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Modeling the relative risk of SARS-CoV-2 infection to inform risk-cost-benefit analyses of activities during the SARS-CoV-2 pandemic.

ABSTRACT: Risk-cost-benefit analysis requires the enumeration of decision alternatives, their associated outcomes, and the quantification of uncertainty. Public and private decision-making surrounding the COVID-19 pandemic must contend with uncertainty about the probability of infection during activities involving groups of people, in order to decide whether that activity is worth undertaking. We propose a model of SARS-CoV-2 infection probability that can produce estimates of relative risk of infection for diverse activities, so long as those activities meet a list of assumptions, including that they do not last longer than one day (e.g., sporting events, flights, concerts), and that the probability of infection among possible routes of infection (i.e., droplet, aerosol, fomite, and direct contact) are independent. We show how the model can be used to inform decisions facing governments and industry, such as opening stadiums or flying on airplanes; in particular, it allows for estimating the ranking of the constituent components of activities (e.g., going through a turnstile, sitting in one's seat) by their relative risk of infection, even when the probability of infection is unknown or uncertain. We prove that the model is a good approximation of a more refined model in which we assume infections come from a series of independent risks. A linearity assumption governing several potentially modifiable risks factors-such as duration of the activity, density of participants, and infectiousness of the attendees-makes interpreting and using the model straightforward, and we argue that it does so without significantly diminishing the reliability of the model.

SUBMITTER: McCarthy JE

PROVIDER: S-EPMC7842882 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Modeling the relative risk of SARS-CoV-2 infection to inform risk-cost-benefit analyses of activities during the SARS-CoV-2 pandemic.

McCarthy John E JE Dewitt Barry D BD Dumas Bob A BA McCarthy Myles T MT

PloS one 20210128 1

Risk-cost-benefit analysis requires the enumeration of decision alternatives, their associated outcomes, and the quantification of uncertainty. Public and private decision-making surrounding the COVID-19 pandemic must contend with uncertainty about the probability of infection during activities involving groups of people, in order to decide whether that activity is worth undertaking. We propose a model of SARS-CoV-2 infection probability that can produce estimates of relative risk of infection f ...[more]

PMID: 33507962

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Project description:BackgroundFierce debate about the health and financial tradeoffs presented by different COVID-19 pandemic mitigation strategies highlights the need for rigorous quantitative evaluation of policy options.ObjectiveTo quantify the economic value of the costs and benefits of a policy of continued limited reopening with social distancing relative to alternative COVID-19 response strategies in the United States.DesignWe estimate the number and value of quality-adjusted life-years (QALY) gained from mortality averted, with a value of $125,000 per QALY, and compare these benefits to the associated costs in terms of plausible effects on US GDP under a policy of continued limited reopening with social distancing relative to a policy of full reopening toward herd immunity. Using the same QALY value assumptions, we further evaluate cost-effectiveness of a return to Shelter-in-Place relative to a policy of limited reopening.SettingUnited States Measurements: QALY and cost as percent of GDP of limited reopening with continued social distancing relative to a strategy of full reopening aimed at achieving herd immunity; a limited reopening budget measured in the number of months before this strategy fails to demonstrate cost-effectiveness relative to a full reopening; a shelter-in-place threshold measured in the number of lives saved at which a month of sheltering in place demonstrates cost effectiveness relative to the limited reopening strategy.ResultsQALY benefits from mortality averted by continued social distancing and limited reopening relative to a policy of full reopening exceed projected GDP costs if an effective vaccine or therapeutic can be developed within 11.1 months from late May 2020. White House vaccine projections fall within this date, supporting a partial reopening strategy. One month of shelter-in-place restrictions provides QALY benefits from averted mortality that exceed the associated GDP costs relative to limited reopening if the restrictions prevent at least 154,586 additional COVID-19 deaths over the course of the pandemic. Current models of disease progression suggest that limited reopening will not cause this many additional deaths, again supporting a limited reopening strategy.LimitationLimited horizon of COVID-19 mortality projections; infection fatality ratio stable across strategies, ignoring both the potential for ICU overload to increase mortality and the deployment of partially effective therapeutics to decrease mortality; effect on GDP modeled as constant within a given phase of the pandemic; accounts for age and sex distribution of QALYs, but not effect of comorbidities; only considers impact from QALY lost due to mortality and from changes in GDP, excluding numerous other considerations, such as non-fatal COVID-19 morbidity, reduced quality of life caused by prolonged social distancing, or educational regression associated with prolonged school closures and restrictions.ConclusionsA limited reopening to achieve partial mitigation of COVID-19 is cost effective relative to a full reopening if an effective therapeutic or vaccine can be deployed within 11.1 months of late May 2020. One additional month of shelter-in-place restrictions should only be imposed if it saves at least 154,586 lives per month before the development of an effective therapeutic or vaccine relative to limited reopening.

Project description:BackgroundEconomic evaluation of school-based obesity interventions could provide support for public health decision of obesity prevention. This study is to perform cost-utility and cost-benefit assessment of three school-based childhood obesity interventions including nutrition education intervention (NE), physical activity intervention (PA) and comprehensive intervention (both NE and PA, CNP) with secondary data analysis of one randomized controlled trial.MethodsThe standard cost-effectiveness analysis methods were employed from a societal perspective to the health outcome and costs that are attributable to the intervention. NE, PA and CNP were carried out separately for 2 semesters for childhood obesity interventions in primary schools. The additional quality-adjusted life years (QALYs) resulting from the interventions were measured as the health outcome. A cost-utility ratio (CUR) and A cost-benefit ratio (CBR) was calculated as the ratio of implementation costs to the total medical and productivity loss costs averted by the interventions.ResultsThe CUR and CBR were ¥11,505.9 ($1646.0) per QALY and ¥1.2 benefit per ¥1 cost respectively, and the net saving was ¥73,659.6 ($10,537.9). The CUR and CBR for nutrition education and physical activity interventions were ¥21,316.4 ($3049.6) per QALY and ¥0.7 benefit per ¥1 cost, ¥28,417.1 ($4065.4) per QALY and ¥0.4 benefit per ¥1 cost, respectively (in 2019 RMB). Compared with PA intervention, the ICERs were ¥10,335.2 ($1478.6) and 4626.3 ($661.8) for CNP and NE respectively. The CBR was ¥1.2, 0.7, and 0.4 benefits per ¥1 cost for CNP, NE, and PA interventions, respectively. Net estimated savings were achieved only through CNP intervention, amounting to ¥73,659.6 ($10,537.9).ConclusionsComprehensive school-based obesity intervention is a beneficial investment that is both cost-effective and cost saving. Compared with PA intervention, both CNP and NE intervention were more cost-effective.

Dataset Information

Modeling the relative risk of SARS-CoV-2 infection to inform risk-cost-benefit analyses of activities during the SARS-CoV-2 pandemic.

Publications

Modeling the relative risk of SARS-CoV-2 infection to inform risk-cost-benefit analyses of activities during the SARS-CoV-2 pandemic.

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