A Systematic Review of Economic Evaluations of COVID-19 Interventions: Considerations of Non-Health Impacts and Distributional Issues

Growth and changing landscape of the cost-utility literature: an Australian perspective, 1992-2022

BACKGROUND

Since the introduction of cost-utility analysis (CUA) in the 1990s, its methodologies and applications have evolved significantly in Australia.

OBJECTIVES

To provide a comprehensive overview of the volume, trends, and characteristics of the application of CUA in healthcare decision-making.

METHODS

Bibliometric analysis of published CUAs identified from the Cost-Effectiveness Analysis Registry, a `1comprehensive source of CUA data between 1992 and 2022. Multinomial logistic regression models were conducted to explore the associations between ICERs and variables including sponsorship, perspective, and discount rate.

RESULTS

N = 484 unique Australian-based CUAs were analysed. Over the last three decades, the volume and quality of CUAs in Australia have steadily increased. Commonly evaluated interventions included pharmaceuticals (21.5 %), health education/behaviour (18.0 %), and models of care (16.6 %), while diseases of circulatory system, cancers, and metabolic diseases were the most studied health conditions. Only nine CUAs involved First Nations people. Most CUAs (72.9 %) were conducted from a healthcare payer perspective, with only 19.0 % adopting a societal perspective. Approximately half of studies applied a 5 % discount rate, and 50.4 % used a $50,000 WTP threshold. 14.7 % CUAs were sponsored by industry. Regression analyses showed that industry sponsorship, societal perspective, and lower discount rate were positively associated with lower ICERs.

CONCLUSIONS

The increasing volume of CUAs underscores the importance of efficient allocation of scare resources in Australian health system. However, gaps remain, particularly in the inclusion of First Nations populations and the societal costs. Further research is needed to address these gaps and to evaluate the impact of sponsorship and discounting on CUA outcomes.

Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent

PURPOSE

Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized.

METHODS

We compare iSTM-produced estimates of decision uncertainty and VOI to corresponding cSTMs. For a 2-alternative decision and normally distributed incremental costs and benefits, we derive analytical expressions for the probability of being cost-effective and the expected value of perfect information (EVPI) for cSTMs and iSTMs, accounting for correlations in incremental outcomes at the population and individual levels. We use numerical simulations to illustrate our findings and explore the impact of relaxing normality assumptions or having >2 decision alternatives.

RESULTS

iSTM estimates of decision uncertainty and VOI are biased but asymptotically consistent (i.e., bias approaches 0 as number of microsimulated individuals approaches infinity). Decision uncertainty depends on 1 tail of the INMB distribution (e.g., P[INMB <0]), which depends on estimated variance (larger with iSTMs given first-order noise). While iSTMs overestimate EVPI, their direction of bias for the probability of being cost-effective is ambiguous. Bias is larger when uncertainties in incremental costs and effects are negatively correlated since this increases INMB variance.

CONCLUSIONS

iSTMs are useful for probabilistic economic evaluations. While more samples at the population uncertainty level are interchangeable with more microsimulations for estimating EINMB, minimizing iSTM bias in estimating decision uncertainty and VOI depends on sufficient microsimulations. Analysts should account for this when allocating their computational budgets and, at minimum, characterize such bias in their reported results.

HIGHLIGHTS

Individual-level state-transition microsimulation models (iSTMs) produce biased but consistent estimates of the probability that interventions are cost-effective.iSTMs also produce biased but consistent estimates of the expected value of perfect information.The biases in these decision uncertainty and value-of-information measures are not reduced by more parameter sets being sampled from their population-level uncertainty distribution but rather by more individuals being microsimulated for each parameter set sampled.Analysts using iSTMs to quantify decision uncertainty and value of information should account for these biases when allocating their computational budgets and, at minimum, characterize such bias in their reported results.

Managing Pandemic Threats-The Need for Adaptive Leadership

The threat of the H5N1-influenza virus prompts reflection on COVID-19 pandemic experiences. This paper integrates insights from a first responder using the Cynefin framework to advocate for an adaptive strategic approach to future pandemics. Balancing individual freedoms with containment measures serves to leverage the human capital needed for rapid learning and resource distribution. The Cynefin framework aids in understanding complex problem-solving dynamics which involve varying degrees of order and chaos. Hierarchies in the ordered world support heterarchies which explore the unordered world. Both operate within scale free human systems which must adapt to existential challenges such as pandemics. Experience leading to knowledge and understanding occurs simultaneously at all dimensions of human existence. Ultimately, adaptive leadership and decentralized decision-making, supported by the best available knowledge, enable effective pandemic management and restoration of normal societal functions.

The present value of human life losses associated with COVID-19 and likely productivity losses averted through COVID-19 vaccination in Madagascar

BACKGROUND

As of 3 March 2023, Madagascar had reported 1,422 deaths from COVID-19. Up to now, there hasn't been a study to estimate the Total Present Value of Human Life lostTPVHL MADAGASCAR , productivity losses, and potential productivity losses averted through COVID-19 vaccination for use in advocacy. The study reported in this paper aimed to fill these information gaps.

METHODS

The Human Capital Model (HCM) was used to estimate theTPVHL MADAGASCAR , which is the sum of the discounted value of human life losses among individuals in seven different age groups. The Present Value of Human Life for each age groupPVHL i was calculated by multiplying the discount factor, the undiscounted years of life, the non-health gross domestic product (GDP) per capita, and the number of COVID-19 deaths in that age group. To test the robustness of the results, the HCM was rerun five times, assuming (i) a 5% discount rate, (ii) a 10% discount rate, (iii) Africa's highest average life expectancy at birth of 78.76 years, (iv) the world's highest life expectancy of 88.17 years, (v) projected excess COVID-19 mortality of 11,418.66 deaths as of 3 March 2023 in Madagascar, and assuming different levels of vaccine coverage: 100%, 70%, 60.93%, and 8.266%.

RESULTS

The 1,422 human lives lost due to COVID-19 had aTPVHL MADAGASCAR of Int$ 46,331,412; and an average of Int$ 32,582 per human life. Re-estimation of the HCM, using (i) discount rates of 5% and 10% reducedTPVHL MADAGASCAR by 23% and 53%, respectively; (ii) average life expectancies of 78.76 years and 88.17 years increasedTPVHL MADAGASCAR by 23.7% and 39.5%, respectively; (iii) projected excess COVID-19 mortality of 11,418.66 augmentedTPVHL MADAGASCAR by 703%. Furthermore, it is estimated that vaccinating 70% of the target population could potentially save the country Int$ 1.1 billion, equivalent to 1.94% of the GDP.

CONCLUSIONS

The COVID-19 pandemic has resulted in significant health and productivity losses for Madagascar. Optimizing COVID-19 vaccination coverage for the target population could substantially reduce these losses.

The role of economic evaluation in modelling public health and social measures for pandemic policy: a systematic review

BACKGROUND

Dynamic transmission models are often used to provide epidemiological guidance for pandemic policy decisions. However, how economic evaluation is typically incorporated into this technique to generate cost-effectiveness estimates of pandemic policy responses has not previously been reviewed.

METHODS

We systematically searched the Embase, PubMed and Scopus databases for dynamic epidemiological modelling studies that incorporated economic evaluation of public health and social measures (PHSMs), with no date restrictions, on 7 July 2024.

RESULTS

Of the 2,719 screened studies, 51 met the inclusion criteria. Most studies (n = 42, 82%) modelled SARS-CoV-2. A range of PHSMs were examined, including school closures, testing/screening, social distancing and mask use. Half of the studies utilised an extension of a Susceptible-Exposed-Infectious-Recovered (SEIR) compartmental model. The most common type of economic evaluation was cost-effectiveness analysis (n = 24, 47%), followed by cost-utility analysis (n = 17, 33%) and cost-benefit analysis (n = 17, 33%).

CONCLUSIONS

Economic evaluation is infrequently incorporated into dynamic epidemiological modelling studies of PHSMs. The scope of this research should be expanded, given the substantial cost implications of pandemic PHSM policy responses.

Core health system measures response to COVID-19 among East Asian countries

Objective

The purpose of this study is to summarize the health system response to COVID-19 in four East Asian countries, analyze the effectiveness of their health system response, and provide lessons for other countries to control the epidemic and optimize their health system response.

Methods

This study investigated and summarized COVID-19 data and health system response in four East Asian countries, China, Japan, Mongolia, and South Korea from national governments and ministries of health, WHO country offices, and official websites of international organizations, to assess the effectiveness of health system measures.

Result

As of June 30, 2022, all four countries are in a declining portion of COVID-19. China has two waves, and new cases increased slowly, with the total cases per million remaining within 4, indicating a low level. Japan has experienced six waves, with case growth at an all-time high, total cases per million of 250.994. Mongolia started the epidemic later, but also experienced four waves, with total cases per million of 632.658, the highest of the four countries. South Korea has seen an increasing number of new cases per wave, with a total case per million of 473.759.

Conclusion

In containment strategies adopted by China and Mongolia, and mitigation strategies adopted by Japan and South Korea, health systems have played important roles in COVID-19 prevention and control. While promoting vaccination, countries should pay attention to non-pharmaceutical health system measures, as evidenced by: focusing on public information campaigns to lead public minds; strengthening detection capabilities for early detection and identification; using technical ways to participate in contact tracing, and promoting precise judging isolation.

Lessons Learned from Model-based Economic Evaluations of COVID-19 Drug Treatments Under Pandemic Circumstances: Results from a Systematic Review

BACKGROUND

Following clinical research of potential coronavirus disease 2019 (COVID-19) treatments, numerous decision-analytic models have been developed. Due to pandemic circumstances, clinical evidence was limited and modelling choices were made under great uncertainty. This study aimed to analyse key methodological characteristics of model-based economic evaluations of COVID-19 drug treatments, and specifically focused on modelling choices which pertain to disease severity levels during hospitalisation, model structure, sources of effectiveness and quality of life and long-term sequelae.

METHODS

We conducted a systematic literature review and searched key databases (including MEDLINE, EMBASE, Web of Science, Scopus) for original articles on model-based full economic evaluations of COVID-19 drug treatments. Studies focussing on vaccines, diagnostic techniques and non-pharmaceutical interventions were excluded. The search was last rerun on 22 July 2023. Results were narratively synthesised in tabular form. Several aspects were categorised into rubrics to enable comparison across studies.

RESULTS

Of the 1047 records identified, 27 were included, and 23 studies (85.2%) differentiated patients by disease severity in the hospitalisation phase. Patients were differentiated by type of respiratory support, level of care management, a combination of both or symptoms. A Markov model was applied in 16 studies (59.3%), whether or not preceded by a decision tree or an epidemiological model. Most cost-utility analyses lacked the incorporation of COVID-19-specific health utility values. Of ten studies with a lifetime horizon, seven adjusted general population estimates to account for long-term sequelae (i.e. mortality, quality of life and costs), lasting for 1 year, 5 years, or a patient's lifetime. The most often reported parameter influencing the outcome of the analysis was related to treatment effectiveness.

CONCLUSION

The results illustrate the variety in modelling approaches of COVID-19 drug treatments and address the need for a more standardized approach in model-based economic evaluations of infectious diseases such as COVID-19.

TRIAL REGISTRY

Protocol registered in PROSPERO under CRD42023407646.

The Impacts of COVID-19 Restrictions on Quality Adjusted Life Years (QALY): Heterogeneous effects and post-pandemic recovery

OBJECTIVES

Estimate the effects of non-pharmacological interventions used to prevent the spread of COVID-19 on the quality of life, measured by Quality Adjusted Life Years (QALYs).

METHODS

A survey on 1,506 heads of households from Chile in May of 2022. Respondents were asked basic socioeconomic questions and a version of the EQ-5D-5L questionnaire that was used to calculate the evolution of HRQoLs. Comparisons of means in HRQoLs measures before the pandemic, at the peak of restrictions, and at the moment of the survey were performed.

RESULTS

The average HRQoL of the population before the pandemic was similar to other countries in the region (0.96). At the peak of restrictions (June 2020-August 2021), the average HRQoL decreased to 0.87 (-9%). At the time of survey (May 2022), the average HQRoL was 0.91 (4%). Assuming the recovery trend continued, pre-pandemic HRQoLs would be reached by January 2024. Altogether, the pandemic would have reduced QALYs by 0.2 in average. The effect is larger and the recovery slower among women. Our estimates imply that the restrictions to manage the pandemic came at a cost of 2.4 months of life years for the average (surviving) person, 1.8 months for men and 3.4 for women.

CONCLUSIONS

Our results suggest that COVID-19 had worse effects on life quality than previously thought. These effects are more significant among women than among men. Efforts to improve life quality and speed up its recovery could have large positive consequences for the population.

Quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes

Background: Novel therapies in metastatic cancers have contributed to improvements in survival outcomes, yet real-world data suggest that improvements may be mainly driven by those patient groups who already had the highest survival outcomes. This study aimed to develop and apply a framework for quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes based on published aggregate data. Methods: Nine (N = 9) novel therapies for metastatic breast cancer (mBC), metastatic colorectal cancer (mCRC), and metastatic non-small cell lung cancer (mNSCLC) were identified, 3 for each cancer type. Individual patient data (IPD) for overall survival (OS) and progression-free survival (PFS) were replicated from published Kaplan-Meier (KM) curves. For each cancer type, data were pooled for the novel therapies and comparators separately and weighted based on sample size to ensure equal contribution of each therapy in the analyses. Parametric (mixture) distributions were fitted to the weighted data to model and extrapolate survival. The inequality in survival was defined by the absolute difference between groups with the highest and lowest survival for 2 stratifications: one for which survival was stratified into 2 groups and one using 5 groups. Additionally, a linear regression model was fitted to survival estimates for the 5 groups, with the regression coefficient or slope considered as the inequality gradient (IG). The impact of the pooled novel therapies was subsequently defined as the change in survival inequality relative to the pooled comparator therapies. A probabilistic analysis was performed to quantify parameter uncertainty. Results: The analyses found that novel therapies were associated with significant increases in inequalities in survival outcomes relative to their comparators, except in terms of OS for mNSCLC. For mBC, the inequalities in OS increased by 13.9 (95% CI: 1.4; 26.6) months, or 25.0%, if OS was stratified in 5 groups. The IG for mBC increased by 3.2 (0.3; 6.1) months, or 24.7%. For mCRC, inequalities increased by 6.7 (3.0; 10.5) months, or 40.4%, for stratification based on 5 groups; the IG increased by 1.6 (0.7; 2.4) months, or 40.2%. For mNSCLC, inequalities decreased by 14.9 (-84.5; 19.0) months, or 12.2%, for the 5-group stratification; the IG decreased by 2.0 (-16.1; 5.1) months, or 5.5%. Results for the stratification based on 2 groups demonstrated significant increases in OS inequality for all cancer types. In terms of PFS, the increases in survival inequalities were larger in a relative sense compared with OS. For mBC, PFS inequalities increased by 8.7 (5.9; 11.6) months, or 71.7%, for stratification based on 5 groups; the IG increased by 2.0 (1.3; 2.6) months, or 67.6%. For mCRC, PFS inequalities increased by 5.4 (4.2; 6.6) months, or 147.6%, for the same stratification. The IG increased by 1.3 (1.1; 1.6) months, or 172.7%. For mNSCLC, inequalities increased by 18.2 (12.5; 24.4) months, or 93.8%, for the 5-group stratification; the IG increased by 4.0 (2.8; 5.4) months, or 88.1%. Results from the stratification based on 2 groups were similar. Conclusion: Novel therapies for mBC, mCRC, and mNSCLC are generally associated with significant increases in survival inequalities relative to their comparators in randomized controlled trials, though inequalities in OS for mNSCLC decreased nonsignificantly when stratified based on 5 groups. Although further research using real-world IPD is warranted to assess how, for example, social determinants of health affect the impact of therapies on health inequalities among patient groups, the proposed framework can provide important insights in the absence of such data.

Economic Evaluations of Guideline-Directed Medical Therapies for Heart Failure With Reduced Ejection Fraction: A Systematic Review

OBJECTIVES

Decision-analytic models (DAMs) with varying structures and assumptions have been applied in economic evaluations (EEs) to assist decision making for heart failure with reduced ejection fraction (HFrEF) therapeutics. This systematic review aimed to summarize and critically appraise the EEs of guideline-directed medical therapies (GDMTs) for HFrEF.

METHODS

A systematic search of English articles and gray literature, published from January 2010, was performed on databases including MEDLINE, Embase, Scopus, NHSEED, health technology assessment, Cochrane Library, etc. The included studies were EEs with DAMs that compared the costs and outcomes of angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, angiotensin-receptor neprilysin inhibitors, beta-blockers, mineralocorticoid-receptor agonists, and sodium-glucose cotransporter-2 inhibitors. The study quality was evaluated using the Bias in Economic Evaluation (ECOBIAS) 2015 checklist and Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklists.

RESULTS

A total of 59 EEs were included. Markov model, with a lifetime horizon and a monthly cycle length, was most commonly used in evaluating GDMTs for HFrEF. Most EEs conducted in the high-income countries demonstrated that novel GDMTs for HFrEF were cost-effective compared with the standard of care, with the standardized median incremental cost-effectiveness ratio (ICER) of $21 361/quality-adjusted life-year. The key factors influencing ICERs and study conclusions included model structures, input parameters, clinical heterogeneity, and country-specific willingness-to-pay threshold.

CONCLUSIONS

Novel GDMTs were cost-effective compared with the standard of care. Given the heterogeneity of the DAMs and ICERs, alongside variations in willingness-to-pay thresholds across countries, there is a need to conduct country-specific EEs, particularly in low- and middle-income countries, using model structures that are coherent with the local decision context.

Accounting for Nonhealth and Future Costs in Cost-Effectiveness Analysis: Distributional Impacts of a US Cancer Prevention Strategy

OBJECTIVE

To provide up-to-date and comprehensive US data tables to estimate future net resource use, including nonlabor market production, and examine distributional impacts of including nonhealth and future costs in cost-effectiveness results.

METHODS

Using a published US cancer prevention simulation model, the paper evaluated the lifetime cost effectiveness of implementing a 10% excise tax on processed meats across age- and sex-specific population subgroups. The model examined multiple scenarios accounting for cancer-related healthcare expenditure (HCE) only, cancer-related and unrelated background HCE, adding productivity benefits (i.e., patient time, cancer-related productivity loss, and background labor and nonlabor market production), and with nonhealth consumption costs, adjusted for household economies of scale. Additional analyses include using population-average versus age-sex-specific estimates for quantifying production and consumption value, as well as comparing direct model estimation versus postcorrections with Meltzer's approximation for incorporating future resource use.

RESULTS

Accounting for nonhealth and future costs impacted cost-effectiveness results across population subgroups, often leading to changes in "cost-saving" determination. Including nonlabor market production had a noticeable impact on estimating future resource use and reduced the bias toward undervaluing productivity among females and older populations. The use of age-sex-specific estimates resulted in less favorable cost-effectiveness results compared with population-average estimates. Meltzer's approximation provided reasonable corrections among the middle-aged population for re-engineering cost-effectiveness ratios from a healthcare sector to a societal perspective.

CONCLUSION

With updated US data tables, this paper can help researchers conduct a comprehensive value assessment to reflect net resource use (health and nonhealth resource use minus production value) from a societal perspective.

Experiences of aftermath of COVID-19 in relation to social, financial and health related aspects among previously hospitalized patients: a qualitative exploration

Background

There is increasing evidence of long-term consequences of COVID-19. The world has seen multidimensional impact of the pandemic and Bangladesh is no exception to that. Policymakers in Bangladesh laid out strategies to curb the initial spread of COVID-19. However, long-term consequences of COVID-19 received little or no attention in the country. Evidence suggests that people presumed to be recovered face multidimensional post-covid consequences. This study aimed to describe the aftermath of COVID-19 in relation to social, financial and health related aspects among previously hospitalized patients.

Methods

This descriptive qualitative study includes participants (n = 14) who were previously hospitalized for COVID-19 and returned home after recovery. The participants were part of a mixed method study from which they were purposively selected. Semi-structured in-depth interviews were conducted over telephone. Inductive content analysis was used to analyze the data.

Results

Twelve sub-categories emerged from the data analysis which converged into five main categories. The main categories included perspective on physical health, financial struggle, life adjustment, interplay between different domains, and spontaneous support.

Conclusion

The lived experiences of COVID-19 recovered patients highlighted multidimensional impact on their daily lives. Physical and psychological wellbeing found to be related to the effort of restoring financial status. People's perception about life altered due to pandemic, for few the pandemic was an opportunity to grow while others found it difficult to accept the hardship. Such multidimensional post COVID-19 impact on people's lives and wellbeing holds considerable implication for response and mitigation plan for future related pandemics.

Estimating loss in capability wellbeing in the first year of the COVID-19 pandemic: a cross-sectional study of the general adult population in the UK, Australia and the Netherlands

OBJECTIVES

To estimate capability wellbeing lost from the general adult populations in the UK, Australia and the Netherlands in the first year of the COVID-19 pandemic and the associated social restrictions, including lockdowns.

DESIGN

Cross-sectional with recalled timepoints.

SETTING

Online panels in the UK, Australia and the Netherlands conducted in February 2021 (data collected 26 January-2 March 2021).

PARTICIPANTS

Representative general adult (≥ 18 years old) population samples in the UK (n = 1,017), Australia (n = 1,011) and the Netherlands (n = 1,017) MAIN OUTCOME MEASURE: Participants completed the ICECAP-A capability wellbeing measure in February 2021, and for two recalled timepoints during the initial lockdowns in April 2020 and in February 2020 (prior to COVID-19 restrictions in all three countries). ICECAP-A scores on a 0-1 no capability-full capability scale were calculated for each timepoint. Societal willingness to pay estimates for a year of full capability (YFC) was used to place a monetary value associated with change in capability per person and per country. Paired t tests were used to compare changes in ICECAP-A and YFC from pre- to post-COVID-19-related restrictions in each country.

RESULTS

Mean (standard deviation) loss of capability wellbeing during the initial lockdown was 0.100 (0.17) in the UK, 0.074 (0.17) in Australia and 0.049 (0.12) in the Netherlands. In February 2021, losses compared to pre-lockdown were 0.043 (0.14) in the UK, 0.022 (0.13) in Australia and 0.006 (0.11) in the Netherlands. In monetary terms, these losses were equivalent to £14.8 billion, AUD$8.6 billion and €2.1 billion lost per month in April 2020 and £6.4 billion, A$2.6 billion and €260 million per month in February 2021 for the UK, Australia and the Netherlands, respectively.

CONCLUSIONS

There were substantial losses in capability wellbeing in the first year of the COVID-19 pandemic. Future research is required to understand the specific impact of particular COVID-19 restrictions on people's capabilities.

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

OBJECTIVES

We conducted a distributional cost-effectiveness analysis (DCEA) to evaluate how Medicare funding of inpatient COVID-19 treatments affected health equity in the United States.

METHODS

A DCEA, based on an existing cost-effectiveness analysis model, was conducted from the perspective of a single US payer, Medicare. The US population was divided based on race and ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and county-level social vulnerability index (5 quintile groups) into 15 equity-relevant subgroups. The baseline distribution of quality-adjusted life expectancy was estimated across the equity subgroups. Opportunity costs were estimated by converting total spend on COVID-19 inpatient treatments into health losses, expressed as quality-adjusted life-years (QALYs), using base-case assumptions of an opportunity cost threshold of $150 000 per QALY gained and an equal distribution of opportunity costs across equity-relevant subgroups.

RESULTS

More socially vulnerable populations received larger per capita health benefits due to higher COVID-19 incidence and baseline in-hospital mortality. The total direct medical cost of inpatient COVID-19 interventions in the United States in 2020 was estimated at $25.83 billion with an estimated net benefit of 735 569 QALYs after adjusting for opportunity costs. Funding inpatient COVID-19 treatment reduced the population-level burden of health inequality by 0.234%. Conclusions remained robust across scenario and sensitivity analyses.

CONCLUSIONS

To the best of our knowledge, this is the first DCEA to quantify the equity implications of funding COVID-19 treatments in the United States. Medicare funding of COVID-19 treatments in the United States could improve overall health while reducing existing health inequalities.