TRACE-COVID-19 is an Oregon State University public health project designed to gather information about the presence of SARS-CoV-2, the virus that causes COVID-19, in communities. Throughout 2020-2021, TRACE (Team-based Rapid Assessment of community-level Coronavirus Epidemics) used random sampling to understand the prevalence of the virus, rather than relying on clinically reported cases which are subject to biases that changed over time. In this talk, we provide an overview of a targeted random door-to-door sampling method informed by community wastewater measurements we developed that was implemented in two communities in Oregon in 2021. The sampling design is a three-stage design with strata informed by microsewershed boundaries, clusters corresponding to one or more adjacent census blocks selected with probability proportional to size, and systematic sampling of housing units within clusters. The details of the design, data requirements for implementation, design-based analysis strategies, methods to address nonresponse and measurement error, and results will be discussed. This design is intended to allow the allocation of field teams collecting nasal swabs such that an unbiased prevalence estimate can be obtained while attempting to discover positive individuals. We also detail a simulation study framework that can be used to consider adapting the design across communities with different characteristics and different pathogens. The survey design and analysis for this project involve the integration of data at different spatial and temporal scales, including time series of wastewater measurements collected at microsewersheds throughout a community, Census data at the block level, and information provided by local public health officials. We also discuss lessons learned and how our sampling and surveillance techniques have evolved over the course of the pandemic. With an eye toward the future, we consider the role of survey data integration with epidemic modeling and passive surveillance to create cities that are more resilient to pandemics.

Authors: Jeffrey Bethel, Nicole Breuner, Benjamin Dalziel, Roy Haggerty, Kathryn Higley, Jane Lubchenco, Allison Myers, Javier Nieto, Justin Preece, Tyler Radniecki, Justin Sanders