Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study
Barts Health NHS Trust · Royal London Hospital · +10 more institutions
Abstract
The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease.
In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation.
Citation impact
- FWCI
- 40.73
- Percentile
- 100%
- References
- 23
Authors
16- ABAmitava BanerjeeCorresponding
Barts Health NHS Trust, Royal London Hospital, University College London, University College London Hospitals NHS Foundation Trust
- LPLaura Pasea
University College London
- SHSteve Harris
University College London, University College London Hospitals NHS Foundation Trust
- AGArturo González-Izquierdo
University College London
- ATAna Torralbo
University College London
Topics & keywords
- Pandemic
- Medicine
- Population
- Demography
- Public health
- Cohort
- Cohort study
- Relative risk
- Good health and well-being
Funding
- WTWellcome Trust
- SGScottish Government
- EFEuropean Federation of Pharmaceutical Industries and AssociationsAward: 116074
- NINational Institute for Health and Care ResearchAwards: LOND1, CS-2016-007
- BHBritish Heart Foundation
- DODepartment of Health and Social CareAward: LOND1
- UCUniversity College London
- PHPublic Health Agency
- CSChief Scientist Office, Scottish Government Health and Social Care Directorate
- MRMedical Research CouncilAwards: MR/K006584/1, MC_UU_12015/1
- EAEngineering and Physical Sciences Research Council
- EAEconomic and Social Research Council
- HAHealth and Social Care Research and Development Division