Genomic diversity of respiratory pathogens in clinical versus community surveillance: a comparative analysis of SARS-CoV-2, RSV, and influenza viruses in Washington State

Background Genomic surveillance of respiratory viruses typically relies on sequences from individuals seeking health care, and whether these sequences represent the viruses circulating in the community is not well-characterized. We aimed to compare the diversity, proportion, and dynamics of influenza, respiratory syncytial virus (RSV), and SARS-CoV-2 between clinical and community samples. Methods In this retrospective comparative genomic analysis, we used whole-genome sequences from community-based surveillance studies in the Seattle area, and clinical sequences from the Washington State Department of Health. We compared clade proportions and dynamics, sequence-cluster diversity, non-synonymous mutations, and Ct values between clinical and community samples. Findings We analyzed 538 RSV sequences collected between 2019 and 2021 (278 community, 260 clinical), 1506 influenza sequences (260 community, 1246 clinical) between 2019 and 2020, and 8660 SARS-CoV-2 sequences (5923 community, 2737 clinical) from 2020 to 2022. Clade proportions did not differ between clinical and community samples for RSV or influenza, but differed for SARS-CoV-2: clades 21J (Delta) and 21K (Omicron BA.1) were more frequent in community samples and clade 22B (Omicron BA.5) in clinical samples. SARS-CoV-2 clinical sequence clusters were more diverse than community clusters, whereas RSV and influenza showed no significant difference. Several spike mutations associated with monoclonal antibody resistance were more prevalent in community samples for SARS-CoV-2. Ct values were lower in clinical samples for multiple SARS-CoV-2, RSV, and influenza clades. Interpretation Seasonal respiratory viruses had similar dynamics and diversity in clinical and community samples, whereas pandemic SARS-CoV-2 differed between settings. Genomic surveillance programs should combine clinical and community sampling, particularly during pandemics in order to better capture viral diversity.