Optimizing COVID-19 testing strategies on college campuses: evaluation of the health and economic costs

Colleges and universities in the US struggled to provide safe in-person education throughout the COVID-19 pandemic. Testing coupled with isolation is a nimble intervention strategy that can be tailored to mitigate health and economic costs, as the virus and our arsenal of medical countermeasures continue to evolve. We developed a decision-support tool to aid in the design of university-based testing strategies using a mathematical model of SARS-CoV-2 transmission. Applying this framework to a large public university reopening in the fall of 2021 with a 60% student vaccination rate, we find that the optimal strategy, in terms of health and economic costs, is twice weekly antigen testing of all students. This strategy provides a 95% guarantee that, throughout the fall semester, case counts would not exceed the CDCs original high transmission threshold of 100 cases per 100k persons over 7 days. As the virus and our medical armament continue to evolve, testing will remain a flexible tool for managing risks and keeping campuses open. We have implemented this model as an online tool to facilitate the design of testing strategies that adjust for COVID-19 conditions, university-specific parameters, and institutional goals. Author SummaryAs a part of the COVID-19 response team at a large public university in the US, we performed an analysis that considered together, the potential health and economic costs of different testing policies for the student body. University administrators had to weigh the up-front effort needed to implement wide scale testing against the potential costs of responding to high levels of disease on campus in the Fall of 2021, after vaccines were widely available but vaccination rates among college students were uncertain. The results presented here are applied to this specific instance, but the online tool provided can be tailored to university specific parameters, the epidemiological conditions, and the goals of the university. As we confront newly emerging variants of COVID-19 or novel pathogens, consideration of both the health and economic costs of proactive testing may serve as a politically tractable and cost-effective disease mitigation strategy.

Determining population-level allocation strategies for COVID-19 treatments in the United States using a quantitative framework, a case study using nirmatrelvir/ritonavir

BackgroundNew COVID-19 medications force decision makers to weigh limited evidence of efficacy and cost in determining which patient populations to target for treatment. A case in point is nirmatrelvir/ritonavir, a drug that has been recommended for elderly, high-risk individuals, regardless of vaccination status, even though clinical trials have only evaluated it in unvaccinated patients. A simple optimization framework might inform a more reasoned approach to the tradeoffs implicit in the treatment allocation decision. MethodsWe used a mathematical model to analyze the cost-effectiveness of four nirmatrelvir/ritonavir allocation strategies, stratified by vaccination status and risk for severe disease. We considered treatment effectiveness at preventing hospitalization ranging from 21% to 89%. Sensitivity analyses were performed on major parameters of interest. A web-based tool was developed to permit decision-makers to tailor the analysis to their settings and priorities. ResultsProviding nirmatrelvir/ritonavir to unvaccinated patients at high-risk for severe disease was cost-saving when effectiveness against hospitalization exceeded 33% and cost-effective under all other data scenarios we considered. The cost-effectiveness of other allocation strategies, including those for vaccinated adults and those at lower-risk for severe disease, depended on willingness-to-pay thresholds, treatment cost and effectiveness, and the likelihood of severe disease. ConclusionsPriority for nirmatrelvir/ritonavir treatment should be given to unvaccinated persons at high-risk of severe disease from COVID-19. Further priority may be assigned by weighing treatment effectiveness, disease severity, drug cost, and willingness to pay for deaths averted.

Model-based estimates of deaths averted and cost per life saved by scaling-up mRNA COVID-19 vaccination in low and lower-middle income countries in the COVID-19 Omicron variant era

BackgroundWhile almost 60% of the world has received at least one dose of COVID-19 vaccine, the global distribution of vaccination has not been equitable. Only 4% of the population of low-income countries has received a full primary vaccine series, compared to over 70% of the population of high-income nations. MethodsWe used economic and epidemiologic models, parameterized with public data on global vaccination and COVID-19 deaths, to estimate the potential benefits of scaling up vaccination programs in low and lower-middle income countries (LIC/LMIC) in 2022 in the context of global spread of the Omicron variant of SARS-CoV2. Outcomes were expressed as number of avertable deaths through vaccination, costs of scale-up, and cost per death averted. We conducted sensitivity analyses over a wide range of parameter estimates to account for uncertainty around key inputs. FindingsGlobal scale up of vaccination to provide two doses of mRNA vaccine to everyone in LIC/LMIC would cost $35.5 billion and avert 1.3 million deaths from COVID-19, at a cost of $26,900 per death averted. Scaling up vaccination to provide three doses of mRNA vaccine to everyone in LIC/LMIC would cost $61.2 billion and avert 1.5 million deaths from COVID-19 at a cost of $40,800 per death averted. Lower estimated infection fatality ratios, higher cost-per-dose, and lower vaccine effectiveness or uptake lead to higher cost-per-death averted estimates in the analysis. InterpretationScaling up COVID-19 global vaccination would avert millions of COVID-19 deaths and represents a reasonable investment in the context of the value of a statistical life (VSL). Given the magnitude of expected mortality facing LIC/LMIC without vaccination, this effort should be an urgent priority.

COVID-19 in Connecticut institutions of higher education during the 2020-2021 academic year

BackgroundDuring the 2020-2021 academic year, many institutions of higher education reopened to residential students while pursuing strategies to mitigate the risk of SARS-CoV-2 transmission on campus. Reopening guidance emphasized PCR or antigen testing for residential students and social distancing measures to reduce the frequency of close interpersonal contact. Connecticut colleges and universities employed a variety of approaches to reopening campuses to residential students. MethodsWe used data on testing, cases, and social contact in 18 residential college and university campuses in Connecticut to characterize institutional reopening strategies and COVID-19 outcomes. We compared institutions fall 2020 COVID-19 plans, submitted to the Connecticut Department of Public Health, and analyzed contact rates and COVID-19 outcomes throughout the academic year. ResultsIn census block groups containing residence halls, fall student move-in resulted in a 475% (95% CI 373%-606%) increase in average contact, and spring move-in resulted in a 561% (441%-713%) increase in average contact. The relationship between test frequency and case rate per residential student was complex: institutions that tested students infrequently detected few cases but failed to blunt transmission, while institutions that tested students more frequently detected more cases and prevented further spread. In fall 2020, each additional test per student per week was associated with a reduction of 0.0014 cases per student per week (95% CI: -0.0028, -0.000012). Residential student case rates were associated with higher case rates in the town where the school was located, but it is not possible to determine whether on-campus infections were transmitted to the broader community or vice versa. ConclusionsCampus outbreaks among residential students might be avoided or mitigated by frequent testing, social distancing, and mandatory vaccination. Vaccination rates among residential students and surrounding communities may determine the necessary scale of residential testing programs and social distancing measures during the 2021-2022 academic year.

Assessing COVID prevention strategies to permit the safe opening of college campuses in fall 2021

BackgroundEffective vaccines, improved testing technologies, and declines in COVID-19 incidence prompt an examination of the choices available to college administrators to safely resume in-person campus activities in fall 2021. ObjectiveTo develop a decision support tool that assists college administrators in designing and evaluating customized COVID vaccination, screening, and prevention plans. DesignDecision analysis linked to a compartmental epidemic model, quantifying the interaction of policy instruments (e.g., vaccination promotion, asymptomatic testing, physical distancing, and other non-pharmaceutical interventions), institutional priorities (e.g., risk tolerance, desire to resume activities), and assumptions about vaccine performance and background epidemic severity. ParticipantsHypothetical cohort of 5000 individuals (students, faculty, and staff) living and working in the close environs of a residential college campus. Main Outcome(s) and Measure(s)Cumulative infections over a 120-day semester. ResultsUnder Base Case assumptions, if 90% coverage with an 85%-effective vaccine can be attained, the model finds that campus activities can be fully resumed while holding cumulative cases below 5% of the population without the need for routine, asymptomatic testing. With 50% population coverage using such a vaccine, a similar "return to normalcy" would require daily asymptomatic testing of unvaccinated individuals. The effectiveness of vaccination in reducing susceptibility to infection is a critical uncertainty. Conclusions & RelevanceVaccination coverage is the most powerful tool available to college administrators to achieve a safe return to pre-pandemic operations this fall. Given the breadth of potential outcomes in the face of uncontrollable and uncertain factors, even colleges that achieve high vaccination coverage should be prepared to reinstitute testing and distancing policies on short notice.

Clinical and Economic Impact of Widespread Rapid Testing to Decrease SARS-CoV-2 Transmission

BackgroundThe value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood. ObjectiveTo define performance standards and predict the clinical, epidemiological, and economic outcomes of nationwide, home-based, antigen testing. DesignA simple compartmental epidemic model estimated viral transmission, clinical history, and resource use, with and without testing. Data SourcesParameter values and ranges informed by Centers for Disease Control guidance and published literature. Target PopulationUnited States population. Time Horizon60 days. PerspectiveSocietal.Costs include: testing, inpatient care, and lost workdays. InterventionHome-based SARS-CoV-2 antigen testing. Outcome MeasuresCumulative infections and deaths, numbers isolated and/or hospitalized, and total costs. Results of Base-Case AnalysisWithout a testing intervention, the model anticipates 15 million infections, 125,000 deaths, and $10.4 billion in costs ($6.5 billion inpatient; $3.9 billion lost productivity) over a 60-day horizon. Weekly availability of testing may avert 4 million infections and 19,000 deaths, raising costs by $21.5 billion. Lower inpatient outlays ($5.9 billion) would partially offset additional testing expenditures ($12.0 billion) and workdays lost ($13.9 billion), yielding incremental costs per infection (death) averted of $5,400 ($1,100,000). Results of Sensitivity AnalysisOutcome estimates vary widely under different behavioral assumptions and testing frequencies. However, key findings persist across all scenarios: large reductions in infections, mortality, and hospitalizations; and costs per death averted roughly an order of magnitude lower than commonly accepted willingness-to-pay values per statistical life saved ($5-17 million). LimitationsAnalysis restricted to at-home testing and limited by uncertainties about test performance. ConclusionHigh-frequency home testing for SARS-CoV-2 using an inexpensive, imperfect test could contribute to pandemic control at justifiable cost and warrants consideration as part of a national containment strategy. Primary Funding SourcesDr. Paltiel was supported by grant R37DA015612 from the National Institute on Drug Abuse of the National Institutes of Health. Dr. Sax was supported by grant R01AI042006 from the National Institute of Allergy and Infectious Diseases of the National Institutes of Health.

COVID-19 screening strategies that permit the safe re-opening of college campuses

ImportanceThe COVID-19 pandemic poses an existential threat to many US residential colleges: either they open their doors to students in September or they risk serious financial consequences. ObjectiveTo define SARS-CoV-2 screening performance standards that would permit the safe return of students to campus for the Fall 2020 semester. DesignDecision and cost-effectiveness analysis linked to a compartmental epidemic model to evaluate campus screening using tests of varying frequency (daily-weekly), sensitivity (70%-99%), specificity (98%-99.7%), and cost ($10-$50/test). Reproductive numbers Rt = {1.5, 2.5, 3.5} defined three epidemic scenarios, with additional infections imported via exogenous shocks. We generally adhered to US government guidance for parameterization data. ParticipantsA hypothetical cohort of 5000 college-age, uninfected students. Main Outcome(s) and Measure(s)Cumulative tests, infections, and costs; daily isolation dormitory census; incremental cost-effectiveness; and budget impact. All measured over an 80-day, abbreviated semester. ResultsWith Rt = 2.5, daily screening with a 70% sensitive, 98% specific test produces 85 cumulative student infections and isolation dormitory daily census averaging 108 (88% false positives). Screening every 2 (7) days nets 135 (3662) cumulative infections and daily isolation census 66 (252) with 73% (4%) false positives. Across all scenarios, test frequency exerts more influence on outcomes than test sensitivity. Cost-effectiveness analysis selects screening every {2, 1, 7} days with a 70% sensitive test as the preferred strategy for Rt = {2.5, 3.5, 1.5}, implying a screening cost of {$470, $920, $120} per student per semester. Conclusions & RelevanceRapid, inexpensive and frequently conducted screening - even if only 70% sensitive - would be cost-effective and produce a modest number of COVID-19 infections. While the optimal screening frequency hinges on the success of behavioral interventions to reduce the base severity of transmission (Rt), this could permit the safe return of student to campus. KEY POINTSO_ST_ABSQuestionC_ST_ABSWhat SARS-CoV-2 screening and isolation program will keep U.S. residential college students safe and permit the reopening of campuses? FindingsFrequent screening (every 2 or 3 days) of all students with a low-sensitivity, high-specificity test will control outbreaks with manageable isolation dormitory utilization at a justifiable cost. MeaningCampuses can safely reopen in the Fall 2020 but success hinges on frequent screening and uncompromising, continuous attention to basic prevention and behavioral interventions to reduce the baseline severity of transmission.

Adaptive policies for use of physical distancing interventions during the COVID-19 pandemic

Policymakers need decision tools to determine when to use physical distancing interventions to maximize the control of COVID-19 while minimizing the economic and social costs of these interventions. We develop a pragmatic decision tool to characterize adaptive policies that combine real-time surveillance data with clear decision rules to guide when to trigger, continue, or stop physical distancing interventions during the current pandemic. In model-based experiments, we find that adaptive policies characterized by our proposed approach prevent more deaths and require a shorter overall duration of physical distancing than alternative physical distancing policies. Our proposed approach can readily be extended to more complex models and interventions. One-sentence summariesAdaptive physical distancing policies save more lives with fewer weeks of intervention than policies which prespecify the length and timing of interventions.