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.

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.

SARS-CoV-2 vaccine boosters: The time to act is now.

We have a new and unprecedented opportunity to mitigate the suffering, death and inequities of COVID-19 in the United States with vaccine boosters-if we deploy them effectively, rapidly, and widely with simplified messaging to all eligible adults.

Community Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 Disproportionately Affects the Latinx Population During Shelter-in-Place in San Francisco.

BACKGROUND: There is an urgent need to understand the dynamics and risk factors driving ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission during shelter-in-place mandates. METHODS: We offered SARS-CoV-2 reverse-transcription polymerase chain reaction (PCR) and antibody (Abbott ARCHITECT IgG) testing, regardless of symptoms, to all residents (aged ≥4 years) and workers in a San Francisco census tract (population: 5174) at outdoor, community-mobilized events over 4 days. We estimated SARS-CoV-2 point prevalence (PCR positive) and cumulative incidence (antibody or PCR positive) in the census tract and evaluated risk factors for recent (PCR positive/antibody negative) vs prior infection (antibody positive/PCR negative). SARS-CoV-2 genome recovery and phylogenetics were used to measure viral strain diversity, establish viral lineages present, and estimate number of introductions. RESULTS: We tested 3953 persons (40% Latinx; 41% White; 9% Asian/Pacific Islander; and 2% Black). Overall, 2.1% (83/3871) tested PCR positive: 95% were Latinx and 52% were asymptomatic when tested; 1.7% of census tract residents and 6.0% of workers (non-census tract residents) were PCR positive. Among 2598 tract residents, estimated point prevalence of PCR positives was 2.3% (95% confidence interval [CI], 1.2%-3.8%): 3.9% (95% CI, 2.0%-6.4%) among Latinx persons vs 0.2% (95% CI, .0-.4%) among non-Latinx persons. Estimated cumulative incidence among residents was 6.1% (95% CI, 4.0%-8.6%). Prior infections were 67% Latinx, 16% White, and 17% other ethnicities. Among recent infections, 96% were Latinx. Risk factors for recent infection were Latinx ethnicity, inability to shelter in place and maintain income, frontline service work, unemployment, and household income <$50 000/year. Five SARS-CoV-2 phylogenetic lineages were detected. CONCLUSIONS: SARS-CoV-2 infections from diverse lineages continued circulating among low-income, Latinx persons unable to work from home and maintain income during San Francisco's shelter-in-place ordinance.

Outcomes Associated With Social Distancing Policies in St Louis, Missouri, During the Early Phase of the COVID-19 Pandemic.

Importance: In the absence of a national strategy in response to the COVID-19 pandemic, many public health decisions fell to local elected officials and agencies. Outcomes of such policies depend on a complex combination of local epidemic conditions and demographic features as well as the intensity and timing of such policies and are therefore unclear. Objective: To use a decision analytical model of the COVID-19 epidemic to investigate potential outcomes if actual policies enacted in March 2020 (during the first wave of the epidemic) in the St Louis region of Missouri had been delayed. Design, Setting, and Participants: A previously developed, publicly available, open-source modeling platform (Local Epidemic Modeling for Management & Action, version 2.1) designed to enable localized COVID-19 epidemic projections was used. The compartmental epidemic model is programmed in R and Stan, uses bayesian inference, and accepts user-supplied demographic, epidemiologic, and policy inputs. Hospital census data for 1.3 million people from St Louis City and County from March 14, 2020, through July 15, 2020, were used to calibrate the model. Exposures: Hypothetical delays in actual social distancing policies (which began on March 13, 2020) by 1, 2, or 4 weeks. Sensitivity analyses were conducted that explored plausible spontaneous behavior change in the absence of social distancing policies. Main Outcomes and Measures: Hospitalizations and deaths. Results: A model of 1.3 million residents of the greater St Louis, Missouri, area found an initial reproductive number (indicating transmissibility of an infectious agent) of 3.9 (95% credible interval [CrI], 3.1-4.5) in the St Louis region before March 15, 2020, which fell to 0.93 (95% CrI, 0.88-0.98) after social distancing policies were implemented between March 15 and March 21, 2020. By June 15, a 1-week delay in policies would have increased cumulative hospitalizations from an observed actual number of 2246 hospitalizations to 8005 hospitalizations (75% CrI: 3973-15 236 hospitalizations) and increased deaths from an observed actual number of 482 deaths to a projected 1304 deaths (75% CrI, 656-2428 deaths). By June 15, a 2-week delay would have yielded 3292 deaths (75% CrI, 2104-4905 deaths)-an additional 2810 deaths or a 583% increase beyond what was actually observed. Sensitivity analyses incorporating a range of spontaneous behavior changes did not avert severe epidemic projections. Conclusions and Relevance: The results of this decision analytical model study suggest that, in the St Louis region, timely social distancing policies were associated with improved population health outcomes, and small delays may likely have led to a COVID-19 epidemic similar to the most heavily affected areas in the US. These findings indicate that an open-source modeling platform designed to accept user-supplied local and regional data may provide projections tailored to, and more relevant for, local settings.