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Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach.
Iuliano, A Danielle; Chang, Howard H; Patel, Neha N; Threlkel, Ryan; Kniss, Krista; Reich, Jeremy; Steele, Molly; Hall, Aron J; Fry, Alicia M; Reed, Carrie.
  • Iuliano AD; COVID-19 Emergency Response, Centers for Disease Control and Prevention, United States.
  • Chang HH; Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.
  • Patel NN; United States Public Health Service, United States.
  • Threlkel R; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States.
  • Kniss K; COVID-19 Emergency Response, Centers for Disease Control and Prevention, United States.
  • Reich J; Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.
  • Steele M; Abt Associates, Division of Health and Environment, Atlanta, GA, United States.
  • Hall AJ; COVID-19 Emergency Response, Centers for Disease Control and Prevention, United States.
  • Fry AM; Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.
  • Reed C; General Dynamics Information Technology, Atlanta, GA, United States.
Lancet Reg Health Am ; 1: 100019, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1309322
ABSTRACT

BACKGROUND:

In the United States, Coronavirus Disease 2019 (COVID-19) deaths are captured through the National Notifiable Disease Surveillance System and death certificates reported to the National Vital Statistics System (NVSS). However, not all COVID-19 deaths are recognized and reported because of limitations in testing, exacerbation of chronic health conditions that are listed as the cause of death, or delays in reporting. Estimating deaths may provide a more comprehensive understanding of total COVID-19-attributable deaths.

METHODS:

We estimated COVID-19 unrecognized attributable deaths, from March 2020-April 2021, using all-cause deaths reported to NVSS by week and six age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) for 50 states, New York City, and the District of Columbia using a linear time series regression model. Reported COVID-19 deaths were subtracted from all-cause deaths before applying the model. Weekly expected deaths, assuming no SARS-CoV-2 circulation and predicted all-cause deaths using SARS-CoV-2 weekly percent positive as a covariate were modelled by age group and including state as a random intercept. COVID-19-attributable unrecognized deaths were calculated for each state and age group by subtracting the expected all-cause deaths from the predicted deaths.

FINDINGS:

We estimated that 766,611 deaths attributable to COVID-19 occurred in the United States from March 8, 2020-May 29, 2021. Of these, 184,477 (24%) deaths were not documented on death certificates. Eighty-two percent of unrecognized deaths were among persons aged ≥65 years; the proportion of unrecognized deaths were 0•24-0•31 times lower among those 0-17 years relative to all other age groups. More COVID-19-attributable deaths were not captured during the early months of the pandemic (March-May 2020) and during increases in SARS-CoV-2 activity (July 2020, November 2020-February 2021).

INTERPRETATION:

Estimating COVID-19-attributable unrecognized deaths provides a better understanding of the COVID-19 mortality burden and may better quantify the severity of the COVID-19 pandemic.

FUNDING:

None.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: Lancet Reg Health Am Year: 2021 Document Type: Article Affiliation country: J.lana.2021.100019

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: Lancet Reg Health Am Year: 2021 Document Type: Article Affiliation country: J.lana.2021.100019