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Value Health ; 23(11): 1432-1437, 2020 11.
Article in English | MEDLINE | ID: covidwho-894096

ABSTRACT

OBJECTIVE: This study aims to cost and calculate the relative cost-effectiveness of the hypothetical suppression policies found in the Imperial College COVID-19 Response Team model. METHODS: Key population-level disease projections in deaths, intensive care unit bed days, and non-intensive care unit bed days were taken from the Imperial College COVID-19 Response Team report of March 2020, which influenced the decision to introduce suppression policies in the United Kingdom. National income loss estimates were from a study that estimated the impact of a hypothetical pandemic on the UK economy, with sensitivity analyses based on projections that are more recent. Individual quality-adjusted life-year (QALY) loss and costed resource use inputs were taken from published sources. RESULTS: Imperial model projected suppression polices compared to an unmitigated pandemic, even with the most pessimistic national income loss scenarios under suppression (10%), give incremental cost-effectiveness ratios below £50 000 per QALY. Assuming a maximum reduction in national income of 7.75%, incremental cost-effectiveness ratios for Imperial model projected suppression versus mitigation are below 60 000 per QALY. CONCLUSIONS: Results are uncertain and conditional on the accuracy of the Imperial model projections; they are also sensitive to estimates of national income loss. Nevertheless, it would be difficult to claim that the hypothetical Imperial model-projected suppression policies are obviously cost-ineffective relative to the alternatives available. Despite evolving differences between government policy and Imperial model-projected suppression policy, it is hoped this article will provide some early insight into the trade-offs that are involved.


Subject(s)
Coronavirus Infections/epidemiology , Disease Eradication/economics , Health Policy/economics , Pneumonia, Viral/epidemiology , Betacoronavirus , COVID-19 , Cost-Benefit Analysis , Humans , Pandemics , Quality-Adjusted Life Years , SARS-CoV-2 , United Kingdom/epidemiology
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