Evidence map›Paper›PMID 32609310›Full record

Observational studyJAMA internal medicine2020

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020.

Daniel M Weinberger, Jenny Chen, Ted Cohen, Forrest W Crawford, Farzad Mostashari, Don Olson, Virginia E Pitzer, Nicholas G Reich, Marcus Russi, Lone Simonsen and 2 more

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in JAMA internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06844227 (Perioperative Anticoagulant Use for Surgery Evaluation -Virtual Visit), which is not on this map. Cited by 273 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
273citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06844227 recruitingnot on this mapstarted 2021, after this paper: background citation

Perioperative Anticoagulant Use for Surgery Evaluation -Virtual Visit (PAUSE-Virtual), a Simple Perioperative Anticoagulant Management Approach, Replacing a Resource-intensive In-person Doctor-patient Consultation, With a Simple Virtual Care Model That Will Provide a New Standard of Care for Patients on a Direct Oral Anticoagulant or Warfarin and Require Elective Surgery/Procedure.

TypeobservationalSponsorMcMaster UniversityRan2021 to 2026Enrolled1,780ConditionsAtrial Fibrillation (AF)
3 · Its place in the literature

Who cites it

273 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  18. A Bayesian spatial-temporal varying coefficients model for estimating excess deaths associated with respiratory infections.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025
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213 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Daniel M WeinbergerDepartment of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Jenny ChenDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland.
Ted CohenDepartment of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Forrest W CrawfordDepartment of Biostatistics and the Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Farzad MostashariAledade Inc, Bethesda, Maryland.
Don OlsonDepartment of Health and Mental Hygiene, New York, New York.
Virginia E PitzerDepartment of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Nicholas G ReichDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst.
Marcus RussiDepartment of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Lone SimonsenDepartment of Science and Environment, Roskilde University, Fredeiksberg, Denmark.
Anne WatkinsDepartment of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Cecile ViboudDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Influenza Forecasting Center of Excellence at University of Massachusetts AmherstU01IP001122 · IP · UNIVERSITY OF MASSACHUSETTS AMHERST · PI REICH, NICHOLAS G · 2019 to 2023
$5.4M
Statistical methods for real-time forecasts of infectious disease: expanding dynamic time-series and machine learning approaches for pandemic scenariosR35GM119582 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Nicholas G Reich · 2016 to 2026
$4.8M
Modeling the impact and cost-effectiveness of next-generation rotavirus vaccine strategies in low- and middle-income countriesR01AI112970 · NIAID · YALE UNIVERSITY · PI PITZER, VIRGINIA E · 2015 to 2024
$4.1M
Predicting and monitoring variations in the effects of vaccines against RSVR01AI137093 · NIAID · YALE UNIVERSITY · PI Virginia E Pitzer, Daniel Martin Weinberger · 2018 to 2026
$3.4M
Forecasting pneumococcal serotype frequencies to develop adult-specific vaccinesR01AI123208 · NIAID · YALE UNIVERSITY · PI WEINBERGER, DANIEL MARTIN · 2016 to 2019
$2.5M
Optimal targeting for individual and population-level TB preventionR01AI146555 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI MENZIES, NICOLAS A · 2020 to 2024
$2.5M
NCATS NIH HHS UL1 TR001863NCIRD CDC HHS U01 IP001122NIAID NIH HHS R01 AI112970NIAID NIH HHS R01 AI123208NIAID NIH HHS R01 AI137093NIAID NIH HHS R01 AI146555NIGMS NIH HHS R35 GM119582
6 · The paper itself

Abstract

Importance: Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19. Objective: To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020. Design, Setting, and Population: This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020. Main Outcomes and Measures: Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data. Results: There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths. Conclusions and Relevance: Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

Indexed as

Coronavirus InfectionsInfluenza, HumanPneumoniaPneumonia, ViralAdultBetacoronavirusCause of DeathClinical Laboratory TechniquesCost of IllnessCOVID-19COVID-19 TestingFemaleHumansMaleMortalityPandemics

Identifiers

PMID32609310
PMCPMC7330834

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.