Virtual Program

Non-Health Considerations in Economic Evaluations of COVID-19 Interventions: A Systemic Review

Author(s)

Podolsky M, Kim D, Neumann PI
Tufts Medical Center, Boston, MA, USA

OBJECTIVES

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To examine whether and how economic evaluations for COVID-19 interventions incorporate non-health impacts.

METHODS

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Using pre-specified keywords, we searched the National Institute of Health’s iSearch COVID-19 portfolio, containing both pre-prints and peer-reviewed articles, as our primary database to identify economic evaluations of COVID-19 interventions in December 2020. We retained studies that empirically evaluated economic as well as health consequences of COVID-19 interventions. We supplemented our search with additional sources, such as Google Scholar, COVID Scholar, EconLit, and NBER. Based on the Second Panel’s “Impact Inventory,” modified for COVID-19, we examined in the identified studies any consideration of non-health impacts, such as reduced productivity due to remote work, short-term job-related income loss, long-term unemployment, and other impacts on gross domestic product (GDP), and other sectors (e.g., related to environment or housing).

RESULTS

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Of 274 articles screened, 61 met our inclusion criteria. The sample was comprised of 39 (64%) cost-effectiveness analyses (CEA), 17 (28%) cost-benefit analyses, and 5 (8%) other economic evaluations. The most commonly examined intervention was mobility restrictions, including stay-at-home orders and travel/gathering bans (n=25, 41%), followed by testing strategies (n=15, 25%) and therapeutics (n=15, 25%). Out of 22 CEAs that reported cost-per-quality-adjusted-life-years (QALY) outcomes, the median incremental cost-effectiveness ratio was lowest for therapeutics ($848/QALY, n=7, inter-quartile range [IQR]: $547-$10,306) and highest for testing strategies ($2,172,300/QALY, n=9, IQR: $993,550-31,376,150). Twenty-nine studies (47%) included some type of non-health impact, most commonly lost income (n=17, 28%), followed by GDP impacts (n=11, 18%) and productivity (n=6, 10%).

CONCLUSIONS

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Consideration of non-health impacts is lacking in evaluations of COVID-19 interventions. Omission of these impacts can skew the value of pharmaceutical and non-pharmaceutical interventions and could have consequences for policy determinations as the pandemic continues. Researchers should consider including societal impacts in their analyses to more closely reflect the true value of interventions.