About: Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study
Creator	Sebire, Neil Pillay, Deenan Williams, Bryan Wong, Wai Banerjee, Amitava Denaxas, Spiros Hemingway, Harry Langenberg, Claudia Noursadeghi, Mahdad Pasea, Laura Shallcross, Laura Torralbo, Ana Holmes, Chris Gonzalez-Izquierdo, Arturo Harris, Steve Pagel, Christina
Source	Elsevier; Medline; PMC
abstract	BACKGROUND: 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. METHODS: 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. FINDINGS: We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41–4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. INTERPRETATION: We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. FUNDING: National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.
has issue date	2020-05-12(xsd:dateTime)
bibo:doi	10.1016/s0140-6736(20)30854-0
bibo:pmid	32405103
has license	no-cc
sha1sum (hex)	2f58271a42b1fcfa9c4ab5bfbe5cdf33b0441dbb
schema:url	https://doi.org/10.1016/s0140-6736%2820%2930854-0
resource representing a document's title	Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study
has PubMed Central identifier	PMC7217641
has PubMed identifier	32405103
schema:publication	Lancet
resource representing a document's body	covid:2f58271a42b1fcfa9c4ab5bfbe5cdf33b0441dbb#body_text
is schema:about of	named entity 'mortality' named entity 'Models' named entity 'impact' named entity 'cohort study' named entity 'COVID-19' named entity 'PREVIOUS' named entity 'DAYS' named entity 'MEDICAL' named entity 'effects' named entity 'models' named entity 'COVID-19' named entity '1 year' named entity 'COVID-19 pandemic' named entity 'population-based' named entity 'Declaration of Helsinki' named entity 'Office of National Statistics' named entity 'electronic health records' named entity 'chronic kidney disease' named entity 'heart attack' named entity 'excess deaths' named entity 'COPD' named entity 'cardiovascular diseases' named entity 'general practice' named entity 'AstraZeneca' named entity 'excess deaths' named entity 'socioeconomic' named entity 'England' named entity 'primary care' named entity 'cardiovascular disease' named entity 'COVID-19' named entity 'Germany' named entity 'cardiovascular disease' named entity 'COVID' named entity 'heart disease' named entity 'research groups' named entity 'solid organ transplants' named entity 'daily living' named entity 'vascular disease' named entity 'comorbidities' named entity 'immunosuppression' named entity 'COVID-19' named entity 'excess deaths' named entity 'social isolation' named entity 'Italy' named entity 'COVID-19' named entity 'health-care' named entity 'COVID-19' named entity 'relative risk' named entity 'infection' named entity 'diabetes' named entity 'COVID-19 pandemic' named entity 'excess deaths' named entity 'Kaplan-Meier' named entity 'diabetes' named entity 'mm Hg' named entity 'electronic health records' named entity 'underlying condition' named entity 'diabetes' named entity 'cystic fibrosis' named entity 'COVID-19' named entity 'health records' named entity 'coronavirus disease 2019' named entity 'COPD' named entity 'NSAIDs' named entity 'vascular disease' named entity 'excess mortality'

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