Network-Targeted Strategies for Efficient Community SARS-CoV-2 (COVID-19) Sampling

Purpose and objective: The purpose of this study is to use community sampling to detect active, undiagnosed COVID-19 cases and/or determine the spread or distribution of active infection. The objective is to use a network targeted sampling design to direct testing to yield a higher proportion of results which indicate active infection and possibly differentiating between venues or communities where transmission is active and undiagnosed.

Study activities: A person who tests positive for COVID-19 will be given a set of "tokens" to give to contacts that will entitle these contacts to make an appointment to receive a test for COVID-19.

Population groups: The population group will include people with index cases of COVID-19 and their contacts for the past 14 days. As these contacts are tested and receive positive results, they will be given tokens to hand out to their contacts over the past 14 days. The network of positive cases will "blossom" to reveal community transmission and asymptomatic cases, thus giving researchers an indication of disease prevalence.

Data analysis: At the completion of each epoch and at the end of the study, we will scale the social networks up and conduct network analysis using SAS and the igraph package in R. These analyses will be applied in an ongoing manner to guide selection of seeds in subsequent epochs to ensure representativeness and to guide selection of alters to encourage longer referral chain lengths.

Risk/safety issues: The primary risks include discomfort from the nasal swab and risks from the venous blood draw used in testing and the potential loss of confidentiality. All efforts will be made to securely manage the data to ensure participant confidentiality.