Predictors of SARS-CoV-2 Infection in Youth at a Large, Urban Healthcare Center in California, March–September 2020

Objective: To understand which social, epidemiologic, and clinical risk factors are associated with SARS-CoV-2 infection in youth accessing care in a large, urban academic institution. Methods: We conducted a prospective cohort study with case-control analyses in youth who received testing for SARS-CoV-2 at our academic institution in Los Angeles during the first wave of the COVID-19 pandemic (March-September 2020). Results: A total of 27,976 SARS-CoV-2 assays among 11,922 youth aged 0-24 years were performed, including 475 youth with positive SARS-CoV-2 results. Positivity rate was higher among older, African American, and Hispanic/Latinx youth. Cases were more likely to be from non-English-speaking households and have safety-net insurance. Zip codes with higher proportion of Hispanic/Latinx and residents living under the poverty line were associated with increased SARS-CoV-2 cases. Youth were more likely to have positive results if tested for exposure (OR 21.5, 95% CI 14.6-32.1) or recent travel (OR 1.5, 95% CI 1.0-2.3). Students were less likely to have positive results than essential worker youth (OR 0.5, 95% CI 0.3-0.8). Patterns of symptom presentation varied significantly by age group; number of symptoms correlated significantly with age in SARS-CoV-2 cases (r = 0.030, p < 0.001). SARS-CoV-2 viral load did not vary by symptom severity, but asymptomatic youth had lower median viral load than those with symptoms (21.5 vs. 26.7, p = 0.009). Conclusions: Socioeconomic factors are important drivers of SARS-CoV-2 infection in youth. Presence of symptoms, exposure, and travel can be used to drive testing in older youth. Policies for school reopening and infection prevention should be tailored differently for elementary schools and universities

Clinical and epidemiological characteristics of SARS-CoV-2 Infection in Los Angeles County youth during the first year of the pandemic

ObjectivesThe aim of this study was to characterize SARS-CoV-2 infection patterns in Los Angeles (LA) County youth followed at our institution during the first pandemic year.DesignA prospective cohort of patients aged < 25 years who tested positive for SARS-CoV-2 using reverse-transcriptase polymerase chain reaction (RT-PCR) assays between March 13, 2020, and March 31, 2021, was evaluated at a large LA County health network. Demographics, age distribution, and disease severity were analyzed.ResultsThere were 28,088 youth aged < 25 years tested for SARS-CoV-2 using RT-PCR, with 1849 positive results identified (7%). Among the positive results, 475 of 11,922 (4%) were identified at the pandemic onset (March-September 2020) (Cohort 1) and 1374 of 16,166 (9%) between October 2020 and March 2021 (Cohort 2), P < 0.001. When disease severity was compared across cohorts, Cohort 2 had a greater proportion of asymptomatic and mild/moderate disease categories than Cohort 1 (98% vs 80%, respectively); conversely, Cohort 1 had a near-10-fold higher proportion of severe disease than Cohort 2 (17% vs 1.8%). Cohort 2 comprised younger patients with a mean age of 13.7 years vs 17.3 years in Cohort 1. Older age was associated with a higher percentage of infection, with 63% of all confirmed cases found in participants aged 19 to 25 years in Cohort 1, compared with 38% of confirmed cases in Cohort 2. Age increase was also associated with greater disease severity by linear regression modeling (P< 0.001).ConclusionCoronavirus disease 2019 (COVID-19) disease severity in youth decreased over time in LA County during the first pandemic year, likely a reflection of changing demographics, with younger children infected. A higher infection rate in youth did not lead to higher disease severity over time

Risk of COVID-19 after natural infection or vaccinationResearch in context

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health

Risk of COVID-19 after natural infection or vaccinationResearch in context

Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health

Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig

The type and genomic context of cancer mutations depend on their causes. These causes have been characterized using signatures that represent mutation types that co-occur in the same tumours. However, it remains unclear how mutation processes change during cancer evolution due to the lack of reliable methods to reconstruct evolutionary trajectories of mutational signature activity. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we present TrackSig, a new method that reconstructs these trajectories using optimal, joint segmentation and deconvolution of mutation type and allele frequencies from a single tumour sample. In simulations, we find TrackSig has a 3-5% activity reconstruction error, and 12% false detection rate. It outperforms an aggressive baseline in situations with branching evolution, CNA gain, and neutral mutations. Applied to data from 2658 tumours and 38 cancer types, TrackSig permits pan-cancer insight into evolutionary changes in mutational processes