Abstract
•Current literature on excess mortality during the first wave of COVID-19 is limited.•We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) for weeks 2 to 20 in 2020 from surveillance network data.•AER of mortality was 197.8 per 10,000 person years.•Being male, older, of black ethnicity, more deprived, and living in a larger household increased EMR.•Presence of comorbidities also increased EMR.
Few studies report contributors to the excess mortality in England during the first wave of coronavirus disease 2019 (COVID-19) infection. We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) from a nationally representative COVID-19 sentinel surveillance network including known COVID-19 risk factors in people aged 45 years and above.
Pseudonymised, coded clinical data were uploaded from contributing primary care providers (N = 1,970,314, ≥45years). We calculated the AER in mortality by comparing mortality for weeks 2 to 20 this year with mortality data from the Office for National Statistics (ONS) from 2018 for the same weeks. We conducted univariate and multivariate analysis including preselected variables. We report AER and EMR, with 95% confidence intervals (95% CI).
The AER of mortality was 197.8/10,000 person years (95%CI:194.30–201.40). The EMR for male gender, compared with female, was 1.4 (95%CI:1.35–1.44, p<0.00); for our oldest age band (≥75 years) 10.09 (95%CI:9.46–10.75, p<0.00) compared to 45–64 year olds; Black ethnicity's EMR was 1.17 (95%CI: 1.03–1.33, p<0.02), reference white; and for dwellings with ≥9 occupants 8.01 (95%CI: 9.46–10.75, p<0.00). Presence of all included comorbidities significantly increased EMR. Ranked from lowest to highest these were: hypertension, chronic kidney disease, chronic respiratory and heart disease, and cancer or immunocompromised.
The absolute excess mortality was approximately 2 deaths per 100 person years in the first wave of COVID-19. More personalised shielding advice for any second wave should include ethnicity, comorbidity and household size as predictors of risk.