COVID-19 Community Infection and Immunity Surveillance

Principal Investigator: Casey Cazer

Co-PI: Bettina Wagner, Diego Diel, Kevin Cummings

Department of Population Medicine and Diagnostic Sciences
Sponsor: The David and Lucile Packard Foundation
Grant Number: 2021-72608
Title: COVID-19 Community Infection and Immunity Surveillance
Project Amount: $300,000
Project Period: September 2021 to August 2023

DESCRIPTION (provided by applicant): 

Over one year into the COVID-19 pandemic, our national focus has shifted from testing and tracing to vaccination. However, accurate and timely data on SARS-CoV-2 transmission, and now immunity, are still critical for appropriate local and national pandemic responses. The risk of COVID-19 infection is proportional to the number of people actively infected (prevalence) and the number of susceptible (non-immune) people. Therefore, the COVID-19 prevalence and percent of susceptible people in a geographic area are the ideal indicators to guide public health interventions, including increased testing, vaccinations, social restrictions, and mask use. Importantly, these indicators must be measured and acted upon at the local level because heterogeneity of comorbidities, behaviors, population density, and test and vaccine availability result in significant variability in epidemic trajectories across municipalities and regions.

Typical approaches used to estimate COVID-19 prevalence, such as counting confirmed cases or the test-positive rate, do not accurately represent the true burden of disease because asymptomatic infections, and lack of test availability/access result in an under-estimation of cases. Furthermore, immunity is expected to wane after vaccination, but the rate of decline in antibody titers after 6 months post-infection or post-vaccination and the correlation between antibody titers and protection against infection are still uncertain. SARS-CoV-2 variants introduce further uncertainty because vaccines have variable efficacy against common and emerging variants. Therefore, real-world data on active infections, immunity, and variants within a community are urgently needed to ensure successful COVID-19 control while economic and social restrictions are lifted.

Our goal is to estimate both active infection prevalence and immunity from both past infections and vaccination in our local community. Our work will provide a framework for gathering reliable COVID-19 prevalence, variant, and immunity data that local municipalities can use to guide their COVID-19 response. Importantly, we will adapt a door-to-door sampling approach for rural areas by combining mail-based recruitment with in-person sample collection. We expect the short-term outcomes to include unbiased estimates of COVID-19 prevalence and immunity, and improved understanding of the impact of COVID-19 and vaccination intent in different groups. The medium-term outcomes will include the development and implementation of interventions to reduce COVID-19 spread in high-risk groups, and outreach plans to increase vaccination rates. Our approach will be adaptable and scalable for assessing COVID-19 prevalence and immunity in rural and under-resourced communities.