Scalable Strategies to Increase Efficiency and Augment Public Health Activities During Epidemic Peaks

Abstract

Objective: Scalable strategies to reduce the time burden and increase contact tracing efficiency are crucial during early waves and peaks of infectious transmission. Design: We enrolled a cohort of SARS-CoV-2-positive seed cases into a peer recruitment study testing social network methodology and a novel electronic platform to increase contact tracing efficiency. Setting: Index cases were recruited from an academic medical center and requested to recruit their local social contacts for enrollment and SARS-CoV-2 testing. Participants: A total of 509 adult participants enrolled over 19 months (384 seed cases and 125 social peers). Intervention: Participants completed a survey and were then eligible to recruit their social contacts with unique “coupons” for enrollment. Peer participants were eligible for SARS-CoV-2 and respiratory pathogen screening. Main Outcome Measures: The main outcome measures were the percentage of tests administered through the study that identified new SARS-CoV-2 cases, the feasibility of deploying the platform and the peer recruitment strategy, the perceived acceptability of the platform and the peer recruitment strategy, and the scalability of both during pandemic peaks. Results: After development and deployment, few human resources were needed to maintain the platform and enroll participants, regardless of peaks. Platform acceptability was high. Percent positivity tracked with other testing programs in the area. Conclusions: An electronic platform may be a suitable tool to augment public health contact tracing activities by allowing participants to select an online platform for contact tracing rather than sitting for an interview.

Homophily and social mixing in a small community: Implications for infectious disease transmission

“…We enrolled seed cases who were recently diagnosed with SARS-CoV-2 at a large, academic medical center (Duke University Health System) into a snowball sampling study in which they could recruit their local community contacts for respiratory infection sampling (ClinicalTrials.gov ID NCT04437706). Enrollment occurred from December 2020-July 2022 (19 months), as previously described [ 18 ]. Briefly, residents of Durham County, North Carolina, USA who were recently diagnosed with SARS-CoV-2 and aged 18 years or older were invited to complete a survey and then recruit their contacts to complete the survey and receive SARS-CoV-2 testing within a snowball sampling protocol to detect new SARS-CoV-2 infections in the community.…”

“…gov ID NCT04437706). Enrollment occurred from December 2020-July 2022 (19 months), as previously described [18]. Briefly, residents of Durham County, North Carolina, USA who were recently diagnosed with SARS-CoV-2 and aged 18 years or older were invited to complete a survey and then recruit their contacts to complete the survey and receive SARS-CoV-2 testing within a snowball sampling protocol to detect new SARS-CoV-2 infections in the community.…”

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

“…To uphold privacy standards, these apps employ decentralized data storage and cryptographic techniques that safeguard sensitive data from unauthorized access. Through the implementation of AI technology, public health agencies can effectively trace potential infection routes, control outbreaks, and promptly notify individuals who may be at risk [105]. However, it is important to address privacy concerns that arise with the use of AI-powered contact tracing applications.…”