Abstract
Background Deaths are frequently under-estimated during emergencies, including hurricanes and pandemics. Accurate mortality data may improve public compliance with non-pharmaceutical interventions.
Methods This study estimates excess all-cause, pneumonia, and influenza mortality during the COVID-19 health emergency using a semiparametric method and a conventional time-series method — in 9 states in the United States using weekly mortality data from the Mortality Surveillance Survey from September 27, 2015 to April 18, 2020. We chose 9 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Florida, Illinois, Massachusetts, Michigan, New Jersey, New York, and Washington.
Findings For the United States, we estimated more excess deaths than COVID-19 official mortality (excess mortality 95% CI (44256, 62263) vs. 34571 COVID-19 deaths). Furthermore: California (excess mortality 95% CI (1347, 3494) vs. 1072 COVID-19 deaths); Colorado (95% CI (622, 1012) vs. 391 COVID-19 deaths); Illinois (95% CI (1931, 2896) vs. 1259 COVID-19 deaths); Massachusetts (95% CI (2128, 2921) vs. 1983 COVID-19 deaths); Michigan (95% CI (3223, 4270) vs. 2308 COVID-19 deaths);New Jersey (95% CI (7799, 9740) vs. 4070 COVID-19 deaths); and New York (95% CI (22420, 27349) vs. 13362 COVID-19 deaths).
Interpretation Official COVID-19 mortality figures substantially understate actual mortality and suggest greater case-fatality rates. Some excess mortality may be due to not seeking care for emergent severe conditions. Improving the speed and scope of data dissemination of mortality and syndromic surveillance may reduce mortality in future pandemics by improving public adherence to non-pharmaceutical interventions and improving care-seeking for emergent conditions.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
NSF OAC 1940179
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Paper in collection COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv
The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, University of Washington, and Vrije Universiteit Amsterdam.
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