A collaborative approach to improving representation in viral genomic surveillance

Abstract

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building ‘next generation’ genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness.