RESUMEN
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.
Asunto(s)
COVID-19 , Epidemias , Humanos , SARS-CoV-2/genética , COVID-19/epidemiología , Washingtón/epidemiologíaRESUMEN
The rapid emergence of SARS-CoV-2 variants raised public health questions concerning the capability of diagnostic tests to detect new strains, the efficacy of vaccines, and how to map the geographical distribution of variants to understand transmission patterns and loads on healthcare resources. Next-generation sequencing (NGS) is the primary method for detecting and tracing new variants, but it is expensive, and it can take weeks before sequence data are available in public repositories. This article describes a customizable reverse transcription PCR (RT-PCR)-based genotyping approach which is significantly less expensive, accelerates reporting, and can be implemented in any lab that performs RT-PCR. Specific single-nucleotide polymorphisms (SNPs) and indels were identified which had high positive-percent agreement (PPA) and negative-percent agreement (NPA) compared to NGS for the major genotypes that circulated through September 11, 2021. Using a 48-marker panel, testing on 1,031 retrospective SARS-CoV-2 positive samples yielded a PPA and NPA ranging from 96.3 to 100% and 99.2 to 100%, respectively, for the top 10 most prevalent World Health Organization (WHO) lineages during that time. The effect of reducing the quantity of panel markers was explored, and a 16-marker panel was determined to be nearly as effective as the 48-marker panel at lineage assignment. Responding to the emergence of Omicron, a genotyping panel was developed which distinguishes Delta and Omicron using four highly specific SNPs. The results demonstrate the utility of the condensed panel to rapidly track the growing prevalence of Omicron across the US in December 2021 and January 2022.
Asunto(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnóstico , Humanos , Técnicas de Amplificación de Ácido Nucleico , Estudios Retrospectivos , SARS-CoV-2/genéticaRESUMEN
BACKGROUND: Some mutations in the receptor binding domain of the SARS-CoV-2 Spike protein are associated with increased transmission or substantial reductions in vaccine efficacy, including in recently described Omicron subvariants. The changing frequencies of these mutations combined with their differing susceptibility to available therapies have posed significant problems for clinicians and public health professionals. OBJECTIVE: To develop an assay capable of rapidly and accurately identifying variants including Omicron in clinical specimens to enable case tracking and/or selection of appropriate clinical treatment. STUDY DESIGN: Using three duplex RT-ddPCR reactions targeting four amino acids, we tested 419 positive clinical specimens from February to December 2021 during a period of rapidly shifting variant prevalences and compared genotyping results to genome sequences for each sample, determining the sensitivity and specificity of the assay for each variant. RESULTS: Mutation determinations for 99.7% of detected samples agree with NGS data for those samples, and are accurate despite wide variation in RNA concentration and potential confounding factors like transport medium, presence of additional respiratory viruses, and additional mutations in primer and probe sequences. The assay accurately identified the first 15 Omicron variants in our laboratory including the first Omicron in Washington State and discriminated against S-gene dropout Delta specimen. CONCLUSION: We describe an accurate, precise, and specific RT-ddPCR assay for variant detection that remains robust despite being designed prior the emergence of Delta and Omicron variants. The assay can quickly identify mutations in current and past SARS-CoV-2 variants, and can be adapted to future mutations.
Asunto(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnóstico , Prueba de COVID-19 , Humanos , Reacción en Cadena de la Polimerasa , ARN Viral/análisis , ARN Viral/genética , SARS-CoV-2/genética , Glicoproteína de la Espiga del CoronavirusRESUMEN
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.