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COVID-19 Vaccination and Estimated Public Health Impact in California

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  How many COVID-19 cases, hospitalizations, and deaths were averted because of COVID-19 vaccination in California?

Findings  In this modeling study using data from the California Department of Public Health, COVID-19 vaccination was estimated to have prevented more than 1.5 million COVID-19 cases, 72 000 hospitalizations, and 19 000 deaths during the first 10 months of vaccination, through October 16, 2021.

Meaning  These findings suggest that COVID-19 vaccination had a large public health benefit in California, which can be generalized across the United States.

Abstract

Importance  Despite widespread vaccination against COVID-19 in the United States, there are limited empirical data quantifying their public health impact in the population.

Objective  To estimate the number of COVID-19 cases, hospitalizations, and deaths directly averted because of COVID-19 vaccination in California.

Design, Setting, and Participants  This modeling study used person-level data provided by the California Department of Public Health (CDPH) on COVID-19 cases, hospitalizations, and deaths as well as COVID-19 vaccine administration from January 1, 2020, to October 16, 2021. A statistical model was used to estimate the number of COVID-19 cases that would have occurred in the vaccine era (November 29, 2020, to October 16, 2021) in the absence of vaccination based on the ratio of the number of cases among the unvaccinated (aged <12 years) and vaccine-eligible groups (aged ≥12 years) before vaccine introduction. Vaccine-averted COVID-19 cases were estimated by finding the difference between the projected and observed number of COVID-19 cases. Averted COVID-19 hospitalizations and deaths were assessed by applying estimated hospitalization and case fatality risks to estimates of vaccine-averted COVID-19 cases. As a sensitivity analysis, a second independent model was developed to estimate the number of vaccine-averted COVID-19 outcomes by applying published data on vaccine effectiveness to data on COVID-19 vaccine administration and estimated risk of COVID-19 over time.

Exposure  COVID-19 vaccination.

Main Outcomes and Measures  Number of COVID-19 cases, hospitalizations, and deaths estimated to have been averted because of COVID-19 vaccination.

Results  There were 4 585 248 confirmed COVID-19 cases, 240 718 hospitalizations, and 70 406 deaths in California from January 1, 2020, to October 16, 2021, during which 27 164 680 vaccine-eligible individuals aged 12 years and older were reported to have received at least 1 dose of a COVID-19 vaccine in the vaccine era (79.5% of the eligible population). The primary model estimated that COVID-19 vaccination averted 1 523 500 (95% prediction interval [PI], 976 800-2 230 800) COVID-19 cases in California, corresponding to a 72% (95% PI, 53%-91%) relative reduction in cases because of vaccination. COVID-19 vaccination was estimated to have averted 72 930 (95% PI, 53 250-99 160) hospitalizations and 19 430 (95% PI, 14 840-26 230) deaths during the study period. The alternative model identified comparable findings.

Conclusions and Relevance  This study provides evidence of the public health benefit of COVID-19 vaccination in the United States and further supports the urgency for continued vaccination.

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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Accepted for Publication: March 6, 2022.

Published: April 22, 2022. doi:10.1001/jamanetworkopen.2022.8526

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Tan ST et al. JAMA Network Open.

Corresponding Author: Nathan C. Lo, MD, PhD, Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA 94110 (nathan.lo@ucsf.edu).

Author Contributions: Ms Tan and Dr Lo had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Tan, Rodríguez-Barraquer, Bibbins-Domingo, Schechter, Lo.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Tan, Lo.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Tan, Park, Rodríguez-Barraquer, Lo.

Obtained funding: Schechter, Lo.

Administrative, technical, or material support: Park, Rutherford, Schechter, Lo.

Supervision: Bibbins-Domingo, Lo.

Conflict of Interest Disclosures: Dr Lo reported receiving personal fees from the World Health Organization outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by the California Department of Public Health (CDPH).

Role of the Funder/Sponsor: Dr Schechter is an employee of the CDPH and was involved analysis and interpretation of the data and the review and approval of the manuscript. The funder had otherwise no role in the design and conduct of the study; analysis and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: These findings and conclusions represent the viewpoints of the authors alone and not necessarily the views or opinions of the CDPH or the California Health and Human Services Agency.

Additional Contributions: We thank the CDPH for sharing the data used in this article and appreciate all the individuals involved in data collection and curation. We specifically appreciate assistance from the CDPH COVID-19 Data Processing and Informatics Section and COVID-19 Modeling Team. We would also like to thank all those involved in the ongoing response to the COVID-19 pandemic in California.

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