Factors Associated with COVID-19 Vaccination Promptness after Eligibility in a North Carolina Longitudinal Cohort Study.

Many studies identified factors associated with vaccination intention and hesitancy, but factors associated with vaccination promptness and the effect of vaccination intention on vaccination promptness are unknown. This study identified factors associated with COVID-19 vaccination promptness and evaluated the role of vaccination intention on vaccination promptness in 1223 participants in a community-based longitudinal cohort study (June 2020 to December 2021). Participants answered questions regarding COVID-19 vaccination intention, vaccination status, and reasons for not receiving a vaccine. The association of baseline vaccine hesitancy with vaccination was assessed by the Kaplan-Meier survival analysis. Follow-up analyses tested the importance of other variables predicting vaccination using the Cox proportional hazards model. Older age was associated with shorter time to vaccination (HR = 1.76 [1.37-2.25] 85-year-old versus 65-year-old). Lower education levels (HR = 0.80 [0.69-0.92]), household incomes (HR = 0.84 [0.72-0.98]), and baseline vaccination intention of 'No' (HR = 0.16 [0.11-0.23]) were associated with longer times to vaccination. The most common reasons for not being vaccinated (N = 58) were vaccine safety concerns (n = 33), side effects (n = 28), and vaccine effectiveness (n = 25). Vaccination campaigns that target populations prone to hesitancy and address vaccine safety and effectiveness could be helpful in future vaccination rollouts.

Access to COVID-19 testing by individuals with housing insecurity during the early days of the COVID-19 pandemic in the United States: a scoping review.

Introduction: The COVID-19 pandemic focused attention on healthcare disparities and inequities faced by individuals within marginalized and structurally disadvantaged groups in the United States. These individuals bore the heaviest burden across this pandemic as they faced increased risk of infection and difficulty in accessing testing and medical care. Individuals experiencing housing insecurity are a particularly vulnerable population given the additional barriers they face. In this scoping review, we identify some of the barriers this high-risk group experienced during the early days of the pandemic and assess novel solutions to overcome these barriers. Methods: A scoping review was performed following PRISMA-Sc guidelines looking for studies focusing on COVID-19 testing among individuals experiencing housing insecurity. Barriers as well as solutions to barriers were identified as applicable and summarized using qualitative methods, highlighting particular ways that proved effective in facilitating access to testing access and delivery. Results: Ultimately, 42 studies were included in the scoping review, with 143 barriers grouped into four categories: lack of cultural understanding, systemic racism, and stigma; medical care cost, insurance, and logistics; immigration policies, language, and fear of deportation; and other. Out of these 42 studies, 30 of these studies also suggested solutions to address them. Conclusion: A paucity of studies have analyzed COVID-19 testing barriers among those experiencing housing insecurity, and this is even more pronounced in terms of solutions to address those barriers. Expanding resources and supporting investigators within this space is necessary to ensure equitable healthcare delivery.

Evaluation of SARS-CoV-2 identification methods through surveillance of companion animals in SARS-CoV-2-positive homes in North Carolina, March to December 2020.

We collected oral and/or rectal swabs and serum from dogs and cats living in homes with SARS-CoV-2-PCR-positive persons for SARS-CoV-2 PCR and serology testing. Pre-COVID-19 serum samples from dogs and cats were used as negative controls, and samples were tested in duplicate at different timepoints. Raw ELISA results scrutinized relative to known negative samples suggested that cut-offs for IgG seropositivity may require adjustment relative to previously proposed values, while proposed cut-offs for IgM require more extensive validation. A small number of pet dogs (2/43, 4.7%) and one cat (1/21, 4.8%) were positive for SARS-CoV-2 RNA, and 28.6 and 37.5% of cats and dogs were positive for anti-SARS-CoV-2 IgG, respectively.

RADx-UP Testing Core: Access to COVID-19 Diagnostics in Community-Engaged Research with Underserved Populations.

Research on the COVID-19 pandemic revealed a disproportionate burden of COVID-19 infection and death among underserved populations and exposed low rates of SARS-CoV-2 testing in these communities. A landmark National Institutes of Health (NIH) funding initiative, the Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program, was developed to address the research gap in understanding the adoption of COVID-19 testing in underserved populations. This program is the single largest investment in health disparities and community-engaged research in the history of the NIH. The RADx-UP Testing Core (TC) provides community-based investigators with essential scientific expertise and guidance on COVID-19 diagnostics. This commentary describes the first 2 years of the TC's experience, highlighting the challenges faced and insights gained to safely and effectively deploy large-scale diagnostics for community-initiated research in underserved populations during a pandemic. The success of RADx-UP shows that community-based research to increase access and uptake of testing among underserved populations can be accomplished during a pandemic with tools, resources, and multidisciplinary expertise provided by a centralized testing-specific coordinating center. We developed adaptive tools to support individual testing strategies and frameworks for these diverse studies and ensured continuous monitoring of testing strategies and use of study data. In a rapidly evolving setting of tremendous uncertainty, the TC provided essential and real-time technical expertise to support safe, effective, and adaptive testing. The lessons learned go beyond this pandemic and can serve as a framework for rapid deployment of testing in response to future crises, especially when populations are affected inequitably.

Influenza Vaccination Implementation in Sri Lanka: A Cost-Effectiveness Analysis.

Influenza causes an estimated 3 to 5 million cases of severe illness annually, along with substantial morbidity and mortality, particularly in low- and middle-income countries (LMICs). Currently, Sri Lanka has no influenza vaccination policies and does not offer vaccination within the public healthcare sector. Therefore, we performed a cost-effectiveness analysis of influenza vaccine implementation for the Sri Lankan population. We designed a static Markov model that followed a population cohort of Sri Lankans in three age groups, 0-4, 5-64, and 65+ years, through two potential scenarios: trivalent inactivated vaccination (TIV) and no TIV across twelve-monthly cycles using a governmental perspective at the national level. We also performed probabilistic and one-way sensitivity analyses to identify influential variables and account for uncertainty. The vaccination model arm reduced influenza outcomes by 20,710 cases, 438 hospitalizations, and 20 deaths compared to no vaccination in one year. Universal vaccination became cost-effective at approximately 98.01% of Sri Lanka's 2022 GDP per capita (incremental cost-effectiveness ratio = 874,890.55 Rs/DALY averted; 3624.84 USD/DALY averted). Results were most sensitive to the vaccine coverage in the 5-64-year-old age group, the cost of the influenza vaccine dose in the 5-64-years-old age group, vaccine effectiveness in the under-5-years-old age group, and the vaccine coverage in the under-5-years-old age group. No value for a variable within our estimated ranges resulted in ICERs above Rs. 1,300,000 (USD 5386.15) per DALY adverted. Providing influenza vaccines was considered highly cost-effective compared to no vaccines. However, large-scale national studies with improved data are needed to better inform estimates and determine the impact of vaccination implementation.

COVID-19 Infection Risk Among Previously Uninfected Adults: Development of a Prognostic Model.

Background: Few models exist that incorporate measures from an array of individual characteristics to predict the risk of COVID-19 infection in the general population. The aim was to develop a prognostic model for COVID-19 using readily obtainable clinical variables. Methods: Over 74 weeks surveys were periodically administered to a cohort of 1381 participants previously uninfected with COVID-19 (June 2020 to December 2021). Candidate predictors of incident infection during follow-up included demographics, living situation, financial status, physical activity, health conditions, flu vaccination history, COVID-19 vaccine intention, work/employment status, and use of COVID-19 mitigation behaviors. The final logistic regression model was created using a penalized regression method known as the least absolute shrinkage and selection operator. Model performance was assessed by discrimination and calibration. Internal validation was performed via bootstrapping, and results were adjusted for overoptimism. Results: Of the 1381 participants, 154 (11.2%) had an incident COVID-19 infection during the follow-up period. The final model included six variables: health insurance, race, household size, and the frequency of practicing three mitigation behavior (working at home, avoiding high-risk situations, and using facemasks). The c-statistic of the final model was 0.631 (0.617 after bootstrapped optimism-correction). A calibration plot suggested that with this sample the model shows modest concordance with incident infection at the lowest risk. Conclusion: This prognostic model can help identify which community-dwelling older adults are at the highest risk for incident COVID-19 infection and may inform medical provider counseling of their patients about the risk of incident COVID-19 infection.

Mitigation behavior prior to COVID-19 vaccination availability is associated with COVID-19 infection and time to vaccination.

BACKGROUND: Mitigation behaviors reduce the incidence of COVID-19 infection. Determining characteristics of groups defined by mitigation behaviors compliance may be useful to inform targeted public health policies and interventions. This study aimed to identify groups of individuals according to self-reported compliance with COVID-19 mitigation behaviors, define compliance class characteristics, and explore associations between compliance classes and important study and public health outcomes. METHODS AND FINDINGS: We studied 1,410 participants in the Cabarrus County COVID-19 Prevalence and Immunity longitudinal cohort study (June 2020 to December 2021) who were asked 10 questions regarding compliance with recommended COVID-19 mitigation behaviors. By Latent Class Analysis, 1,381 participants were categorized into 3 classes (most [49.4%], moderately [45.0%], and least [5.6%] compliant). Compared with the most compliant class, the least and moderately compliant classes were younger (mean = 61.9 v. 59.0 v. 53.8 years), had fewer medical conditions per individual (1.37 v. 1.08 v. 0.77), and differed in Hispanic ethnicity (6.2% v. 2.8% v. 9.1%) and COVID-19 vaccine intention (65.8% v. 59.8% v. 35.1%). Compared to the most compliant class, the least compliant class had fewer women (54.6% v. 76.3%), fewer insured individuals (92.2% v. 97.4%), and more withdrew from study participation early (28.6% v. 16.0%). Relative to the most compliant class, the least compliant class had a higher likelihood of COVID-19 infection (OR = 2.08 [95% CI 1.13, 3.85]), lower rate of COVID-19 vaccination (72.6% v. 95.1%), and longer time to 50% COVID-19 vaccination following eligibility (8-9 vs 16 days). CONCLUSIONS: Classes defined by mitigation behaviors compliance had distinct characteristics, including age, sex, medical history, and ethnicity, and were associated with important study and public health outcomes. Targeted public health policies and interventions according to the compliance group characteristics may be of value in current and future pandemic responses to increase compliance.

The Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study: design, methods, and baseline characteristics.

OBJECTIVES: Coronavirus Disease 2019 (COVID-19) is a viral illness with public health importance. The Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study is a prospective, longitudinal cohort study designed to contribute valuable information on community prevalence of active COVID-19 infection and SARS-CoV-2 antibodies as the pandemic and responses to it have and continue to evolve. We present the rationale, study design, and baseline characteristics of the C3PI Study. METHODS: We recruited 1,426 participants between June 2020 and August 2020 from the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) Study Community Registry and Biorepository, a previously established, community-based, longitudinal cohort. Participants completed a baseline survey and follow-up surveys every two weeks. A nested weighted, random sub-cohort (n=300) was recruited to measure the incidence and prevalence of active COVID-19 infection and SARS-CoV-2 IgG antibodies. RESULTS: The sub-cohort was younger (56 vs 61 years), had more men (39.0% vs 30.9%), and a higher proportion of Hispanic (11.0% vs 5.1%) and Black participants (17.0% vs 8.2%) compared with the overall cohort. They had similar anthropometrics and medical histories, but a greater proportion of the sub-cohort had a higher educational degree (36.1% vs 31.3%) and reported a pre-pandemic annual household income of >$90,000 (57.1% vs 47.9%). CONCLUSION: This study is part of a multisite consortium that will provide critical data on the epidemiology of COVID-19 and community perspectives about the pandemic, behaviors and mitigation strategies, and individual and community burden in North Carolina.

Comparison of a Blood Self-Collection System with Routine Phlebotomy for SARS-CoV-2 Antibody Testing.

The Coronavirus Disease 2019 (COVID-19) pandemic forced researchers to reconsider in-person assessments due to transmission risk. We conducted a pilot study to evaluate the feasibility of using the Tasso-SST (Tasso, Inc, Seattle, Washington) device for blood self-collection for use in SARS-CoV-2 antibody testing in an ongoing COVID-19 prevalence and immunity research study. 100 participants were recruited between January and March 2021 from a previously identified sub-cohort of the Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study who were under-going bimonthly COVID-19 antibody testing. Participants were given a Tasso-SST kit and asked to self-collect blood during a scheduled visit where trained laboratory personnel performed routine phlebotomy. All participants completed an after-visit survey about their experience. Overall, 70.0% of participants were able to collect an adequate sample for testing using the device. Among those with an adequate sample, there was a high concordance in results between the Tasso-SST and phlebotomy blood collection methods (Cohen's kappa coefficient = 0.88, Interclass correlation coefficient 0.98 [0.97, 0.99], p < 0.0001). The device received a high-level (90.0%) of acceptance among all participants. Overall, the Tasso-SST could prove to be a valuable tool for seroprevalence testing. However, future studies in larger, diverse populations over longer periods may provide a better understanding of device usability and acceptance among older participants and those with comorbidities in various use scenarios.