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• W4313277734 abstract "SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape.Analysis of SARS-CoV-2 genomes in King County, Washington show that diverse areas in the same metropolitan region can have different epidemic dynamics." @default.
• W4313277734 created "2023-01-06" @default.
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• W4313277734 date "2022-12-16" @default.
• W4313277734 modified "2023-10-11" @default.
• W4313277734 title "Local-Scale phylodynamics reveal differential community impact of SARS-CoV-2 in metropolitan US county" @default.
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• W4313277734 doi "https://doi.org/10.1101/2022.12.15.22283536" @default.
• W4313277734 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36561171" @default.
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