Cost-Effectiveness of COVID-19 Policy Measures: A Systematic Review

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.

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.

Implementing a pilot study of COVID-19 self-testing in high-risk populations and remote locations: results and lessons learnt

BACKGROUND

Rapid antigen-detection tests for SARS-CoV-2 self-testing represent a useful tool for pandemic control and expanding access to community-level case screening. COVID-19 self-tests have been extensively used in high-income countries since 2021; however, their introduction and programmatic implementation in low- and middle-income countries was delayed. We aimed to identify and continuously improve a weekly COVID-19 self-testing model among staff at healthcare facilities and schools.

METHODS

This mixed-methods, observational prospective study was conducted in 5 healthcare centres and 24 schools in Georgia, between June and December 2022. The study comprised the integration of COVID-19 self-testing into the national mandatory testing programme for high-risk groups, with primary distribution of self-tests among staff performed weekly, plus secondary distribution to their household members. These use cases were selected because NCDC was seeking to strengthen their already strong weekly testing programme, by investigating self-testing to ease the burden of testing in the healthcare system. Online surveys and semi-structured interviews were used for data collection.

RESULTS

In total, 2156 participants were enrolled (1963 female, 72%). At baseline and mid- and end-points, 88%, 97% and 99%, respectively, of participants agreed/strongly agreed they would self-test. Similarly, the majority were willing to report their self-testing results (88%, 98% and 96% at baseline and mid- and end-points, respectively). Weekly reporting of test results to the national COVID-19 database was high during all the implementation. There were 622 COVID-19 positive results reported, and linked to care, from 601 individuals (282 participants and 319 household members). Findings from qualitative interviews showed great satisfaction with self-testing for its convenience, ease of use, trust in the results, no need to travel for diagnostics, and increased perception of safety.

CONCLUSIONS

Our findings contribute to the evidence-base regarding self-testing strategies conducted via workplaces and secondary distribution to households. Willingness to perform a COVID-19 self-test increased after implementation. This pilot enhanced pandemic preparedness through expansion of the national self-testing reporting system, development of communications materials, changes in the national legal framework and coordination mechanisms, and improved perceptions around self-care in the community. The lessons learnt can inform operational aspects of the introduction and scale-up of self-care strategies.

Mitigating the COVID-19 Pandemic through Data-Driven Resource Sharing

COVID-19 outbreaks in local communities can result in a drastic surge in demand for scarce resources such as mechanical ventilators. To deal with such demand surges, many hospitals (1) purchased large quantities of mechanical ventilators, and (2) canceled/postponed elective procedures to preserve care capacity for COVID-19 patients. These measures resulted in a substantial financial burden to the hospitals and poor outcomes for non-COVID-19 patients. Given that COVID-19 transmits at different rates across various regions, there is an opportunity to share portable healthcare resources to mitigate capacity shortages triggered by local outbreaks with fewer total resources. This paper develops a novel data-driven adaptive robust simulation-based optimization (DARSO) methodology for optimal allocation and relocation of mechanical ventilators over different states and regions. Our main methodological contributions lie in a new policy-guided approach and an efficient algorithmic framework that mitigates critical limitations of current robust and stochastic models and make resource-sharing decisions implementable in real-time. In collaboration with epidemiologists and infectious disease doctors, we give proof of concept for the DARSO methodology through a case study of sharing ventilators among regions in Ohio and Michigan. The results suggest that our optimal policy could satisfy ventilator demand during the first pandemic's peak in Ohio and Michigan with 14% (limited sharing) to 63% (full sharing) fewer ventilators compared to a no sharing strategy (status quo), thereby allowing hospitals to preserve more elective procedures. Furthermore, we demonstrate that sharing unused ventilators (rather than purchasing new machines) can result in 5% (limited sharing) to 44% (full sharing) lower expenditure, compared to no sharing, considering the transshipment and new ventilator costs.

Mental health status and related factors influencing healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis

BACKGROUND

The mental health of healthcare workers during the coronavirus-2019 pandemic was seriously affected, and the risk of mental health problems was high. The present study sought to systematically evaluate the mental health problems of healthcare workers worldwide during the pandemic and to determine the latest global frequency of COVID-19 associated mental health problems.

METHODS

Data in the Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE, Elsevier, MEDLINE, PubMed, PsycINFO and the Web of Science before November 11, 2022, were systematically searched. Cohort, case-control and cross-sectional studies were included. The meta-analysis used a random effects model to synthesize the comprehensive prevalence rate of mental health problems. Subgroup analyses were performed based on time of data collection; whether the country was or was not developed; continent; doctors and nurses; doctors/nurses vs. other healthcare workers; and psychological evaluation scale.

RESULTS

A total of 161 studies were included, including 341,014 healthcare workers worldwide, with women accounting for 82.8%. Occupationally, 16.2% of the healthcare workers were doctors, 63.6% were nurses and 13.3% were other medical staff. During the pandemic, 47% (95% confidence interval [CI], 35-60%) of healthcare workers reported job burnout, 38% (95% CI, 35-41%) experienced anxiety, 34% (95% CI 30-38%) reported depression, 30% (95% CI, 29-31%) had acute stress disorder, and 26% (95% CI, 21-31%) had post-traumatic stress disorder.

CONCLUSIONS

The study found that there were common mental health problems among health care workers during the COVID-19 pandemic. The most common was job burnout, followed by anxiety, depression, acute stress and post-traumatic stress disorder. Although the global pandemic has been brought under control, its long-term impact on the mental health of healthcare workers cannot be ignored. Additional research is required to develop measures to prevent, monitor and treat psychological disorders among healthcare workers.

The evolution of the subjective well-being of the general population during the COVID-19 pandemic period: the case of Belgium

The consequences of the COVID-19 pandemic period on a nation's well-being remain inadequately understood, especially over time. Therefore, this research aims to map the changes in the subjective well-being (SWB) of the general Belgian adult population during the COVID-19 pandemic. Analyses of variances (ANOVA) were performed to evaluate the changes in SWB during the pandemic at five different time points during the period from February 2020 until December 2022 using repeated cross-sectional representative samples of the Belgian population. The differences over time in subjective well-being were investigated in terms of life evaluation, positive affect, and negative affect. The changes in autonomy, competence, relatedness, loneliness and peace of mind were also explored as explanatory variables. Moderation analyses were performed to investigate the differential changes in well-being for different age groups. Our results show the subjective well-being of the Belgian population decreased during the COVID-19 pandemic, notably during the second lockdown and the fifth wave. Furthermore, younger individuals are significantly more susceptible to negative changes in well-being during the pandemic period. Finally, our results show that peace of mind is an important predictor of all SWB components during the pandemic. Based on these results several policy recommendations are formulated.

Cost-effectiveness analysis of isolation strategies for asymptomatic and mild symptom COVID-19 patients

BACKGROUND

Management of COVID-19 patients with mild and moderate symptoms could be isolated at home isolation (HI), community isolation (CI) or hospitel. However, it was still unclear which strategy was more cost-effective. Therefore, this study was conducted to evaluate this.

METHODS

This study used data from patients who initially stayed at HI, CI, and hospitel under supervision of Ramathibodi Hospital between April and October 2021. Outcomes of interest were hospitalisation and mortality. An incremental cost-effectiveness ratios (ICER) was calculated based on hospital perspective using home isolation as the reference.

RESULTS

From 7,077 patients, 4,349 2,356, and 372 were admitted at hospitel, HI, and CI, respectively. Most patients were females (57.04%) and the mean age was 40.42 (SD = 16.15). Average durations of stay were 4.47, 3.35, and 3.91 days for HI, CI, and hospitel, respectively. The average cost per day for staying in these corresponding places were 24.22, 63.69, and 65.23 US$. For hospitalisation, the ICER for hospitel was at 41.93 US$ to avoid one hospitalisation in 1,000 patients when compared to HI, while CI had more cost, but less cases avoided. The ICER for hospitel and CI were at 46.21 and 866.17 US$ to avoid one death in 1,000 patients.

CONCLUSIONS

HI may be cost-effective isolated strategy for preventing hospitalisation and death in developing countries with limited resources.

Cost of the COVID-19 pandemic versus the cost-effectiveness of mitigation strategies in EU/UK/OECD: a systematic review

OBJECTIVES

The economic burden of COVID-19 pandemic is substantial, with both direct and indirect costs playing a significant role.

DESIGN

A systematic literature review was conducted to estimate the cost of the COVID-19 pandemic and the cost-effectiveness of pharmaceutical or non-pharmaceutical interventions. All cost data were adjusted to the 2021 Euro, and interventions compared with null.

DATA SOURCES

Ovid MEDLINE and EMBASE were searched from January 2020 through 22 April 2021.

ELIGIBILITY CRITERIA

Studies regarding COVID-19 outbreak or public health preparedness measures or interventions with outcome measures related to the direct and indirect costs for disease and preparedness and/or response in countries of the European Union (EU), the European Economic Area (EEA), the UK and the Organisation for Economic Co-operation and Development (OECD) of all relevant epidemiological designs which estimate cost within the selected time frame were considered eligible.

DATA EXTRACTION AND SYNTHESIS

Studies were searched, screened and coded independently by two reviewers with high measure of inter-rater agreement. Data were extracted to a predefined data extraction sheet. The risk of bias was assessed using the Consensus on Health Economic Criteria checklist.

RESULTS

We included data from 41 economic studies. Ten studies evaluated the cost of the COVID-19 pandemic, while 31 assessed the cost-benefit of public health surveillance, preparedness and response measures. Overall, the economic burden of the COVID-19 pandemic was found to be substantial. Community screening, bed provision policies, investing in personal-protective-equipment and vaccination strategies were cost-effective. Physical distancing measures were associated with health benefits; however, their cost-effectiveness was dependent on the duration, compliance and the phase of the epidemic in which it was implemented.

CONCLUSIONS

COVID-19 pandemic is associated with substantial short-term and long-term economic costs to healthcare systems, payers and societies, while interventions including testing and screening policies, vaccination and physical distancing policies were identified as those presenting cost-effective options to deal with the pandemic, dependent on population vaccination and the Re at the stage of the pandemic.

Cost-effectiveness of empagliflozin for the treatment of heart failure: a systematic review

Objective: This study aims to synthesize evidence on the cost-effectiveness of empagliflozin for heart failure (HF). Methods: MEDLINE, Embase, the Cochrane Library, EconLit, CNKI, Wanfang Data and Chongqing VIP were searched to identify original articles on cost-effectiveness of empagliflozin for HF, and literature surveillance ended on 20 November 2022. The reporting quality of the included articles was determined using the Consolidated Health Economic Evaluation Reporting Standards statement. Results: Of 97 articles identified, 11 studies published from 2020 to 2022 met the inclusion criteria, and the overall quality was accepted. The studies were conducted in 8 countries (China, Japan, Korea, Singapore, Thailand, Australia, United States, and United Kingdom). This body of evidence suggested that add-on empagliflozin was cost effective for HF with reduced ejection fraction (HFrEF) patients compared to standard of care alone in all the related studies including China, Japan, Korea, Singapore, Thailand, and Australia. For HF with preserved ejection fraction (HFpEF) patients, add-on empagliflozin was cost effective in China and Australia, but not in United States and Thailand. For HF with diabetes, add-on empagliflozin was cost effective in United Kingdom. Moreover, the incremental cost-effectiveness ratios (ICER) were lower for patients with diabetes than without in subgroup analysis. In the uncertainty analysis of all included studies, the ICERs were most sensitive to the cost of empagliflozin and cardiovascular mortality, followed by the cost of the standard treatment, hazard ratio of HF hospitalization. Conclusion: add-on empagliflozin for HFrEF might be cost-effective or dominant compared with standard of care alone. However, for HFpEF patients, add-on empagliflozin might be cost-effective in China and Australian, but not cost-effective in United States and Thailand.

The trade-off between COVID-19 and mental diseases burden during a lockdown: Mathematical modeling of control measures

Background

During the COVID-19 pandemic, many countries used lockdowns as a containment measure. While lockdowns successfully contributed to slowing down the contagion, the related mobility restrictions were reportedly associated with an increased risk of major depressive and anxiety disorders. We aimed to quantify the trade-off between the quality-adjusted life years (QALY) gain due to lower COVID-19 incidence as a result of a lockdown and QALY loss due to lockdown-induced mental disorders.

Methods

We developed an agent-based model of COVID-19 epidemic and coupled mental disorder development in the population of a large city. We used data sources on the places of living, studying and working, public health and census surveys. Modeling of mental disorders was based on diathesis-stress concept. We quantified mental and physical health burden in terms of QALY taking into account major depressive and anxiety disorder episodes, lethal and non-lethal cases of COVID-19, and immunization.

Findings

We evaluated the dynamics of new major depressive disorder (MDD) and anxiety disorder (AD) cases during the period between September 2020 and December 2021 in Moscow, Russia. We found that lockdown imposition increases the daily chances of getting MDD or ADD by a vulnerable person by 16.79% (95% CI [12.36%, 21.23%]). The QALY loss associated with COVID-19-induced and lockdown-induced mental disorders was estimated to be 18.93% (95% CI [16.94%, 19.73%]) of the total QALY loss caused by COVID-19, immunization, and all kinds of mental disorders. For a synthetic "strong" lockdown, it had been shown that QALY loss is minimized when about 70% of the population are isolated.

Interpretation

The burden associated with mental disorders amounts to a considerable part of COVID-19-related losses. Our findings demonstrate that cost-benefit analysis of mobility restriction should include a forecast of mental disorder development in the population.

The FLURESP European commission project: cost-effectiveness assessment of ten public health measures against influenza in Italy: is there an interest in COVID-19 pandemic?

BACKGROUND

The FLURESP project is a public health research funded by the European Commission, with the objective to design a methodological framework to assess the cost-effectiveness of existing public health measures against human influenza pandemics. A dataset has been specifically collected in the frame of the Italian health system. As most of interventions against human influenza are relavant against other respiratory diseases pandemics, potential interests in COVID-19 are discussed.

METHODS

Ten public health measures against human influenza pandemics pandemic were selected to be also relevant to other respiratory virus pandemics such as COVID 19: individual (hand washing, using masks), border control (quarantine, fever screening, border closure), community infection (school closure, class dismissal, social distancing, limitation of public transport), reduction of secondary infections (implementation of antibiotic therapy guidelines), pneumococcal vaccination for at-risk people, development of Intensive Care Unit (ICU) capacity, implementation of life support equipments in ICU, screening interventions, vaccination programs targeting health professional and targeting general population.

RESULTS

Using mortality reduction as effectiveness criteria, the most cost-effective strategies are "reduction of secondary infections" and "implementation of life support equipment in ICU". The least cost-effective option whatever the level of pandemic events are screening interventions and mass vaccination.

CONCLUSIONS

A number of intervention strategies against human influenza pandemics appears relevant against every respiratory virus, including the COVID-19 event. Measures against pandemics should be considered according to their expected effectiveness but also their costs for the society because they impose substantial burden to the population, confirming the interest of considering cost-effectiveness of public health measures to enlighten decision making.

Cost-effectiveness analysis of COVID-19 screening strategy under China's dynamic zero-case policy

This study aims to optimize the COVID-19 screening strategies under China's dynamic zero-case policy through cost-effectiveness analysis. A total of 9 screening strategies with different screening frequencies and combinations of detection methods were designed. A stochastic agent-based model was used to simulate the progress of the COVID-19 outbreak in scenario I (close contacts were promptly quarantined) and scenario II (close contacts were not promptly quarantined). The primary outcomes included the number of infections, number of close contacts, number of deaths, the duration of the epidemic, and duration of movement restriction. Net monetary benefit (NMB) and the incremental cost-benefit ratio were used to compare the cost-effectiveness of different screening strategies. The results indicated that under China's COVID-19 dynamic zero-case policy, high-frequency screening can help contain the spread of the epidemic, reduce the size and burden of the epidemic, and is cost-effective. Mass antigen testing is not cost-effective compared with mass nucleic acid testing in the same screening frequency. It would be more cost-effective to use AT as a supplemental screening tool when NAT capacity is insufficient or when outbreaks are spreading very rapidly.

Economic evaluation of strategies against coronavirus: a systematic review

BACKGROUND

The COVID-19 outbreak was defined as a pandemic on 11 March 2020 by the World Health Organization. After that, COVID-19 has enormously influenced health systems around the world, and it has claimed more than 4.2 million deaths until July 2021. The pandemic has led to global health, social and economic costs. This situation has prompted a crucial search for beneficial interventions and treatments, but little is known about their monetary value. This study is aimed at systematically reviewing the articles conducted on the economic evaluation of preventive, control and treatment strategies against COVID-19.

MATERIAL AND METHOD

We searched PubMed, Web of Science, Scopus, and Google Scholar from December 2019 to October 2021 to find applicable literature to the economic evaluation of strategies against COVID-19. Two researchers screened potentially eligible titles and abstracts. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist was used to quality assessment of studies.

RESULTS

Thirty-six studies were included in this review, and the average CHEERS score was 72. Cost-effectiveness analysis was the most common type of economic evaluation, used in 21 studies. And the quality-adjusted life year (QALY) was the main outcome applied to measure the effectiveness of interventions, which was used in 19 studies. In addition, articles were reported a wide range of incremental cost-effectiveness ratio (ICER), and the lowest cost per QALY ($321.14) was related to the use of vaccines.

CONCLUSION

Based on the results of this systematic review, it seems that all strategies are likely to be more cost-effective against COVID-19 than no intervention and vaccination was the most cost-effective strategy. This research provides insight for decision makers in choosing optimal interventions against the next waves of the current pandemic and possible future pandemics.

Epidemiologic and economic modelling of optimal COVID-19 policy: public health and social measures, masks and vaccines in Victoria, Australia

Background

Identifying optimal COVID-19 policies is challenging. For Victoria, Australia (6.6 million people), we evaluated 104 policy packages (two levels of stringency of public health and social measures [PHSMs], by two levels each of mask-wearing and respirator provision during large outbreaks, by 13 vaccination schedules) for nine future SARS-CoV-2 variant scenarios.

Methods

We used an agent-based model to estimate morbidity, mortality, and costs over 12 months from October 2022 for each scenario. The 104 policies (each averaged over the nine future variant scenarios) were ranked based on four evenly weighted criteria: cost-effectiveness from (a) health system only and (b) health system plus GDP perspectives, (c) deaths and (d) days exceeding hospital occupancy thresholds.

Findings

More compared to less stringent PHSMs reduced cumulative infections, hospitalisations and deaths but also increased time in stage ≥3 PHSMs. Any further vaccination from October 2022 decreased hospitalisations and deaths by 12% and 27% respectively compared to no further vaccination and was usually a cost-saving intervention from a health expenditure plus GDP perspective. High versus low vaccine coverage decreased deaths by 15% and reduced time in stage ≥3 PHSMs by 20%. The modelled mask policies had modest impacts on morbidity, mortality, and health system pressure. The highest-ranking policy combination was more stringent PHSMs, two further vaccine doses (an Omicron-targeted vaccine followed by a multivalent vaccine) for ≥30-year-olds with high uptake, and promotion of increased mask wearing (but not Government provision of respirators).

Interpretation

Ongoing vaccination and PHSMs continue to be key components of the COVID-19 pandemic response. Integrated epidemiologic and economic modelling, as exemplified in this paper, can be rapidly updated and used in pandemic decision making.

Funding

Anonymous donation, University of Melbourne funding.

The economic evaluation of ALS care: quality and cost

Objective: The study aims to analyze the quality of studies that make economic evaluations for amyotrophic lateral sclerosis (ALS). Assessing the quality of studies can guide policy-making and planning. Methods: One of the most recognized checklists "The Consensus on Health Economic Criteria" (CHEC)-list designed by Evers et al. in 2005 aims to answer two important questions: is the methodology of the study appropriate, and are the results of the study valid? We reviewed studies focusing on ALS and its economic costs, and evaluated the studies with (CHEC)-list. Results: We examined 25 articles in terms of their cost evaluation and quality. It is seen that they mainly focus on medical costs, ignoring social care costs. When the quality of the studies is examined, it is seen that the studies overall achieve high scores in terms of their purpose and research question, but some of the studies score low in terms of ethical dimension, comprehensiveness of expenditure items, their application of sensitivity analyses and their study design. Conclusions: The main recommendation of our study for future cost evaluation studies is that they should focus on the questions in the checklist that are scored low overall by the 25 articles, and consider the social care costs as well as medical costs. Our recommendations when designing cost studies can be applied to other chronic diseases with long-term economic costs like ALS.

Challenges and Limitations in Distributional Cost-Effectiveness Analysis: A Systematic Literature Review

BACKGROUND

Cost-effectiveness is a tool to maximize health benefits and to improve efficiency in healthcare. However, efficient outcomes are not always the most equitable ones. Distributional cost-effectiveness analysis (DCEA) offers a framework for incorporating equity concerns into cost-effectiveness analysis.

OBJECTIVE

This systematic review aims to outline the challenges and limitations in applying DCEA in healthcare settings.

METHODS

We searched Medline, Scopus, BASE, APA Psych, and JSTOR databases. We also included Google Scholar. We searched for English-language peer-reviewed academic publications, while books, editorials and commentary papers were excluded. Titles and abstract screening, full-text screening, reference list reviews, and data extraction were performed by the main researcher. Another researcher checked every paper for eligibility. Details, such as study population, disease area, intervention and comparators, costs and health effects, cost-effectiveness findings, equity analysis and effects, and modelling technique, were extracted. Thematic analysis was applied, focusing on challenges, obstacles, and gaps in DCEA.

RESULTS

In total, 615 references were identified, of which 18 studies met the inclusion criteria. Most of these studies were published after 2017. DCEA studies were mainly conducted in Europe and Africa and used quality health-adjusted measurements. In the included studies, absolute inequality indices were used more frequently than relative inequality indices. Every stage of the DCEA presented challenges and/or limitations.

CONCLUSION

This review provides an overview of the literature on the DCEA in healthcare as well as the challenges and limitations related to the different steps needed to conduct the analysis. In particular, we found problems with data availability, the relative unfamiliarity of this analysis among policymakers, and challenges in estimating differences among socioeconomic groups.

Comparing swab- and different symptoms-based strategies to ascertain COVID-19 recovery in healthcare workers: a cost-effectiveness analysis

Objective

Given the human and economic cost of the COVID-19 pandemic, protecting healthcare workers (HCW) and ensuring continuity of care is critical. The aim of this study is to evaluate the cost-effectiveness of different strategies to ascertain COVID-19 recovery in HCWs.

Methods

Data were collected from the hospital health surveillance program on HCWs at the University Hospital of Verona between 29/02/2020 and 14/04/2021. The diagnosis of SARS-CoV-2 infection and the assessment of the recovery were made through RT-PCR on oro-nasopharyngeal swab-sample. Recovery time and probability were estimated through Kaplan–Meier estimate. For each recovery assessment strategy costs (laboratory diagnostics and human resources), expressed in local currency (euro—€), and working days saved (WDS—effectiveness) were estimated. A decision-tree was created where each knot was a time point scheduled by the different recovery assessment strategies. A Monte Carlo simulation method was used, and probabilistic sensitivity analysis assessed the effect of input uncertainty.

Results

In the study period 916 (9.9%) HCWs tested positive. Recovery time through symptom-based strategy (21 days 0.95 CI 16–24) was significantly lower compared to swab-based one (25 days 0.95 CI 23–28, p < 0.001). The swab-based strategy was dominated by all symptoms-based ones. Symptoms-based with a swab on days 14 and 17 had an ICER of 2 €/WDS and 27 €/WDS compared to the one scheduled on days 10 and 17 and with only one swab on the 17th day.

Conclusions

Scheduling swabs on days 14 and 17 in a symptom-based strategy was the most cost-effective, saving 7.5 more working days than the standard one with swabs on days 10 and 17.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12962-022-00385-w.