Estimation of Secondary Household Attack Rates for Emergent Spike L452R Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants Detected by Genomic Surveillance at a Community-Based Testing Site in San Francisco
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Abstract
Background: Sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities. Methods: SARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during 22 November to 1 December, 2020, and 10–29 January 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants. Results: A total of 12 124 tests were performed yielding 1099 positives. From these, 928 high-quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.4% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to the “California” or “West Coast” variants (B.1.427 and B.1.429) were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.36 vs 0.29, risk ratio [RR] = 1.28; 95% confidence interval [CI]: 1.00–1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.3%). Conclusions: The increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants. Summary: We observed a growing prevalence and modestly elevated attack rate for “West Coast” severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.
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The Epsilon variant was estimated to be about 20% more transmissible than co-circulating lineages and to be associated with twofold higher upper-airway virus levels.
“It was estimated to be about 20% more transmissible than co-circulating lineages and to be associated with twofold higher upper-airway virus levels 123,192 .”
From The biological and clinical significance of emerging SARS-CoV-2 variants (2021) · cites this paper as [192]
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Allen, K., Marmor, A., & Pourmarzi, D. (2022) · Communicable Diseases Intelligence · doi:10.33321/cdi.2022.46.44 · Cited by 5 · see citing works
SARS-CoV-2 Mutations and Variants: what do we know so far?
Pecho‐Silva, S., Barboza, J. J., Navarro‐Solsol, A. C., Rodriguez-Morales, A. J., Bonilla‐Aldana, D. K., & Panduro‐Correa, V. (2021) · Microbes Infection and Chemotherapy · doi:10.54034/mic.e1256 · Cited by 6 · see citing works
Methods for sequencing the pandemic: benefits of rapid or high-throughput processing
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SARS-CoV-2 vaccines and their challenges against the variants
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Is the Increased Transmissibility of SARS-CoV-2 Variants Driven by within or Outside-Host Processes?
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Durable tracking anti-SARS-CoV-2 antibodies in cancer patients recovered from COVID-19
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21 Epidemiologic Research in the Setting of Outbreak Response
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Self-citationRole of cellular fatty acids in combating the corona virus
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Self-citationVariant indien : est-il plus contagieux, plus dangereux ?
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Self-citation
- Authors
- Peng, J., Liu, J., Mann, S. A., Mitchell, A. M., Laurie, M. T., Sunshine, S., Pilarowski, G., Ayscue, P., Kistler, A., Vanaerschot, M., Li, L. M., McGeever, A., Chow, E. D., Marquez, C., Nakamura, R., Rubio, L., Chamie, G., Jones, D., Jacobo, J., Rojas, S., Rojas, S., Tulier-Laiwa, V., Black, D., Martinez, J., Naso, J., Schwab, J., Petersen, M., Havlir, D., DeRisi, J., & IDseq Team
- Affiliations
- University of California, San Francisco (US)
- Stanford Medicine (US)
- Chan Zuckerberg Biohub San Francisco (US)
- California Department of Public Health (US)
- United in Health (US)
- University of California, Berkeley (US)
- Chan Zuckerberg Initiative (United States) (US)
- Corresponding author
- DeRisi, Joseph
- ORCID
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-03-31
- Volume
- 74
- Issue
- 1
- Pages
- 32-39
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- PMC
- PMC8083548
- OpenAlex
- W3143386891
- Cited by
- 41
- References
- 44
- Citations by year
- 2024: 1 · 2023: 8 · 2022: 14 · 2021: 18
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Clinical Infectious Diseases (publishedVersion, cc-by-nc-nd)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- California Department of Public Health
- Chan Zuckerberg Initiative
- Stupski Foundation
- National Institutes of Health
- University of California, San Francisco
- National Institute of General Medical Sciences (T32GM007810)
- National Institute of Allergy and Infectious Diseases (F31AI150007, T32AI060530, T32AI060537, UM1AI069496)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- SARS-CoV-2, COVID-19 pandemic, viral transmissibility, reproduction number, viral load, genomic surveillance, community-based testing, San Francisco
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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