Estimate of undetected severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in acute-care hospital settings using an individual-based microsimulation model.

OBJECTIVE: Current guidance states that asymptomatic screening for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) prior to admission to an acute-care setting is at the facility's discretion. This study's objective was to estimate the number of undetected cases of SARS-CoV-2 admitted as inpatients under 4 testing approaches and varying assumptions. DESIGN AND SETTING: Individual-based microsimulation of 104 North Carolina acute-care hospitals. PATIENTS: All simulated inpatient admissions to acute-care hospitals from December 15, 2021, to January 13, 2022 [ie, during the SARS-COV-2 ο (omicron) variant surge]. INTERVENTIONS: We simulated (1) only testing symptomatic patients, (2) 1-stage antigen testing with no confirmatory polymerase chain reaction (PCR) test, (3) 1-stage antigen testing with a confirmatory PCR for negative results, and (4) serial antigen screening (ie, repeat antigen test 2 days after a negative result). RESULTS: Over 1 month, there were 77,980 admissions: 13.7% for COVID-19, 4.3% with but not for COVID-19, and 82.0% for non-COVID-19 indications without current infection. Without asymptomatic screening, 1,089 (credible interval [CI], 946-1,253) total SARS-CoV-2 infections (7.72%) went undetected. With 1-stage antigen screening, 734 (CI, 638-845) asymptomatic infections (67.4%) were detected, with 1,277 false positives. With combined antigen and PCR screening, 1,007 (CI, 875-1,159) asymptomatic infections (92.5%) were detected, with 5,578 false positives. A serial antigen testing policy detected 973 (CI, 845-1,120) asymptomatic infections (89.4%), with 2,529 false positives. CONCLUSIONS: Serial antigen testing identified >85% of asymptomatic infections and resulted in fewer false positives with less cost per identified infection compared to combined antigen plus PCR testing.

Tough Talks COVID-19 Digital Health Intervention for Vaccine Hesitancy Among Black Young Adults: Protocol for a Hybrid Type 1 Effectiveness Implementation Randomized Controlled Trial.

BACKGROUND: Interventions for increasing the uptake of COVID-19 vaccination among Black young adults are central to ending the pandemic. Black young adults experience harms from structural forces, such as racism and stigma, that reduce receptivity to traditional public health messaging due to skepticism and distrust. As such, Black young adults continue to represent a priority population on which to focus efforts for promoting COVID-19 vaccine uptake. OBJECTIVE: In aims 1 and 2, the Tough Talks digital health intervention for HIV disclosure will be adapted to address COVID-19 vaccine hesitancy and tailored to the experiences of Black young adults in the southern United States (Tough Talks for COVID-19). In aim 3, the newly adapted Tough Talks for COVID-19 digital health intervention will be tested across the following three southern states: Alabama, Georgia, and North Carolina. METHODS: Our innovative digital health intervention study will include qualitative and quantitative assessments. A unique combination of methodological techniques, including web-based surveys, choose-your-own-adventures, digital storytelling, user acceptability testing, and community-based participatory approaches, will culminate in a 2-arm hybrid type 1 effectiveness implementation randomized controlled trial, wherein participants will be randomized to the Tough Talks for COVID-19 intervention arm or a standard-of-care control condition (N=360). Logistic regression will be used to determine the effect of the treatment arm on the probability of vaccination uptake (primary COVID-19 vaccine series or recommended boosters). Concurrently, the inner and outer contexts of implementation will be ascertained and catalogued to inform future scale-up. Florida State University's institutional review board approved the study (STUDY00003617). RESULTS: Our study was funded at the end of April 2021. Aim 1 data collection concluded in early 2022. The entire study is expected to conclude in January 2025. CONCLUSIONS: If effective, our digital health intervention will be poised for broad, rapid dissemination to reduce COVID-19 mortality among unvaccinated Black young adults in the southern United States. Our findings will have the potential to inform efforts that seek to address medical mistrust through participatory approaches. The lessons learned from the conduct of our study could be instrumental in improving health care engagement among Black young adults for several critical areas that disproportionately harm this community, such as tobacco control and diabetes prevention. TRIAL REGISTRATION: ClinicalTrials.gov NCT05490329; https://clinicaltrials.gov/ct2/show/NCT05490329. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41240.

Using narratives to inform the development of a digital health intervention related to COVID-19 vaccination in Black young adults in Georgia, North Carolina and Alabama.

Interactive stories are a relatively newer form of storytelling with great potential to correct misinformation while increasing self-efficacy, which is crucial to vaccine acceptance. To address COVID-19 vaccine hesitancy and medical mistrust in young Black adults (BYA), we sought to adapt a pre-existing application ("app"; Tough Talks) designed to address HIV disclosure decision-making through choose-your-own adventure (CYOA) narratives and other activities. The adapted app (Tough Talks - COVID) uses a similar approach to situate COVID-19 vaccination decision-making within social contexts and to encourage greater deliberation about decisions. To inform content for the CYOA narratives, we conducted an online survey that was used to elicit the behavioral, cognitive, and environmental determinants influencing COVID-19 vaccine hesitancy among 150 BYA (ages 18-29) in Georgia, Alabama, and North Carolina. The survey included scenario questions that were developed with input from a youth advisory board to understand responses to peer and family influences. In two scenarios that involved discussions with family and friends about vaccination status, most respondents chose to be honest about their vaccination status. However, vaccinated individuals perceived more social pressure and stigma about not being vaccinated than unvaccinated respondents who were not as motivated by social pressure. Personal choice/agency in the face of perceived vaccine risks was a more common theme for unvaccinated respondents. Results suggest that relying on changing social norms alone may not impact barriers to vaccination in unvaccinated young adults without also addressing other barriers to vaccination such as concerns about autonomy and vaccine safety. Based on these findings, CYOA narratives in the app were adapted to include discussions with family and friends but also to touch on themes of personal choice as well as other topics that influence behaviors besides norms such as safety, side effects, and risk of COVID-19 in an evolving pandemic.

Incorporation of near-real-time hospital occupancy data to improve hospitalization forecast accuracy during the COVID-19 pandemic.

Public health decision makers rely on hospitalization forecasts to inform COVID-19 pandemic planning and resource allocation. Hospitalization forecasts are most relevant when they are accurate, made available quickly, and updated frequently. We rapidly adapted an agent-based model (ABM) to provide weekly 30-day hospitalization forecasts (i.e., demand for intensive care unit [ICU] beds and non-ICU beds) by state and region in North Carolina for public health decision makers. The ABM was based on a synthetic population of North Carolina residents and included movement of agents (i.e., patients) among North Carolina hospitals, nursing homes, and the community. We assigned SARS-CoV-2 infection to agents using county-level compartmental models and determined agents' COVID-19 severity and probability of hospitalization using synthetic population characteristics (e.g., age, comorbidities). We generated weekly 30-day hospitalization forecasts during May-December 2020 and evaluated the impact of major model updates on statewide forecast accuracy under a SARS-CoV-2 effective reproduction number range of 1.0-1.2. Of the 21 forecasts included in the assessment, the average mean absolute percentage error (MAPE) was 7.8% for non-ICU beds and 23.6% for ICU beds. Among the major model updates, integration of near-real-time hospital occupancy data into the model had the largest impact on improving forecast accuracy, reducing the average MAPE for non-ICU beds from 6.6% to 3.9% and for ICU beds from 33.4% to 6.5%. Our results suggest that future pandemic hospitalization forecasting efforts should prioritize early inclusion of hospital occupancy data to maximize accuracy.

Estimates of Presumed Population Immunity to SARS-CoV-2 by State in the United States, August 2021.

BACKGROUND: Information is needed to monitor progress toward a level of population immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sufficient to disrupt viral transmission. We estimated the percentage of the US population with presumed immunity to SARS-CoV-2 due to vaccination, natural infection, or both as of August 26, 2021. METHODS: Publicly available data as of August 26, 2021, from the Centers for Disease Control and Prevention were used to calculate presumed population immunity by state. Seroprevalence data were used to estimate the percentage of the population previously infected with SARS-CoV-2, with adjustments for underreporting. Vaccination coverage data for both fully and partially vaccinated persons were used to calculate presumed immunity from vaccination. Finally, we estimated the percentage of the total population in each state with presumed immunity to SARS-CoV-2, with a sensitivity analysis to account for waning immunity, and compared these estimates with a range of population immunity thresholds. RESULTS: In our main analysis, which was the most optimistic scenario, presumed population immunity varied among states (43.1% to 70.6%), with 19 states with ≤60% of their population having been infected or vaccinated. Four states had presumed immunity greater than thresholds estimated to be sufficient to disrupt transmission of less infectious variants (67%), and none were greater than the threshold estimated for more infectious variants (≥78%). CONCLUSIONS: The United States remains a distance below the threshold sufficient to disrupt viral transmission, with some states remarkably low. As more infectious variants emerge, it is critical that vaccination efforts intensify across all states and ages for which the vaccines are approved.