West, Yorkshire and The Humber and the North East with strongest regional growth in North West, Yorkshire and The Humber and West Midlands. ConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England, with highest rates in the North of England. Prevalence has increased in all age groups, including those at highest risk. Improved compliance with existing policy and, as necessary, additional interventions are required to control the spread of SARS-CoV-2 in the community and limit the numbers of hospital admissions and deaths from COVID-19.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.