A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

Area of Science:

• Epidemiology
• Infectious Disease Dynamics
• Genomic Epidemiology

Background:

• Identifying linked infections is crucial for controlling viral outbreaks.
• Rapid assessment of infection transmission pathways is needed in clinical settings.
• Viral genome sequencing aids in determining infection links but requires integration with other data.

Purpose of the Study:

• To introduce A2B-COVID, a novel method for rapid identification of potentially linked COVID-19 cases in clinical environments.
• To assess the utility of integrating infection dynamics, individual movement data, and genomic analysis for transmission linkage.
• To evaluate the method's performance in distinguishing independent versus directly transmitted infections.

Main Methods:

• A2B-COVID integrates epidemiological data, patient movement logs, and viral genome sequence analysis.
• The method assesses the consistency of case data with direct transmission events.
• Retrospective and real-time analyses were conducted using hospital ward data.

Main Results:

• A2B-COVID demonstrated the ability to rapidly identify potentially linked COVID-19 cases.
• Retrospective analysis revealed distinct linkage patterns on COVID-19 and non-COVID-19 wards.
• Real-time application confirmed the method's value for ongoing infection monitoring.

Conclusions:

• A2B-COVID provides a valuable tool for clinical settings to assess COVID-19 transmission links.
• The integration of diverse data streams enhances the accuracy of linkage identification.
• The method supports effective public health interventions during viral outbreaks.