Your browser doesn't support javascript.
loading
Estimating Vaccine-Preventable COVID-19 Deaths Under Counterfactual Vaccination Scenarios in the United States
Ming Zhong; Meghana Kshirsagar; Richard Johnston; Rahul Dodhia; Tammy Glazer; Allen Kim; Divya Michael; Sameer Nair-Desai; Thomas C Tsai; Stefanie Friedhoff; Juan M Lavista Ferres.
Affiliation
  • Ming Zhong; Microsoft AI for Good Research Lab
  • Meghana Kshirsagar; Microsoft AI for Good Research Lab
  • Richard Johnston; Microsoft AI for Good Research Lab
  • Rahul Dodhia; Microsoft AI for Good Research Lab
  • Tammy Glazer; Microsoft AI for Good Research Lab
  • Allen Kim; Microsoft AI for Good Research Lab
  • Divya Michael; Microsoft AI for Good Research Lab
  • Sameer Nair-Desai; Brown University School of Public Health
  • Thomas C Tsai; Harvard T.H. Chan School of Public Health
  • Stefanie Friedhoff; Brown University School of Public Health
  • Juan M Lavista Ferres; Microsoft AI for Good Research Lab
Preprint in English | medRxiv | ID: ppmedrxiv-22275310
ABSTRACT
ImportanceWith an abundant supply of COVID-19 vaccines becoming available in spring and summer 2021, the major barrier to high vaccination rates in the United States has been a lack of vaccine demand. This has contributed to a higher rate of deaths from SARS-CoV-2 infections amongst unvaccinated individuals as compared to vaccinated individuals. It is important to understand how low vaccination rates directly impact deaths resulting from SARS-CoV-2 infections in unvaccinated populations across the United States. ObjectiveTo estimate a lower bound on the number of vaccine-preventable deaths from SARS-CoV-2 infections under various scenarios of vaccine completion, for every state of the United States. Design, Setting, and ParticipantsThis counterfactual simulation study varies the rates of complete vaccination coverage under the scenarios of 100%, 90% and 85% coverage of the adult (18+) population of the United States. For each scenario, we use U.S. state-level demographic information in conjunction with county-level vaccination statistics to compute a lower bound on the number of vaccine-preventable deaths for each state. ExposuresCOVID-19 vaccines, SARS-CoV-2 infection Main Outcomes and MeasuresDeath from SARS-CoV-2 infection ResultsBetween January 1st, 2021 and April 30th, 2022, there were 641,305 deaths due to COVID-19 in the United States. Assuming each state continued peak vaccination capacity after initially achieving its peak vaccination rate, a vaccination rate of 100% would have led to 322,324 deaths nationally, that of 90% would have led to 415,878 deaths, and that of 85% would have led to 463,305 deaths. As a comparison, using the state with the highest peak vaccination rate (per million population each week) for all the states, a vaccination rate of 100% would have led to 302,344 deaths nationally, that of 90% would have led to 398,289 deaths, and that of 85% would have led to 446,449 deaths. Conclusions and RelevanceOnce COVID-19 vaccine supplies peaked across the United States, if there had been 100% COVID-19 vaccination coverage of the over 18+ population, a conservative estimate of 318,981 deaths could have been potentially avoided through vaccination. For a 90% vaccination coverage, we estimate at least 225,427 deaths averted through vaccination, and at least 178,000 lives saved through vaccination for an 85% vaccination coverage.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2022 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2022 Document type: Preprint
...