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This paper estimates the benefits and costs of state suppression policies to “bend the curve” during the initial outbreak of COVID-19 in the United States. We employ an approach that values benefits and costs in terms of additions or subtractions to total production. Relative to a baseline in which only the infected and at-risk populations mitigate the spread of coronavirus, we estimate that total benefits of suppression policies to economic output are between $632.5 billion and $765.0 billion from early March 2020 to August 1, 2020. Relative to private mitigation, output lost due to suppression policies is estimated to be between $214.2 billion and $331.5 billion. The cost estimate is based on the duration of nonessential business closures and stay-at-home orders, which were enforced between 42 and 65 days. Our results indicate that the net benefits of suppression policies to...

Treatment with tocilizumab in combination with dexamethasone appears to be cost effective in reducing COVID-19-related deaths, according to findings of a US study published in Clinical Infectious Diseases.A decision-tree model populated with data from the randomised RECOVERY trial, which was conducted in the UK, was used to evaluate the cost effectiveness of tocilizumab plus dexamethasone, compared with dexamethasone alone or best supportive care (BSC) alone, in patients with severe COVID-19 infection. Cost effectiveness was assessed from a US perspective. Assumed drug costs were $5304 for tocilizumab and $12 for dexamethasone, and assumed annual healthcare costs in COVID-19 survivors were $6929 per year.Tocilizumab plus dexamethasone, dexamethasone alone and BSC alone were estimated to achieve a gain 9.36, 8.66 and 8.43 QALYs, respectively, at a total cost of $83 130,...

Focusing only on cases and deaths hides the pandemic’s lasting health burden on people, societies and economies.

The COVID-19 pandemic has brought dramatic worldwide consequences affecting social, economic and healthcare systems. Considering that the number of infected patients requiring admission to intensive care units far exceeded the available resources, healthcare professionals have had to face challenging decisions concerning who should benefit from the limited resources and who should not. In this context, after a careful ethical reflection, we propose some principles to be adopted when dealing with allocation resource decisions, based on core ethical values. Ideally, these strategies should be established and integrated into institutional policies before a crisis scenario, in order to anticipate a potential new public health emergency and prevent possible tragic consequences.

Background: Healthcare workers are at a higher risk of COVID-19 infection during care encounters compared to the general population. Personal Protective Equipment (PPE) have been shown to protect COVID-19 among healthcare workers, however, Kenya has faced PPE shortages that can adequately protect all healthcare workers. We, therefore, examined the health and economic consequences of investing in PPE for healthcare workers in Kenya. Methods: We conducted a cost-effectiveness and return on investment (ROI) analysis using a decision-analytic model following the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines. We examined two outcomes: 1) the cost per healthcare worker death averted, and 2) the cost per healthcare worker COVID-19 case averted. We performed a multivariate sensitivity analysis using 10,000 Monte Carlo simulations. Results:...

The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures. Among these, mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to limit the spread of the virus. In this article, we aim to evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population through a Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Excluding the value of monetized health, the Benefit-Cost ratio was estimated at approximately 0.45. However, if monetized health is included in the calculation, the ratio is close to 1.20. The monetization of health is the critical element that tips the scales in favour of the desirability of screening. Screenings with the highest...

Objectives To evaluate the cost effectiveness of an asymptomatic SARS-CoV-2 whole area testing pilot. Design Epidemiological modelling and cost effectiveness analysis. Setting The community of Merthyr Tydfil County Borough between20 Nov and 21 Dec 2020. Participants A total of 33,822 people tested as part of the pilot in Merthyr Tydfil County Borough, 712 of whom tested positive by lateral flow test and reported being asymptomatic. Main outcome measures Estimated number of cases, hospitalisations, ICU admissions and deaths prevented, and associated costs per quality-adjusted life years (QALYs) gained and monitory cost to the healthcare system. Results An initial conservative estimate of 360 (95% CI: 311 – 418) cases were prevented by the mass testing, representing a would-be reduction of 11% of all cases diagnosed in Merthyr Tydfil residents during the same period....

High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. We use computational modeling, coupled with clinical data from rapid antigen tests, to predict the impact of frequent viral antigen rapid testing on COVID-19 spread and outcomes. Using patient nasal or nasopharyngeal swab specimens, we demonstrate that the sensitivity/specificity of two rapid antigen tests compared to quantitative real-time polymerase chain reaction (qRT-PCR) are 82.0%/100% and 84.7%/85.7%, respectively; moreover, sensitivity correlates directly with viral load. Based on COVID-19 data from three regions in the United States and São José do Rio Preto, Brazil, we show that high frequency, strategic population-wide rapid testing, even at varied accuracy levels, diminishes COVID-19 infections, hospitalizations, and deaths at a fraction of the...

  COVID-19 has caused an enormous burden on healthcare facilities around the world. Cohorting patients and healthcare professionals (HCPs) into “bubbles” has been proposed as an infection-control mechanism. In this paper, we present a novel and flexible model for clustering patient care in healthcare facilities into bubbles in order to minimize infection spread. Our model aims to control a variety of costs to patients/residents and HCPs so as to avoid hidden, downstream adverse effects of clustering patient care. This model leads to a discrete optimization problem that we call the BubbleClustering problem. This problem takes as input a temporal visit graph, representing HCP mobility, including visits by HCPs to patient/resident rooms. The output of the problem is a rewired visit graph, obtained by partitioning HCPs and patient rooms into bubbles and rewiring HCP visits to patient...