Excess mortality in the first COVID pandemic peak: cross-sectional analyses of the impact of age, sex, ethnicity, household size, and long-term conditions in people of known SARS-CoV-2 status in England

Br J Gen Pract. 2020 Nov 26;70(701):e890-e898. doi: 10.3399/bjgp20X713393. Print 2020 Dec.

Abstract

Background: The SARS-CoV-2 pandemic has passed its first peak in Europe.

Aim: To describe the mortality in England and its association with SARS-CoV-2 status and other demographic and risk factors.

Design and setting: Cross-sectional analyses of people with known SARS-CoV-2 status in the Oxford RCGP Research and Surveillance Centre (RSC) sentinel network.

Method: Pseudonymised, coded clinical data were uploaded from volunteer general practice members of this nationally representative network (n = 4 413 734). All-cause mortality was compared with national rates for 2019, using a relative survival model, reporting relative hazard ratios (RHR), and 95% confidence intervals (CI). A multivariable adjusted odds ratios (OR) analysis was conducted for those with known SARS-CoV-2 status (n = 56 628, 1.3%) including multiple imputation and inverse probability analysis, and a complete cases sensitivity analysis.

Results: Mortality peaked in week 16. People living in households of ≥9 had a fivefold increase in relative mortality (RHR = 5.1, 95% CI = 4.87 to 5.31, P<0.0001). The ORs of mortality were 8.9 (95% CI = 6.7 to 11.8, P<0.0001) and 9.7 (95% CI = 7.1 to 13.2, P<0.0001) for virologically and clinically diagnosed cases respectively, using people with negative tests as reference. The adjusted mortality for the virologically confirmed group was 18.1% (95% CI = 17.6 to 18.7). Male sex, population density, black ethnicity (compared to white), and people with long-term conditions, including learning disability (OR = 1.96, 95% CI = 1.22 to 3.18, P = 0.0056) had higher odds of mortality.

Conclusion: The first SARS-CoV-2 peak in England has been associated with excess mortality. Planning for subsequent peaks needs to better manage risk in males, those of black ethnicity, older people, people with learning disabilities, and people who live in multi-occupancy dwellings.

Keywords: medical record systems, computerized; mortality; pandemics; sentinel surveillance; severe acute respiratory syndrome coronavirus 2.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • COVID-19* / diagnosis
  • COVID-19* / epidemiology
  • Electronic Health Records / statistics & numerical data
  • England / epidemiology
  • Ethnicity
  • Family Characteristics
  • Female
  • Humans
  • Male
  • Middle Aged
  • Mortality
  • Noncommunicable Diseases / epidemiology*
  • Risk Assessment / methods
  • Risk Factors
  • SARS-CoV-2 / isolation & purification*
  • Sentinel Surveillance
  • Sex Factors