Favipiravir in early symptomatic COVID-19, a randomised placebo-controlled trial.

Background: Well tolerated antivirals administered early in the course of COVID-19 infection when the viremia is highest could prevent progression to severe disease. Favipiravir inhibits SARS-CoV-2 viral replication in vitro with evidence of clinical benefit in open label trials. Placebo controlled studies of people with early symptomatic COVID-19 with regular assessments of SARS-CoV-2 viral load can determine if it has an antiviral effect and improves clinical outcomes. Methods: People with PCR-confirmed COVID-19 and 5 days or less of symptoms were randomised 1:1 to favipiravir 1800 mg on day 1, then 800 mg twice daily or matched placebo for 14 days. SARS-CoV-2 viral load was quantitated from second daily self-collected nose-throat swabs while receiving study drug. The primary endpoint was time to virological cure defined as 2 successive swabs negative for SARS-CoV-2 by PCR and secondary outcomes were progression of disease severity, symptom resolution and safety. Findings: Between 31 July 2020 and 19 September 2021, 200 people were enrolled (199 in the community, 1 in hospital) with 190 receiving one or more doses of drug (modified intention to treat [mITT] population). There was no difference in time to virological cure (Log-rank p=0.6 comparing Kaplan Meier curves), progression to hospitalisation (14 favipiravir, 9 placebo; p=0.38), time to symptom resolution (cough, fever, sore throat) and there were no deaths. 51 people related an adverse event that was possibly drug related, but these were evenly distributed (n=24 favipiravir, n=27 placebo). Sensitivity analyses where the definition of virological cure was changed to: a single negative PCR, exclude datapoints based on the presence or absence of human DNA in the swab, a SARS-CoV-2 viral load < 300 copies/mL being considered negative all demonstrated no difference between arms. Interpretation: Favipiravir does not improve the time to virological cure or clinical outcomes and shows no evidence of an antiviral effect when treating early symptomatic COVID-19 infection. Funding: The study was supported in part by grants from the Commonwealth Bank Australia, the Lord Mayor's Charitable Foundation, Melbourne Australia and the Orloff Family Charitable Trust, Melbourne, Australia. JHM is supported by the Medical Research Future Fund, AYP, JT are supported by the Australian National Health and Medical Research Council.

SARS-CoV-2 infection results in immune responses in the respiratory tract and peripheral blood that suggest mechanisms of disease severity.

Respiratory tract infection with SARS-CoV-2 results in varying immunopathology underlying COVID-19. We examine cellular, humoral and cytokine responses covering 382 immune components in longitudinal blood and respiratory samples from hospitalized COVID-19 patients. SARS-CoV-2-specific IgM, IgG, IgA are detected in respiratory tract and blood, however, receptor-binding domain (RBD)-specific IgM and IgG seroconversion is enhanced in respiratory specimens. SARS-CoV-2 neutralization activity in respiratory samples correlates with RBD-specific IgM and IgG levels. Cytokines/chemokines vary between respiratory samples and plasma, indicating that inflammation should be assessed in respiratory specimens to understand immunopathology. IFN-α2 and IL-12p70 in endotracheal aspirate and neutralization in sputum negatively correlate with duration of hospital stay. Diverse immune subsets are detected in respiratory samples, dominated by neutrophils. Importantly, dexamethasone treatment does not affect humoral responses in blood of COVID-19 patients. Our study unveils differential immune responses between respiratory samples and blood, and shows how drug therapy affects immune responses during COVID-19.

Defective Severe Acute Respiratory Syndrome Coronavirus 2 Immune Responses in an Immunocompromised Individual With Prolonged Viral Replication.

We describe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific immune responses in a patient with lymphoma and recent programmed death 1 (PD-1) inhibitor therapy with late onset of severe coronavirus disease 2019 disease and prolonged SARS-CoV-2 replication, in comparison to age-matched and immunocompromised controls. High levels of HLA-DR+/CD38+ activation, interleukin 6, and interleukin 18 in the absence of B cells and PD-1 expression was observed. SARS-CoV-2-specific antibody responses were absent and SARS-CoV-2-specific T cells were minimally detected. This case highlights challenges in managing immunocompromised hosts who may fail to mount effective virus-specific immune responses.

Staff to staff transmission as a driver of healthcare worker infections with COVID-19.

BACKGROUND: High rates of healthcare worker (HCW) infections due to COVID-19 have been attributed to several factors, including inadequate personal protective equipment (PPE), exposure to a high density of patients with COVID-19, and poor building ventilation. We investigated an increase in the number of staff COVID-19 infections at our hospital to determine the factors contributing to infection and to implement the interventions required to prevent subsequent infections. METHODS: We conducted a single-centre retrospective cohort study of staff working at a tertiary referral hospital who tested positive for SARS-CoV-2 between 25 January 2020 and 25 November 2020. The primary outcome was the source of COVID-19 infection. RESULTS: Of 45 staff who returned a positive test result for SARS-CoV-2, 19 were determined to be acquired at our hospital. Fifteen (15/19; 79% [95% CI: 54-94%]) of these were identified through contact tracing and testing following exposures to other infected staff and were presumed to be staff-to-staff transmission, including an outbreak in 10 healthcare workers (HCWs) linked to a single ward that cared for COVID-19 patients. The staff tearoom was identified as the likely location for transmission, with subsequent reduction in HCW infections and resolution of the outbreak following implementation of enhanced control measures in tearoom facilities. No HCW contacts (0/204; 0% [95% CI: 0-2%]) developed COVID-19 infection following exposure to unrecognised patients with COVID-19. CONCLUSION: Unrecognised infections among staff may be a significant driver of HCW infections in healthcare settings. Control measures should be implemented to prevent acquisition from other staff as well as patient-staff transmission.

Clinical evaluation of four commercial immunoassays for the detection of antibodies against established SARS-CoV-2 infection.

A comparison of the clinical performance of the Elecsys Anti-SARS-CoV-2, Liaison SARS-CoV-2 S1/S2 IgG, Access SARS-CoV-2 IgG and Vitros Immunodiagnostic Products Anti-SARS-CoV-2 IgG immunoassays for the diagnosis of COVID-19 infection was performed. Patient sera were collected at least 6 weeks following onset of COVID-19 infection symptoms. Negative control specimens were stored specimens from those without COVID-19, collected in April-May 2019. Sensitivity and specificity with 95% confidence intervals (CI) were calculated. Linear regression was used to examine the relationship between the magnitude of serological response and clinical characteristics. There were 80 patients from whom 86 sera specimens were collected; six patients had duplicate specimens. There were 95 negative control specimens from 95 patients. The clinical sensitivity of the Elecsys assay was 98.84% (95% CI 93.69-99.97), specificity was 100% (95% CI 96.19-100.00); the Liaison assay clinical sensitivity was 96.51% (95% CI 90.14-99.27), specificity was 97.89% (95% CI 92.60-99.74); the Access assay clinical sensitivity was 84.88% (95% CI 75.54-91.70), specificity was 98.95% (95% CI 94.27-99.97); and the Vitros assay clinical sensitivity was 97.67% (95% CI 91.85-99.72), specificity was 100% (95% CI 96.15-100.00). A requirement for hospitalisation for COVID-19 infection was associated with a larger Vitros, Liaison and Access IgG response whilst fever was associated with a larger Elecsys response. All assays evaluated with the exception of the Access assay demonstrated similar performance. The Elecsys assay demonstrated the highest sensitivity and specificity.

COVID-MATCH65-A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2.

OBJECTIVES: We report on the key clinical predictors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and present a clinical decision rule that can risk stratify patients for COVID-19. DESIGN, PARTICIPANTS AND SETTING: A prospective cohort of patients assessed for COVID-19 at a screening clinic in Melbourne, Australia. The primary outcome was a positive COVID-19 test from nasopharyngeal swab. A backwards stepwise logistic regression was used to derive a model of clinical variables predictive of a positive COVID-19 test. Internal validation of the final model was performed using bootstrapped samples and the model scoring derived from the coefficients, with modelling performed for increasing prevalence. RESULTS: Of 4226 patients with suspected COVID-19 who were assessed, 2976 patients underwent SARS-CoV-2 testing (n = 108 SARS-CoV-2 positive) and were used to determine factors associated with a positive COVID-19 test. The 7 features associated with a positive COVID-19 test on multivariable analysis were: COVID-19 patient exposure or international travel, Myalgia/malaise, Anosmia or ageusia, Temperature, Coryza/sore throat, Hypoxia-oxygen saturation < 97%, 65 years or older-summarized in the mnemonic COVID-MATCH65. Internal validation showed an AUC of 0.836. A cut-off of ≥ 1.5 points was associated with a 92.6% sensitivity and 99.5% negative predictive value (NPV) for COVID-19. CONCLUSIONS: From the largest prospective outpatient cohort of suspected COVID-19 we define the clinical factors predictive of a positive SARS-CoV-2 test. The subsequent clinical decision rule, COVID-MATCH65, has a high sensitivity and NPV for SARS-CoV-2 and can be employed in the pandemic, adjusted for disease prevalence, to aid COVID-19 risk-assessment and vital testing resource allocation.