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SARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening. We used prospective longitudinal quantitative reverse transcription PCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019–2020 National Basketball Association season. For 46 individuals with acute infections, we inferred the peak viral concentration and the duration of the viral proliferation and clearance phases. According to our mathematical model, we found that viral RNA concentrations peaked an average of 3.3 days (95% credible interval [CI] 2.5, 4.2) after first possible detectability at a cycle threshold value of 22.3 (95% CI 20.5, 23.9). The viral clearance phase lasted longer for symptomatic individuals (10.9 days [95% CI 7.9, 14.4]) than for asymptomatic individuals (7.8 days [95% CI 6.1, 9.7]). A second test within 2 days after an initial positive PCR test substantially improves certainty about a patient’s infection stage. The effective sensitivity of a test intended to identify infectious individuals declines substantially with test turnaround time. These findings indicate that SARS-CoV-2 viral concentrations peak rapidly regardless of symptoms. Sequential tests can help reveal a patient’s progress through infection stages. Frequent, rapid-turnaround testing is needed to effectively screen individuals before they become infectious.

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To test whether acute infection with B.1.1.7 is associated with higher or more sustained nasopharyngeal viral concentrations, we assessed longitudinal PCR tests performed in a cohort of 65 individuals infected with SARS-CoV-2 undergoing daily surveillance testing, including seven infected with B.1.1.7. For individuals infected with B.1.1.7, the mean duration of the proliferation phase was 5.3 days (90% credible interval [2.7, 7.8]), the mean duration of the clearance phase was 8.0 days [6.1, 9.9], and the mean overall duration of infection (proliferation plus clearance) was 13.3 days [10.1, 16.5]. These compare to a mean proliferation phase of 2.0 days [0.7, 3.3], a mean clearance phase of 6.2 days [5.1, 7.1], and a mean duration of infection of 8.2 days [6.5, 9.7] for non-B.1.1.7 virus. The peak viral concentration for B.1.1.7 was 19.0 Ct [15.8, 22.0] compared to 20.2 Ct [19.0, 21.4] for non-B.1.1.7. This converts to 8.5 log10 RNA copies/ml [7.6, 9.4] for B.1.1.7 and 8.2 log10 RNA copies/ml [7.8, 8.5] for non-B.1.1.7. These data offer evidence that SARS-CoV-2 variant B.1.1.7 may cause longer infections with similar peak viral concentration compared to non-B.1.1.7 SARS-CoV-2. This extended duration may contribute to B.1.1.7 SARS-CoV-2's increased transmissibility.

Background The first step in infection by human parainfluenza viruses (HPIVs) is binding to the surface of respiratory epithelial cells via interaction between viral receptor-binding molecules and sialic acid-containing receptors. DAS181, a recombinant sialidase protein containing the catalytic domain of A. viscosus sialidase, removes cell surface sialic acid, and we proposed that it would inhibit HPIV infection. Methods Depletion of sialic acid receptors by DAS181 was evaluated by lectin binding assays. Anti-HPIV activity in cultured cell lines and in human airway epithelium (HAE) was assessed by the reduction in viral genomes and/or plaque forming units (PFU) upon treatment. In vivo efficacy of intranasally administered DAS181 was assessed using a cotton rat model. Results DAS181-mediated desialylation led to anti-HPIV activity in cell lines and HAE. Intranasal DAS181 in cotton rats, a model for human disease, significantly curtailed infection. Conclusions Enzymatic removal of the sialic acid moiety of HPIV receptors inhibits infection with all tested HPIV strains, both in vitro and in cotton rats. Enzyme-mediated removal of sialic acid receptors represents a novel antiviral strategy for HPIV. The results of this study raise the possibility of a broad spectrum antiviral agent for influenza virus and HPIVs.

The analysis of gene-environment interaction (G×E) may hold the key for further understanding the etiology of many complex traits. The current availability of high-volume genetic data, the wide range in types of environmental data that can be measured, and the formation of consortiums of multiple studies provide new opportunities to identify G×E but also new analytical challenges. In this article, we summarize several statistical approaches that can be used to test for G×E in a genome-wide association study. These include traditional models of G×E in a case-control or quantitative trait study as well as alternative approaches that can provide substantially greater power. The latest methods for analyzing G×E with gene sets and with data in a consortium setting are summarized, as are issues that arise due to the complexity of environmental data. We provide some speculation on why detecting G×E in a genome-wide association study has thus far been difficult. We conclude with a description of software programs that can be used to implement most of the methods described in the paper.

SARS-CoV-2 diagnostics that report viral RNA concentrations can be used to determine a patient's stage of infection, but this potential has not yet been realized due to a lack of prospective longitudinal data to calibrate such inferences. Here, we report the viral RNA trajectories for 68 individuals using quantitative PCR testing. On average, symptomatic and asymptomatic individuals reached similar peak viral RNA concentrations (22.2 Ct, 95% credible interval [19.1, 25.1] vs. 22.4 Ct [20.2, 24.5]) within similar amounts of time (2.9 days [0.7, 4.7] vs. 3.0 days [1.3, 4.3]), but acute shedding lasted longer for symptomatic individuals (10.5 days [6.5, 14.0] vs. 6.7 days [3.2, 9.2]). A second test within 2 days after an initial positive PCR result reliably indicated whether viral RNA concentration was increasing, decreasing, or in a low-level persistent phase. Quantitative viral RNA assessment, informed by viral trajectory, can improve algorithms for clinical and public health management.

Background: The combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.Methods: We characterized 1,280 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of age, variant, symptom status, infection history, vaccination status and antibody titer to the founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.Results: Among individuals detected partway through their infection, 51.0% (95% credible interval [CrI]: 48.3-53.6%) remained potentially infectious (Ct<30) five days post detection, with small differences across variants and vaccination status. Only seven viral rebounds (0.7%; N=999) were observed, with rebound defined as 3+ days with Ct<30 following an initial clearance of 3+ days with Ct≥30. High antibody titers against the founder SARS-CoV-2 strain predicted lower peak viral loads and shorter durations of infection. Among Omicron BA.1 infections, boosted individuals had lower pre-booster antibody titers and longer clearance times than non-boosted individuals.Conclusions: SARS-CoV-2 viral kinetics are partly determined by immunity and variant but dominated by individual-level variation. Since booster vaccination protects against infection, longer clearance times for BA.1-infected, boosted individuals may reflect a less effective immune response, more common in older individuals, that increases infection risk and reduces viral RNA clearance rate. The shifting landscape of viral kinetics underscores the need for continued monitoring to optimize isolation policies and to contextualize the health impacts of therapeutics and vaccines.Funding: Supported in part by CDC contract #200-2016-91779, a sponsored research agreement to Yale University from the National Basketball Association contract #21-003529, and the National Basketball Players Association.