A collaborative approach to improving representation in viral genomic surveillance

Area of Science:

• Public Health
• Genomic Epidemiology
• Infectious Disease Surveillance

Background:

• Delayed viral genomic surveillance hindered early SARS-CoV-2 detection in the U.S., facilitating widespread transmission.
• Insufficient surveillance allowed for the unnoticed emergence and spread of novel SARS-CoV-2 variants.
• Existing social and racial inequities exacerbated the impact of the epidemic, disproportionately affecting minority populations.

Purpose of the Study:

• To develop and implement a novel variant surveillance model to enhance genomic sequencing capacity.
• To establish a network of university-based genomic surveillance in rural areas.
• To foster community engagement and collaboration with local health clinics for improved pandemic readiness.

Main Methods:

• Developed a "next generation" genome sequencing capacity model at universities in or near rural locations.
• Engaged local communities and established partnerships with academic teams and local health clinics.
• Generated over 1,000 SARS-CoV-2 genomes, including identification of key variants like Omicron, BA.2.75, and BQ.1.1.

Main Results:

• The genomic surveillance network successfully identified early cases of significant SARS-CoV-2 variants in specific regions.
• Higher viral gene copy numbers were observed in Delta variant infections compared to Omicron BA.1.
• Lower viral gene copy numbers were associated with asymptomatic infections versus symptomatic ones.

Conclusions:

• Establishing genomic surveillance capacity at smaller academic institutions in rural areas is a viable strategy.
• Fostering collaborations between academic institutions and local health clinics strengthens pandemic preparedness.
• This model effectively addresses gaps in viral surveillance and contributes to public health equity.