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Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach
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 o...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275579/ https://www.ncbi.nlm.nih.gov/pubmed/34386789 http://dx.doi.org/10.1016/j.lana.2021.100019 |
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author | 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 |
author_facet | 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 |
author_sort | Iuliano, A. Danielle |
collection | PubMed |
description | 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 |
format | Online Article Text |
id | pubmed-8275579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-82755792021-07-14 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 Lancet Reg Health Am Research Paper 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 Elsevier 2021-06-28 /pmc/articles/PMC8275579/ /pubmed/34386789 http://dx.doi.org/10.1016/j.lana.2021.100019 Text en © 2021 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper 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 Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach |
title | Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach |
title_full | Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach |
title_fullStr | Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach |
title_full_unstemmed | Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach |
title_short | Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach |
title_sort | estimating under-recognized covid-19 deaths, united states, march 2020-may 2021 using an excess mortality modelling approach |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275579/ https://www.ncbi.nlm.nih.gov/pubmed/34386789 http://dx.doi.org/10.1016/j.lana.2021.100019 |
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