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112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West

Published online by Cambridge University Press:  19 April 2022

Daryl Domman
Affiliation:
Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center Clinical and Translational Science Center, University of New Mexico Health Sciences Center
Valerie Morley
Affiliation:
Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center
Kurt Schwalm
Affiliation:
Department of Pediatrics, University of New Mexico Health Sciences Center
Jesse Young
Affiliation:
Department of Pediatrics, University of New Mexico Health Sciences Center
Anastacia Griego
Affiliation:
Scientific Laboratory Division, New Mexico Department of Health
Margaret Siebert
Affiliation:
Epidemiology and Response Division, New Mexico Department of Health
Michael Edwards
Affiliation:
Scientific Laboratory Division, New Mexico Department of Health
Emma Goldberg
Affiliation:
The New Mexico Consortium, Los Alamos, NM
Darrell Dinwiddie
Affiliation:
Department of Pediatrics, University of New Mexico Health Sciences Center
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Abstract

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OBJECTIVES/GOALS: Understanding how SARS-CoV-2 is evolving as well as spreading within and between communities is vital for the design of rational, evidence-based control measures. Continuous genomic surveillance is imperative to identify and track variants and can be paired with clinical data, to identify associations with severity or vaccine breakthroughs. METHODS/STUDY POPULATION: In June of 2021, we established UNM as a CDC-funded hub for genomic surveillance of SARS-CoV-2 for New Mexico and 3 other Rocky Mountain region states (Wyoming, Idaho, Montana). Through our Rocky Mountain COVID Consortium (RMCC), we have sequenced over 6,000 genomes of SARS-CoV-2 from RMCC partners. For New Mexico we integrate county and zip code data to provide more granular insights into how SARS-CoV-2, and particular variants, are transmitting within the state. We also pair this data with vaccine breakthrough cases identified by the NMDOH, as well as with clinical outcome data. RESULTS/ANTICIPATED RESULTS: We sequenced over 6,000 SARS-CoV-2 genomes from New Mexico (n=3091), Idaho (n=1538), Arkansas (n=1101), Wyoming (n=251), and Montana (n=33). We used this data to infer the transmission dynamics, identify variants, and map the spread of the virus. We identified a novel local variant that spread across New Mexico in early 2021, but was quickly replaced by the Alpha variant. In all RMCC states, the Delta variant overtook Alpha and has become nearly the only variant currently circulating in these states. We identified sequenced isolates from vaccine breakthrough cases in NM and demonstrate their role in onward transmission. We can identify shifts at a county or zip-code level in circulating lineages which may correspond to clinical outcomes or fluctuating case counts. DISCUSSION/SIGNIFICANCE: This integrated genomic data can be used by policy and decision makers within the New Mexico Department of Health and our RMCC partners to guide their public health response to the COVID-19 pandemic.

Type
Community Engagement
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. The Association for Clinical and Translational Science