Modeling Social Distancing Strategies to Prevent SARS-CoV-2 Spread in Israel: A Cost-Effectiveness Analysis

A Scoping Review and Taxonomy of Epidemiological-Macroeconomic Models of COVID-19

OBJECTIVES

The COVID-19 pandemic placed significant strain on many health systems and economies. Mitigation policies decreased health impacts but had major macroeconomic impact. This article reviews models combining epidemiological and macroeconomic projections to enable policy makers to consider both macroeconomic and health objectives.

METHODS

A scoping review of epidemiological-macroeconomic models of COVID-19 was conducted, covering preprints, working articles, and journal publications. We assessed model methodologies, scope, and application to empirical data.

RESULTS

We found 80 articles modeling both the epidemiological and macroeconomic outcomes of COVID-19. Model scope is often limited to the impact of lockdown on health and total gross domestic product or aggregate consumption and to high-income countries. Just 14% of models assess disparities or poverty. Most models fall under 4 categories: compartmental-utility-maximization models, epidemiological models with stylized macroeconomic projections, epidemiological models linked to computable general equilibrium or input-output models, and epidemiological-economic agent-based models. We propose a taxonomy comparing these approaches to guide future model development.

CONCLUSIONS

The epidemiological-macroeconomic models of COVID-19 identified have varying complexity and meet different modeling needs. Priorities for future modeling include increasing developing country applications, assessing disparities and poverty, and estimating of long-run impacts. This may require better integration between epidemiologists and economists.

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.

COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

INTRODUCTION

Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs.

METHODS

Using daily case data for 84 days (9 March-31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R₀), daily reproduction number (R_e), and case doubling time. Based on pre-restriction and Phase 1 R₀, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis.

RESULTS

The estimated median R₀ during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, -15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, -204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83).

CONCLUSION

Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.

Reducing the basic reproduction number of COVID-19: a model simulation focused on QALYs, hospitalisation, productivity costs and optimal (soft) lockdown

Even if public health interventions are successful at reducing the spread of COVID-19, there is no guarantee that they will bring net benefits to the society because of the dynamic nature of the pandemic, e.g., the risk of a second outbreak if those interventions are stopped too early, and the costs of a continued lockdown. In this analysis, a discrete-time dynamic model is used to simulate the effect of reducing the effective reproduction number, driven by lockdowns ordered in March 2020 in four European countries (UK, France, Italy and Spain), on QALYs and hospitalisation costs. These benefits are valued in monetary terms (€30,000 per QALY assumed) and compared to productivity costs due to reduced economic activity during the lockdown. An analysis of the optimal duration of lockdown is performed where a net benefit is maximised. The switch to a soft lockdown is analysed and compared to a continued lockdown or no intervention. Results vary for two assumptions about hospital capacity of the health system: (a) under unlimited capacity, average benefit ranges from 8.21 to 14.21% of annual GDP, for UK and Spain, respectively; (b) under limited capacity, average benefits are higher than 30.32% of annual GDP in all countries. The simulation results imply that the benefits of lockdown are not substantial unless continued until vaccination of high-risk groups is complete. It is illustrated that lockdown may not bring net benefits under some scenarios and a soft lockdown will be a more efficient alternative from mid-June 2020 only if the basic reproduction number is maintained low (not necessarily below 1) and productivity costs are sufficiently reduced.

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.

Economic evaluations of interventions against viral pandemics: a scoping review

Objectives

The COVID-19 pandemic has led to suggestions that cost-effectiveness analyses should adopt a broader perspective when estimating costs. This review aims to provide an overview of economic evaluations of interventions against viral pandemics in terms of the perspective taken, types of costs included, comparators, type of economic model, data sources and methods for estimating productivity costs.

Study design

Scoping literature review.

Methods

Publications were eligible if they conducted a cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis or cost-minimisation analysis and evaluated interventions aimed at viral pandemics or for patients infected with viral pandemic disease. We searched PubMed, Embase and Scopus for relevant references and charted data from the selected full-text publications into a predefined spreadsheet based on research sub-questions, summary tables and figures.

Results

From 5410 references, 36 full-text publications fulfilled the inclusion criteria. The economic evaluations were mainly model based and included direct medical costs of hospital treatment. Around half of the studies included productivity costs and the proportion of total costs attributed to productivity costs ranged from 10% to 90%, depending on estimation methods, assumptions about valuation of time, type of intervention, severity of illness and degree of transmission.

Conclusions

Economic evaluations of interventions against viral pandemics differed in terms of estimation methods and reporting of productivity costs, even for similar interventions. Hence, the literature on economic evaluations for pandemic response would benefit from having standards for conducting and reporting economic evaluations, especially for productivity costs.

Cost-effectiveness of interventions for the prevention and control of COVID-19: Systematic review of 85 modelling studies

Background

We aimed to quantitatively summarise the health economic evaluation evidence of prevention and control programs addressing COVID-19 globally.

Methods

We did a systematic review and meta-analysis to assess the economic and health benefit of interventions for COVID-19. We searched PubMed, Embase, Web of Science, and Cochrane Library of economic evaluation from December 31, 2019, to March 22, 2022, to identify relevant literature. Meta-analyses were done using random-effects models to estimate pooled incremental net benefit (INB). Heterogeneity was assessed using I2 statistics and publication bias was assessed by Egger's test. This study is registered with PROSPERO, CRD42021267475.

Results

Of 16 860 studies identified, 85 articles were included in the systematic review, and 25 articles (10 studies about non-pharmacological interventions (NPIs), five studies about vaccinations and 10 studies about treatments) were included in the meta-analysis. The pooled INB of NPIs, vaccinations, and treatments were $1378.10 (95% CI = $1079.62, $1676.59), $254.80 (95% CI = $169.84, $339.77) and $4115.11 (95% CI = $1631.09, $6599.14), respectively. Sensitivity analyses showed similar findings.

Conclusions

NPIs, vaccinations, and treatments are all cost-effective in combating the COVID-19 pandemic. However, evidence was mostly from high-income and middle-income countries. Further studies from lower-income countries are needed.

A Simulation-Based Cost-Effectiveness Analysis of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Prevention Strategies for Visitors of Healthcare Institutions

OBJECTIVES

The aim is to quantitatively evaluate different infection prevention strategies in the context of hospital visitor management during pandemics and to provide a decision support system for strategic and operational decisions based on this evaluation.

METHODS

A simulation-based cost-effectiveness analysis is applied to the data of a university hospital in Southern Germany and published COVID-19 research. The performance of different hospital visitor management strategies is evaluated by several decision-theoretic methods with varying objective functions.

RESULTS

Appropriate visitor restrictions and infection prevention measures can reduce additional infections and costs caused by visitors of healthcare institutions by >90%. The risk of transmission of severe acute respiratory syndrome coronavirus 2 by visitors of terminal care (ie, palliative care) patients can be reduced almost to 0 if appropriate infection prevention measures are implemented. Antigen tests do not seem to be beneficial from both a cost and an effectiveness perspective.

CONCLUSIONS

Hospital visitor management is crucial and effectively prevents infections while maintaining cost-effectiveness. For terminal care patients, visitor restrictions can be omitted if appropriate infection prevention measures are taken. Antigen testing plays a subordinate role, except in the case of a pure focus on additional infections caused by visitors of healthcare institutions. We provide decision support to authorities and hospital visitor managers to identify appropriate visitor restriction and infection prevention strategies for specific local conditions, incidence rates, and objectives.

Purposes and duties in scientific modelling

More people than ever are paying attention to philosophical questions about epidemiological models, including their susceptibility to the influence of social and ethical values, sufficiency to inform policy decisions under certain conditions, and even their fundamental nature. One important question pertains to the purposes of epidemiological models, for example, are COVID-19 models for 'prediction' or 'projection'? Are they adequate for making causal inferences? Is one of their goals, or virtues, to change individual responses to the pandemic? In this essay, we offer our perspective on these questions and place them in the context of other recent philosophical arguments about epidemiological models. We argue that clarifying the intended purpose of a model, and assessing its adequacy for that purpose, are moral-epistemic duties, responsibilities which pertain to knowledge but have moral significance nonetheless. This moral significance, we argue, stems from the inherent value-ladenness of models, along with the potential for models to be used in political decision making in ways that conflict with liberal values and which could lead to downstream harms. Increasing conversation about the moral significance of modelling, we argue, could help us to resist further eroding our standards of democratic scrutiny in the COVID-19 era.

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

OBJECTIVES

The COVID-19 pandemic has had a major impact on our society, with drastic policy restrictions being implemented to contain the spread of the severe acute respiratory syndrome coronavirus 2. This study aimed to provide an overview of the available evidence on the cost-effectiveness of various coronavirus disease 2019 policy measures.

METHODS

A systematic literature search was conducted in PubMed, Embase, and Web of Science. Health economic evaluations considering both costs and outcomes were included. Their quality was comprehensively assessed using the Consensus Health Economic Criteria checklist. Next, the quality of the epidemiological models was evaluated.

RESULTS

A total of 3688 articles were identified (March 2021), of which 23 were included. The studies were heterogeneous with regard to methodological quality, contextual factors, strategies' content, adopted perspective, applied models, and outcomes used. Overall, testing/screening, social distancing, personal protective equipment, quarantine/isolation, and hygienic measures were found to be cost-effective. Furthermore, the most optimal choice and combination of strategies depended on the reproduction number and context. With a rising reproduction number, extending the testing strategy and early implementation of combined multiple restriction measures are most efficient.

CONCLUSIONS

The quality assessment highlighted numerous flaws and limitations in the study approaches; hence, their results should be interpreted with caution because the specific context (country, target group, etc) is a key driver for cost-effectiveness. Finally, including a societal perspective in future evaluations is key because this pandemic has an indirect impact on the onset and treatment of other conditions and on our global economy.