SUMMARY Monitoring of the incidence, morbidity, and mortality of respiratory infections has largely been performed by collecting and analyzing data from hospitals and clinical laboratories. While these data sources provide valuable information on risk factors, incidence, therapeutic response, and outcomes of severe disease, they do not reflect the range of potential clinical presentations and courses of disease, factors that increase or decrease the risk of community transmission, and the impact of disease on education and employment. We therefore propose to create “PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement,” which will serve as one of the CDC Pandemic Preparedness Network Cohorts and the Network’s Data Hub. We will participate in Components A1, A2, B, and C, with a catchment that spans San Diego County in HHS Region 9 adjacent to the U.S./Mexico border. Our relevant experience includes establishment of innovative programs for large-scale COVID-19 clinical testing, environmental surveillance through monitoring of wastewater and surface swabs, viral genome sequencing, and monitoring of immunity using co-created community-based sample collection strategies that are highly accessible and culturally sensitive. Major PREVENT activities will include: Component A1: We will enroll and retain a diverse longitudinal cohort of 2,000 individuals for: weekly symptom screening; surveys on knowledge, attitudes, and behaviors related to preventative measures; extraction of outcome and vaccination data from electronic health records and immunization information systems; and collection of follow-up data from participants on use of preventative/therapeutic measures and healthcare resources, missed school/work, symptom type/duration, and long-term sequelae. Symptomatic swabs will be collected and tested for 20 high-priority respiratory pathogens. Viral genome sequencing will be performed on a subset of samples using targeted and metatranscriptomic methods. Samples will be banked for >5 years. Component A2: Serial blood samples will be collected, analyzed, and banked from 20% of participants in Component A1. Samples will be collected at enrollment, in the months flanking the respiratory infection season, before/after vaccinations, and after infection. Quantitative immunoassays for antigen-specific antibody (Ab) levels and neutralizing antibody (nAb) levels against contemporary circulating virus isolates will be performed. Component B: For >100 index cases from A1 per year, we will collect and test daily nasal swabs from >75% of household members for >2 weeks. A subset of swabs (including at least 1 per index case) will be analyzed by viral genome sequencing, and high-priority pathogens/variants will be cultured. For a subset of households, we will also explore the relationships between viral load (quantified by qPCR) and viral titer (by in vitro cell-based assay), and between viral culture positivity and transmission. Component C: We will serve as the Data Hub and Warehouse, and support protocol development across the network, provide data entry and management tools, analyze data; and develop dashboards/visualizations.

NARRATIVE “PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement” proposes to participate in Components A1, A2, and B of the CDC Pandemic Preparedness Network by enrolling and retaining a diverse longitudinal community cohort of 2,000 individuals for collection of longitudinal symptom screening, respiratory pathogen testing and sequencing, assessment of immunity, and case-ascertained tracking of transmission. PREVENT also proposes to serve as the Data Hub for all nine CDC Pandemic Preparedness Network cohorts that will provide real-time publicly accessible data on incidence of the most common respiratory infections. Results from this project will provide information on risk factors, incidence, clinical courses, and impacts of important respiratory pathogens, that can be used for individual, institutional, and public health infection risk and infectious disease management.