Abstract
Objectives
Methods
Results
Conclusions
Keywords
Introduction
- Chalkidou K.
- Walker D.
- Sullivan R.
- et al.
- Elvidge J.
- Summerfield A.
- Knies S.
- et al.
Methods
Selection of Literature Databases
Search Strategy
- Elvidge J.
- Summerfield A.
- Nicholls D.
- Dawoud D.
Selection Criteria
- 1.The target population was people with a different condition.
- 2.The intervention was prophylactic (eg, vaccination program).
- 3.The intervention was a public health measure (eg, lockdown measures, population screening).
- 4.Epidemiological modeling studies without an economic evaluation.
- 5.Partial economic evaluations.
- 6.Poster abstracts that lacked methodological detail.
- 7.Letters to the editor, commentaries, and analysis articles.
Quality Assessment
Data Extraction
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Study | Country | Currency (cost year) | Population/setting | Interventions and comparators | Evaluation type | Analysis approach | Perspective | Time horizon | Costs included | Discounting | Health outcomes | Source of efficacy data | Source of utility data (if relevant) | Uncertainty analyses |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Águas et al (2021) 24 | UK | GBP (2020) | Hospitalized patient who needs supplemental oxygen | Dexamethasone vs SoC | CEA | Decision tree algorithm | Provider (healthcare) | Lifetime | Inpatient costs, intervention | NR | LYG | RCT: Recovery | NA | Probabilistic and limited one-way (Dex efficacy) analyses |
I.C.E.R. (2020) 25 | US | USD (NR) | Hospitalized patient (moderate to severe – respiratory support; mild – no respiratory support) | Remdesivir + SoC (inc Dex) vs SoC | CUA | Markov model with 1-mo cycles (cycle 1 in hospital) | Payer (bundled insurance payments) | Lifetime | Inpatient costs, interventions (Rem course $3990 in moderate to severe, $2750 in mild) | 3% | LYG, QALYs | RCTs: ACTT1, NCT04292730, Recovery, WHO Solidarity. | Age-adjusted general population. Disutilities for symptoms 0.19, hospitalization 0.30, oxygen 0.50, ventilation 0.60 from literature | Scenario and price-threshold analyses |
Jo et al (2021) 26 | South Africa | USD (2020) | ICU, V and NV patients | Dex (V) and Rem (NV) Dex (V and NV) Rem (NV) Dex (V) SoC | CEA | Cost-effectiveness analysis based on projections from National COVID-19 Epidemiology Model | Healthcare system | 6 months (August 2020 to January 2021) | ICU cost per day (capital, staff, overheads); interventions (Dex course $31, Rem course $330) | 5% (to estimate cost annualized cost of capital expenditure) | Deaths averted | RCTs: ACTT1, Recovery, WHO Solidarity. | NA | Probabilistic, one-way and scenario analyses |
Padula et al (2020) 27 Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021. | US | USD (2020) | Mild disease, community setting (not hospitalized) | Hypothetical antiviral treatment vs “do nothing” strategy | CUA | Markov model (10 states) with 1-day cycles | Societal | 1 year | Primary, secondary, emergency and critical care; medications; productivity loss; intervention ($1000) | 3% | QALYs | RCT: zanamivir for influenza | Mild disease 0.614 (source unclear); moderate 0.5, severe 0.25, critical 0.05 (literature; lower bounds of values for SARS from 4 clinical experts) | Probabilistic, one-way and scenario analyses |
Sheinson et al (2021) 28 | US | USD (2020) | Hospitalized patients (age 62.5, male 64%) | Hypothetical treatment vs SoC | CUA | Short-term decision tree (hospital) and long-term 3-state Markov cohort model with 1-year cycles | Three: payer (bundled insurance payments), societal, fee for service | Lifetime | Inpatient costs, unrelated long-term costs, hypothetical intervention ($2500), productivity loss | 3% | LYG, QALYs | RCTs: Covid-NMA, BMJ living NMA, ACTT1, Recovery, WHO Solidarity. | Age-adjusted general population. Disutilities for symptoms 0.27, hospitalization 0.11, oxygen 0.36, ventilation 0.56, and 5 years postdischarge (0.13-0.02, ARDS) from literature | Probabilistic, one-way and scenario analyses |
Stevenson et al (2021) 29 Emergency department | UK | GBP (2020) | Patients attending ED | Hypothetical rapid point-of-care tests vs laboratory tests | CUA | Individual patient model, including transmission within and between patients and staff in the hospital | Healthcare system | ED simulated for 90 days; patient care up to 200 days; lifetime QALYs projected | ICU admission; tests (including staff time) | 3.5% | NMB | Symptomatic patient: Laboratory tests: Sensitivity 95%-99% (MHRA target criteria) or 89% (meta-analysis). Specificity 100% (Foundation for Innovative New Diagnostics). Rapid POC test: Sensitivity 71-86% (MHRA target criteria) or 84.7% (real-world data). Specificity 95-99% (MHRA target criteria). Asymptomatic patient: Sensitivity 17.4% lower | Age- and sex-adjusted general population EQ-5D. 20% utility reduction following ICU (assumed) | Probabilistic simulation. Scenario analyses |
Stevenson et al (2021) 30 Residential care home | UK | GBP (2020) | Residents in a care home for older people | Hypothetical rapid point-of-care tests vs laboratory tests. Lateral flow tests included in sensitivity analysis | CUA | Individual patient model, including transmission within and between residents and staff in the care home | Healthcare system | Care home simulated for 90 days, then lifetime QALYs projected | Testing (unit costs equal in base case) | 3.5% | NMB | As in Stevenson et al (2021) 30 (emergency department), except MHRA target sensitivity for POC test increased to 80%-97%. | Age- and sex-adjusted general population EQ-5D. Isolation: 0.25 (assumed: worsening of anxiety/depression and 50-50 split between no/some problems at baseline). A total of 10% utility reduction following hospitalization (assumed) | Probabilistic simulation. Scenario analyses |
Study | Cost and health outcome results (USD, 2020) | ICER/net benefit of interventions vs comparators | Cost-effectiveness threshold (if relevant) | Sensitivity and scenario analyses | Authors’ conclusions regarding cost effectiveness | Authors’ reported limitations and challenges |
---|---|---|---|---|---|---|
Águas et al (2021) 24 | Dex vs SoC Incremental cost: $117m (90% CI $8.3-$455m). LYG: 102K (90% CI 37K-240K). Results assume 5-15% COVID-19 exposure. | $1300/LYG (90% CI $90/LYG-$2800/LYG) | $0 to $3000/LYG | PSA: 95% of ICERs < $2000/LYG. Scenarios exploring Dex efficacy in people who need but cannot access oxygen (base case = 100%): 25%, 50% and 75%. ICER remains $700-800/LYG. | Dex can be highly cost effective if given to hospitalized patients with COVID-19 requiring oxygen therapy. | NR |
I.C.E.R. (2020) 25 | Moderate to severe LYs: SoC = Rem = 15.164. QALYs: SoC 12.182; Rem 12.189 (+0.006). Costs: SoC $311 620; Rem $313 450 (+1830). Rem course: $3990. Mild LYs: SoC = Rem = 16.997. QALYs: SoC 13.703; Rem 13.704 (+0.001). Costs: SoC $315 630; Rem $318 380 (+2750). Rem course: $2750. | Moderate to severe: £298 160/QALY Mild: $1.85m/QALY | $50K/QALY: Rem price $2470 (moderate to severe), $70 (mild). $100K/QALY: Rem price $2770 (moderate to severe), $150 (mild). $150K/QALY: Rem price $3080 (moderate to severe), $220 (mild). | Scenario with Rem survival benefit (HR = 0.84): $50K/QALY: Rem course $3980-4140 (moderate to severe), $690-760 (mild). $100K/QALY: Rem course $8750-9080 (moderate to severe), $2620-2740 (mild). $150K/QALY: Rem course $13 520-$14 020 (moderate to severe), $4540-4720 (mild). No PSA reported. | The pricing estimate related to the threshold of $50K/QALY is the most policy-relevant consideration. This suggests a price of $2470 per Rem course for moderate to severe (vs actual $3990) and $70 for mild (vs actual $2750). | Important uncertainty remains regarding relative clinical effects and composition of hospitalizations by COVID-19 severity; hospitalization costs; long-term cost and health outcomes; evidence for other interventions. |
Jo et al (2021) 26 | SoC: $83 937. Dex (V) and Rem (NV): $69.3m; 408 deaths averted (vs SoC). Dex (N and NV): $84.1m; 689 DA (vs SoC). Rem (NV): $69.3m; 26 DA (vs SoC). Dex (V): $84.0m; 382 DA (vs SoC). | All vs SoC Dex (V) and Rem (NV): dominant Dex (V and NV): $231/DA Rem (NV): dominant. Dex (V): $174/DA Fully incremental analysis: Dex (V) and Rem (NV): $175/DA; Dex (V) and Rem (NV): £52 491/DA Rem averts deaths by reducing LoS (15 d to 10 d), thereby reducing duration of ICU capacity breach | $36K/death averted (from £3K/DALY averted, assuming average discounted life expectancy = 17 years (12 DALYs per death)). | Dex (V) and Rem (NV) no longer cost saving if ICU capacity is breached for 6 months. Rem not cost saving if ICU always at full capacity. Otherwise, cost saving even if LoS reduction is 1 day. PSA, Dex (V and NV): ∼100% ICERs < $1000/death averted. Rem strategies: ∼75% ICERs dominant. If Rem mortality efficacy is 30% (instead of 0%), fully incremental analysis: Dex (V) and Rem (NV) ICER: $78/DA. | Dex (V) and Rem (NV) could avert 408 deaths and save $15 million vs SoC. Dex (V and NV) would maximize deaths averted (689) at an incremental cost of $159K. | Confounding factors not captured can influence ICU capacity breaches: epidemic conditions, system capacity, policy. Did not consider changes in disease progression or severity, eg, time since symptom onset, age, comorbidities, adverse events, other medications. Cost associated with adverse events were not included. Time horizon was limited to projections from the NCEM. |
Padula et al (2020) 27 Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021. | Hypothetical antiviral treatment: $1299, 0.877 QALYs. Do nothing: $2115, 0.874 QALYs. | Dominant (lower cost, higher QALYs) | $50K/QALY | PSA: treatment almost certainly cost effective vs no treatment. Results most sensitive to treatment efficacy. | A treatment for COVID-19 presents excellent value to the US healthcare system and economy, if it is priced between $750 and $1250. | Probabilities are not time dependent, because of limited understanding of the disease. Risks and effects assumed equal for all groups and ages. Static population, with no death from other causes. Utilities obtained from non-COVID-19 population (SARS). Not all cost items relevant to healthcare system are captured. |
Sheinson et al (2021) 28 | LYs: SoC 12.423; tmt 12.961 (+0.538). QALYs: SoC 9.790; tmt 10.228 (+0.438). Costs Payer: SoC $277 978; tmt $288 005 (+10 027). Payer and societal: SoC $301 259; tmt $306 284 (+5025). FFS: SoC $281 684; tmt $290 196 (+8512). FFS and societal: SoC $304 965; tmt $308 475 (+3510). | Payer: $22 933/QALY Payer and societal: $11 492/QALY FFS: $19 469/QALY FFS and societal: $8028/QALY | $100K/QALY → FFS VBP = £37 710 $150K/QALY → FFS VBP = $59 572 | All OWSA < £50K/QALY. Most sensitive parameter varies by perspective, eg, societal, age at death: 95 y → £18 632; 64 y → dominant. If no LoS benefit: FFS ICER ↑50%: $29 108. PSA (n = 5000), > 99% ICERs < $100K/QALY, max 95% upper bound: payer → $30 937. Almost all results in NEQ. | Potential treatments reducing LoS, mortality, and mechanical ventilation use are likely to be cost effective, at a cost of $2500 per course. | The COVID-19 evidence base is immature, so the model may need to evolve in complexity as data emerge. Examines a hypothetical treatment with a proxy drug cost, rather than an actual potential treatment. Uncertainty exists for mechanical ventilation and long-term outcomes (used ARDS data instead). |
Stevenson et al (2021) 29 Emergency department | (From 22 500 patients entering the model in 90 days:) Laboratory test with 6-h results: $214K, 11.5 QALYs lost. Rapid test with desirable TPP: $275K, 10.5 QALYs lost. Rapid test with acceptable TPP: $272K, 14.2 QALYs lost. Laboratory test (6 h) with weekly testing of asymptomatic staff: $307K, 9.4 QALYs lost. | Highest NMB strategies: At $69K/QALY: laboratory test (6 h) with weekly testing of asymptomatic staff ∼$320K. At $42K/QALY: laboratory test (6 h), ∼$260K. At $28K/QALY: “no testing” strategy, ∼$80K (laboratory test [6 h] provides highest NMB among strategies with testing) | $69K/QALY, $42K/QALY and $28K/QALY (used in NICE appraisals). | Results highly sensitive to test costs (if equal, rapid test with desirable TPP has highest NMB at $42K/QALY; including weekly testing of asymptomatic staff at $69K/QALY). Results sensitive to risk of a hospitalized patient needing ICU care (90% risk reduction → testing has much lower NMB). Various scenario analyses comparing “plausible” strategies (1 lab, 2 POC). In general, laboratory test (24 h) highest NMB at $42K/QALY, POCs (including weekly for asymptomatic staff) highest NMB at $69K/QALY. If laboratory test results take 6 h or less, POC tests unlikely to have ICER < $42K. If laboratory test results take ≥ 16 h and POC test results take 6 h or less, POC tests likely to have ICER < $42K. | Given the heterogeneity of hospitals, no blanket solution can be provided. A POC test with a desirable TPP would appear to have a relatively high NMB, but this may be lower than a laboratory test with 6-h results. A POC test with an acceptable TPP would appear to have a lower NMB than a laboratory test with 24 h results. Testing asymptomatic staff and removing them from duty appears to have higher NMBs at higher cost/QALY thresholds. | The model did not consider hospitalization via a different route than ED; implications for people with existing respiratory diseases; testing at discharge; cost of shutting clinics because of an outbreak. Simplifying assumptions for rapid tests (eg, no dedicated staffing). Considerable uncertainty in input parameters. Some sampling error. |
Stevenson et al (2021) 30 Residential care home | (From 16 residents and 9 staff, using observed, real-world accuracy data, assuming facility is penetrated by 1 SARS-CoV-2 infection:) En suite care facility Rapid POC test: $7365, 2.37 QALYs lost. Laboratory test: $7786, 3.37 QALYs lost. Shared care facility Rapid POC test: $8090, 3.31 QALYs lost. Laboratory test: $7557, 2.97 QALYs lost. (Note: these results are erroneously transposed in primary study.) | At all thresholds, POC test with desirable TPP characteristics provides highest NMB. All testing strategies cause a gain in NMB if the facility has been penetrated by an infection. All testing strategies cause a reduction in NMB if the facility has not been penetrated by an infection, because of unnecessary test costs and isolation | $69K/QALY, $42K/QALY and $28K/QALY (used in NICE appraisals). | Results highly sensitive to diagnostic accuracy values and cost differential between the 2 types of test. Tests with desirable and observed accuracy may still have positive NMB if vaccination reduces the risk of critical care by up to 90% or reduces immunity by up to 90%. Regular lateral flow testing, with accuracy data from Public Health England and assuming $14 cheaper, may be cost effective (but this is exploratory, eg, assumes perfect adherence). | It is only possible to draw broad conclusions from this analysis. POC tests have considerable potential for benefit for use in residential care facilities, providing they are sufficiently accurate. | Unclear whether the MHRA criteria for a “desirable” test can or will be met; may be unrealistic. Limitations include residents not stratified by risk for COVID-19; facilities only penetrated by 1 case initially; model progression time of 6 h may be too long to capture very small time effects; cost of hospitalization not included (this will favor less accurate tests); societal and wider capacity effects not captured. |
Results
Included Studies
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
- Wu G.
- Wu G.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.

Study | Notable limitations identified | Assessment | Decision |
---|---|---|---|
Águas et al (2021) 24 | Estimates of relative treatment effect were derived from 1 randomized controlled trial. Some resource use inputs (hospital days) were derived from 1 early study in the Chinese setting. Tariff costs may not always reflect the true cost of providing healthcare in the UK. | Potentially serious limitations | Include |
Bastos et al (2021) 32 | The study did not provide a robust estimate of cost effectiveness because it did not account for false-positive test results of the diagnostic under evaluation. In addition, no longer-term costs or outcomes were included. The time horizon was not reported, although it appears to be short term, meaning the impact of potential longer-term effects of COVID-19 and treatment effects could not be explored. | Very serious limitations | Exclude |
I.C.E.R. (2020) 25 | The study did not capture the long-term effects of COVID-19 or treatment. Limited uncertainty analyses were reported; for example, probabilistic sensitivity analysis was not reported. | Potentially serious limitations | Include |
Jiang et al (2020) 33 | Several intervention effects, costs, and resource use inputs relevant to the treatment under evaluation were either omitted, and therefore could not be examined, or the input data were not taken from the best available sources. | Very serious limitations | Exclude |
Jiang et al (2021) 34 | The study did not provide a robust estimate of cost effectiveness. The published evidence used to inform the model does not show a survival benefit for the treatment under evaluation. Nevertheless, the model structure used generated substantial gains in life expectancy for the treatment because of an indirect survival benefit. This contradicts the underlying clinical evidence. | Very serious limitations | Exclude |
Jo et al (2021) 26 | The time horizon was 6 months, meaning the impact of potential longer-term effects of COVID-19 and treatment effects could not be explored. | Potentially serious limitations | Include |
Padula et al (2020) 27 Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021. | The time horizon was 1 year, meaning the impact of potential longer-term effects of COVID-19 and treatment effects could not be explored. Some data were from proxy (non-COVID) conditions, including relative effectiveness; nevertheless, the treatment under consideration was hypothetical. | Potentially serious limitations | Include |
Ricks et al (2021) 37 | Baseline outcomes were based on assumptions, and relative effectiveness estimates were derived from separate nonrandomized studies with no adjustment for confounding factors. Critical illness, including intensive care and ventilation, and recovery from COVID-19 were omitted. The time horizon was not reported, although it appears to be short term, meaning the impact of potential longer-term effects of COVID-19 and treatment effects could not be explored. An appropriate incremental cost-effectiveness analysis could not be calculated from the results. | Very serious limitations | Exclude |
Sheinson et al (2021) 28 | Some proxy data from related conditions were used. There is a potential conflict of interest because the study was sponsored by a manufacturer of a therapeutic for COVID-19 (tocilizumab); nevertheless, the treatment under consideration was hypothetical. | Potentially serious limitations | Include |
Sinha and Linas (2021) 35 | The study did not provide a robust estimate of cost effectiveness because several important and relevant costs were omitted. For example, the cost of an inpatient hospital admission only includes the cost of the treatment under evaluation. In addition, the source of the quality-of-life values used in the analysis is unclear, and they have not been subjected to sensitivity analysis. | Very serious limitations | Exclude |
Stevenson et al (2021) 29 Emergency department | Long-term effects of COVID-19 were only included for critical illness, by an assumed reduction in quality of life. Cost of intensive care was omitted, but this was informed by the simulation identifying negligible difference in length of intensive care stay between the strategies under consideration. | Minor limitations | Include |
Stevenson et al (2021) 30 Residential care home | Long-term effects of COVID-19 were only included for severe illness, by an assumed reduction in quality of life. Cost of hospitalization was omitted for simplicity, which will favor strategies that result in more infections. General population utility values may overstate the quality of life of elderly care home residents. | Potentially serious limitations | Include |
Wu et al (2021) 36
Cost effectiveness analysis of remdesivir in COVID-19 patients at a large academic medical center. Open Access Theses and Dissertations. https://oatd.org/ Date accessed: August 25, 2021 | The study did not provide a robust estimate of cost effectiveness. It used a 30-day time horizon for the model, which is insufficient to capture all relevant differences between the intervention and comparator groups. Longer-term outcomes would be expected to influence cost-effectiveness results because the authors assume the treatment under evaluation confers a survival benefit. | Very serious limitations | Exclude |
Cost Effectiveness
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Discussion
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
Padula WV, Malaviya S, Reid NM, Tierce J, Alexander G. Economic value of treatment and vaccine to address the COVID-19 pandemic: AU.S. Cost-Effectiveness and budget Impact Analysis. Published online June 1, 2020. http://dx.doi.org/10.2139/ssrn.3586694. Accessed April 26, 2021.
- Wu G.
Conclusions
Article and Author Information
Acknowledgment
Supplemental Materials
References
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- COVID-19 Health Economics: Looking Back and Scoping the FutureValue in HealthVol. 25Issue 5
- PreviewAs of March 2022, nearly 6 million people have died of COVID-19 globally.1 The COVID-19 pandemic has already gone through several distinct stages during the first 2 years, with noticeable health and health economics impact at each stage. The initial emergency stage resulted in lockdowns that incurred enormous societal costs, concerning gross domestic product reductions as well as (mental) health damages. Diagnostic tests were implemented on a never-before-seen scale in many healthcare systems, without health economics justification,2,3 as exemplified in a systematic review in this themed section.
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