Sentinel Surveillance System Implementation and Evaluation for SARS-CoV-2 Genomic Data, Washington, USA, 2020-2021

Area of Science:

• Public Health Surveillance
• Genomic Epidemiology
• Infectious Disease Dynamics

Background:

• Genomic data combined with epidemiologic data is valuable for public health.
• Sampling bias in genomic surveillance can lead to misleading inferences.
• The Washington State Department of Health established sentinel surveillance for SARS-CoV-2 in March 2021.

Purpose of the Study:

• To assess the representativeness and timeliness of SARS-CoV-2 genomic data.
• To compare data from pre-sentinel and sentinel surveillance periods.
• To identify areas for improvement in public health genomic surveillance systems.

Main Methods:

• Analysis of available genomic and epidemiologic data during pre-sentinel and sentinel periods.
• Evaluation of data representativeness across various demographic and clinical factors.
• Assessment of data timeliness and viral diversity captured.

Main Results:

• Pre-sentinel genomic data was largely unrepresentative of all COVID-19 cases.
• Sentinel surveillance improved data representativeness for age, death, outbreak association, long-term care facility affiliation, and geographic coverage.
• Hospitalized cases were underrepresented in the sentinel data, indicating a need for increased inpatient sampling.

Conclusions:

• Sentinel surveillance significantly enhanced the quality of SARS-CoV-2 genomic data.
• Underrepresentation of hospitalized cases necessitates targeted improvements in sampling strategies.
• Continuous evaluation and refinement of public health surveillance systems are crucial for accurate phylogenetic studies and public health practice.