ABSTRACT
Well-regulated clinical trials have shown FDA-approved COVID-19 vaccines to be immunogenic and highly efficacious. We evaluated seroconversion rates in adults reporting ≥ 1 dose of an mRNA COVID-19 vaccine in a cohort study of nearly 8000 adults residing in North Carolina to validate immunogenicity using a novel approach: at-home, participant administered point-of-care testing. Overall, 91.4% had documented seroconversion within 75 days of first vaccination (median: 31 days). Participants who were older and male participants were less likely to seroconvert (adults aged 41-65: adjusted hazard ratio [aHR] 0.69 [95% confidence interval (CI): 0.64, 0.73], adults aged 66-95: aHR 0.55 [95% CI: 0.50, 0.60], compared to those 18-40; males: aHR 0.92 [95% CI: 0.87, 0.98], compared to females). Participants with evidence of prior infection were more likely to seroconvert than those without (aHR 1.50 [95% CI: 1.19, 1.88]) and those receiving BNT162b2 were less likely to seroconvert compared to those receiving mRNA-1273 (aHR 0.84 [95% CI: 0.79, 0.90]). Reporting at least one new symptom after first vaccination did not affect time to seroconversion, but participants reporting at least one new symptom after second vaccination were more likely to seroconvert (aHR 1.11 [95% CI: 1.05, 1.17]). This data demonstrates the high community-level immunogenicity of COVID-19 vaccines, albeit with notable differences in older adults, and feasibility of using at-home, participant administered point-of-care testing for community cohort monitoring. Trial registration: ClinicalTrials.gov NCT04342884.
Subject(s)
COVID-19 , Vaccines , Aged , Antibodies, Viral , BNT162 Vaccine , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Cohort Studies , Female , Humans , Immunogenicity, Vaccine , Male , North Carolina/epidemiology , RNA, Messenger , SeroconversionABSTRACT
VisualCommunity is a platform designed to support community or neighborhood scale research. The platform integrates mobile, AI, visualization techniques, along with tools to help domain researchers, practitioners, and students collecting and working with spatialized video and geo-narratives. These data, which provide granular spatialized imagery and associated context gained through expert commentary have previously provided value in understanding various community-scale challenges. This paper further enhances this work AI-based image processing and speech transcription tools available in VisualCommunity, allowing for the easy exploration of the acquired semantic and visual information about the area under investigation. In this paper we describe the specific advances through use case examples including COVID-19 related scenarios.