Estimating Variation of Covid-19 ‘infection’ in the Population: Results from Understanding Society’s (UKHLS) first monthly covid-19 survey

  1. Richard Breen
  2. John Ermisch

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Abstract

The analysis in this paper uses the new Understanding Society COVID-19 survey. The key advantage of these data is that they allow us to examine infection rates for people with particular characteristics. We study how reported symptoms vary in the population and relate reported symptoms to a positive Covid-19 test in the small sample in the survey who were tested. Combining these probabilities we find that the chances of infection increase with a person’s education level, are lower and declining with age among those aged over 55, and were higher in the West Midlands and London and lower in the North East than in the rest of the country, and tended to increase with regional population density. There is also evidence that the infection rate was lower among those of a Caribbean origin. A suitably cautious estimate of the mean infection rate is that, during the period up to the end of April 2020, it was between 2% and 8%, with a central rate of about 5%.

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    SciScore for 10.1101/2020.07.22.20159806: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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  2. Version published to 10.1101/2020.07.22.20159806v1 on medRxiv