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Value Health ; 24(5): 632-640, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33933231

RESUMO

OBJECTIVE: To estimate the overall quality-adjusted life-years (QALYs) gained by averting 1 coronavirus disease 2019 (COVID-19) infection over the duration of the pandemic. METHODS: A cohort-based probabilistic simulation model, informed by the latest epidemiological estimates on COVID-19 in the United States provided by the Centers for Disease Control and Prevention and literature review. Heterogeneity of parameter values across age group was accounted for. The main outcome studied was QALYs for the infected patient, patient's family members, and the contagion effect of the infected patient over the duration of the pandemic. RESULTS: Averting a COVID-19 infection in a representative US resident will generate an additional 0.061 (0.016-0.129) QALYs (for the patient: 0.055, 95% confidence interval [CI] 0.014-0.115; for the patient's family members: 0.006, 95% CI 0.002-0.015). Accounting for the contagion effect of this infection, and assuming that an effective vaccine will be available in 3 months, the total QALYs gains from averting 1 single infection is 1.51 (95% CI 0.28-4.37) accrued to patients and their family members affected by the index infection and its sequelae. These results were robust to most parameter values and were most influenced by effective reproduction number, probability of death outside the hospital, the time-varying hazard rates of hospitalization, and death in critical care. CONCLUSION: Our findings suggest that the health benefits of averting 1 COVID-19 infection in the United States are substantial. Efforts to curb infections must weigh the costs against these benefits.


Assuntos
COVID-19/prevenção & controle , Custos de Cuidados de Saúde/estatística & dados numéricos , Medicina Preventiva/normas , Anos de Vida Ajustados por Qualidade de Vida , COVID-19/epidemiologia , Análise Custo-Benefício , Custos de Cuidados de Saúde/tendências , Humanos , Pandemias/prevenção & controle , Pandemias/estatística & dados numéricos , Medicina Preventiva/economia , Medicina Preventiva/métodos , Estados Unidos
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