Patients' Perspectives on Emergency Department COVID-19 Vaccination and Vaccination Messaging Through Randomized Vignettes.

OBJECTIVES: Emergency departments (EDs) could play an important role in the COVID-19 pandemic response by reaching patients who would otherwise not seek vaccination in the community. Prior to expanding COVID-19 vaccination to the acute care setting, we assessed ED patients' COVID-19 vaccine status, perspectives, and hypothetical receptivity to ED-based vaccination. METHODS: From January 11 through March 31, 2021, we conducted a multisite (Albany Medical Center, Boston Medical Center, Buffalo General Hospital, University of Cincinnati Medical Center, and Upstate Medical Center), cross-sectional survey of ED patients, with embedded randomization for participants to receive 1 of 4 vignette vaccination messages (simple opt-in message, recommendation by the hospital, community-oriented message, and acknowledgment of vaccine hesitancy). Main outcomes included COVID-19 vaccination status, prior intention to be vaccinated, and receptivity to randomized hypothetical vignette messages. RESULTS: Of 610 participants, 122 (20.0%) were vaccinated, 234 (38.4%) had prior intent to be vaccinated, 111 (18.2%) were unsure as to prior intent, and 143 (23.4%) had no prior intent to be vaccinated. Vaccine hesitancy (participants who were vaccine unsure or did not intend to receive the vaccine) was associated with the following: age <45 years, female, non-Hispanic Black, no primary health care, and no prior influenza vaccination. Overall, 364 of 565 (64.4%; 95% CI, 60.3%-68.4%) were willing to accept a hypothetical vaccination in the ED. Among participants with prior vaccine hesitancy, a simple opt-in message resulted in the highest acceptance rates to hypothetical vaccination (39.7%; 95% CI, 27.6%-52.8%). CONCLUSIONS: EDs have appropriate patient populations to initiate COVID-19 vaccination programs as a supplement to community efforts. A simple opt-in approach may offer the best messaging to reach vaccine-hesitant ED patients.

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

IMPORTANCE: The 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. OBJECTIVE: To define SARS-CoV-2 screening performance standards that would permit the safe return of students to campus for the Fall 2020 semester. DESIGN: Decision 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. PARTICIPANTS: A 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. RESULTS: With 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 & Relevance: Rapid, 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.

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

BACKGROUND: The value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood. OBJECTIVE: To define performance standards and predict the clinical, epidemiological, and economic outcomes of nationwide, home-based, antigen testing. DESIGN: A simple compartmental epidemic model estimated viral transmission, clinical history, and resource use, with and without testing. DATA SOURCES: Parameter values and ranges informed by Centers for Disease Control guidance and published literature. TARGET POPULATION: United States population. TIME HORIZON: 60 days. PERSPECTIVE: Societal. Costs include: testing, inpatient care, and lost workdays. INTERVENTION: Home-based SARS-CoV-2 antigen testing. OUTCOME MEASURES: Cumulative infections and deaths, numbers isolated and/or hospitalized, and total costs. RESULTS OF BASE-CASE ANALYSIS: Without 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 ANALYSIS: Outcome 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). LIMITATIONS: Analysis restricted to at-home testing and limited by uncertainties about test performance. CONCLUSION: High-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.

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

BACKGROUND: The value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood. OBJECTIVE: To define performance standards and predict the clinical, epidemiologic, and economic outcomes of nationwide, home-based antigen testing. DESIGN: A simple compartmental epidemic model that estimated viral transmission, portrayed disease progression, and forecast resource use, with and without testing. DATA SOURCES: Parameter values and ranges as informed by Centers for Disease Control and Prevention guidance and published literature. TARGET POPULATION: U.S. population. TIME HORIZON: 60 days. PERSPECTIVE: Societal; costs included testing, inpatient care, and lost workdays. INTERVENTION: Home-based SARS-CoV-2 antigen testing. OUTCOME MEASURES: Cumulative infections and deaths, number of persons isolated and hospitalized, and total costs. RESULTS OF BASE-CASE ANALYSIS: Without a testing intervention, the model anticipates 11.6 million infections, 119 000 deaths, and $10.1 billion in costs ($6.5 billion in inpatient care and $3.5 billion in lost productivity) over a 60-day horizon. Weekly availability of testing would avert 2.8 million infections and 15 700 deaths, increasing costs by $22.3 billion. Lower inpatient outlays ($5.9 billion) would partially offset additional testing expenditures ($12.5 billion) and workdays lost ($14.0 billion), yielding incremental cost-effectiveness ratios of $7890 per infection averted and $1 430 000 per death averted. RESULTS OF SENSITIVITY ANALYSIS: Outcome estimates vary widely under different behavioral assumptions and testing frequencies. However, key findings persist across all scenarios, with large reductions in infections, mortality, and hospitalizations. Costs per death averted are roughly an order of magnitude lower than commonly accepted willingness-to-pay values per statistical life saved ($5 to $17 million). LIMITATIONS: Analysis was restricted to at-home testing. There are uncertainties concerning test performance. CONCLUSION: High-frequency home testing for SARS-CoV-2 with an inexpensive, imperfect test could contribute to pandemic control at justifiable cost and warrants consideration as part of a national containment strategy. PRIMARY FUNDING SOURCE: National Institutes of Health.

Clinical Outcomes Of A COVID-19 Vaccine: Implementation Over Efficacy.

The global effort to develop a coronavirus disease 2019 (COVID-19) vaccine is on track to produce one or more authorized vaccines. We examine how different definitions and thresholds of vaccine efficacy, coupled with different levels of implementation effectiveness and background epidemic severity, translate into outcomes including cumulative infections, hospitalizations, and deaths. Using a mathematical simulation of vaccination, we find that factors related to implementation will contribute more to the success of vaccination programs than a vaccine's efficacy as determined in clinical trials. The benefits of a vaccine will decline substantially in the event of manufacturing or deployment delays, significant vaccine hesitancy, or greater epidemic severity. Our findings demonstrate the urgent need for health officials to invest greater financial resources and attention to vaccine production and distribution programs, to redouble efforts to promote public confidence in COVID-19 vaccines, and to encourage continued adherence to other mitigation approaches, even after a vaccine becomes available.

Assessment of SARS-CoV-2 Screening Strategies to Permit the Safe Reopening of College Campuses in the United States.

Importance: The coronavirus disease 2019 (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. Objective: To define severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) screening performance standards that would permit the safe return of students to US residential college campuses for the fall 2020 semester. Design, Setting, and Participants: This analytic modeling study included a hypothetical cohort of 4990 students without SARS-CoV-2 infection and 10 with undetected, asymptomatic SARS-CoV-2 infection at the start of the semester. The decision and cost-effectiveness analyses were linked to a compartmental epidemic model to evaluate symptom-based screening and tests of varying frequency (ie, every 1, 2, 3, and 7 days), sensitivity (ie, 70%-99%), specificity (ie, 98%-99.7%), and cost (ie, $10/test-$50/test). Reproductive numbers (Rt) were 1.5, 2.5, and 3.5, defining 3 epidemic scenarios, with additional infections imported via exogenous shocks. The model assumed a symptomatic case fatality risk of 0.05% and a 30% probability that infection would eventually lead to observable COVID-19-defining symptoms in the cohort. Model projections were for an 80-day, abbreviated fall 2020 semester. This study adhered to US government guidance for parameterization data. Main Outcomes and Measures: Cumulative tests, infections, and costs; daily isolation dormitory census; incremental cost-effectiveness; and budget impact. Results: At the start of the semester, the hypothetical cohort of 5000 students included 4990 (99.8%) with no SARS-CoV-2 infection and 10 (0.2%) with SARS-CoV-2 infection. Assuming an Rt of 2.5 and daily screening with 70% sensitivity, a test with 98% specificity yielded 162 cumulative student infections and a mean isolation dormitory daily census of 116, with 21 students (18%) with true-positive results. Screening every 2 days resulted in 243 cumulative infections and a mean daily isolation census of 76, with 28 students (37%) with true-positive results. Screening every 7 days resulted in 1840 cumulative infections and a mean daily isolation census of 121 students, with 108 students (90%) with true-positive results. Across all scenarios, test frequency was more strongly associated with cumulative infection than test sensitivity. This model did not identify symptom-based screening alone as sufficient to contain an outbreak under any of the scenarios we considered. Cost-effectiveness analysis selected screening with a test with 70% sensitivity every 2, 1, or 7 days as the preferred strategy for an Rt of 2.5, 3.5, or 1.5, respectively, implying screening costs of $470, $910, or $120, respectively, per student per semester. Conclusions and Relevance: In this analytic modeling study, screening every 2 days using a rapid, inexpensive, and even poorly sensitive (>70%) test, coupled with strict behavioral interventions to keep Rt less than 2.5, is estimated to maintain a controllable number of COVID-19 infections and permit the safe return of students to campus.

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

IMPORTANCE: The 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. OBJECTIVE: To define SARS-CoV-2 screening performance standards that would permit the safe return of students to campus for the Fall 2020 semester. DESIGN: Decision 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. PARTICIPANTS: A 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. RESULTS: With 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 & Relevance: Rapid, 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.