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COVID-19 Vaccination and Estimated Public Health Impact in California.
Tan, Sophia T; Park, Hailey J; Rodríguez-Barraquer, Isabel; Rutherford, George W; Bibbins-Domingo, Kirsten; Schechter, Robert; Lo, Nathan C.
Afiliação
  • Tan ST; Division of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco.
  • Park HJ; Division of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco.
  • Rodríguez-Barraquer I; Division of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco.
  • Rutherford GW; Department of Medicine, University of California, San Francisco.
  • Bibbins-Domingo K; Department of Epidemiology and Biostatistics, University of California, San Francisco.
  • Schechter R; Department of Medicine, University of California, San Francisco.
  • Lo NC; Department of Epidemiology and Biostatistics, University of California, San Francisco.
JAMA Netw Open ; 5(4): e228526, 2022 04 01.
Article em En | MEDLINE | ID: mdl-35452106
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vacinas contra COVID-19 / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: JAMA Netw Open Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vacinas contra COVID-19 / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: JAMA Netw Open Ano de publicação: 2022 Tipo de documento: Article