State-wide Genomic Epidemiology Investigations of COVID-19 Infections in Healthcare Workers: Insights for Future Pandemic Preparedness (preprint)

BackgroundCOVID-19 has resulted in many infections in healthcare workers (HCWs) globally. We performed state-wide SARS-CoV-2 genomic epidemiological investigations to identify HCW transmission dynamics and provide recommendations to optimise healthcare system preparedness for future outbreaks. MethodsGenome sequencing was attempted on all COVID-19 cases in Victoria, Australia. We combined genomic and epidemiologic data to investigate the source of HCW infections across multiple healthcare facilities (HCFs) in the state. Phylogenetic analysis and fine-scale hierarchical clustering were performed for the entire Victorian dataset including community and healthcare cases. Facilities provided standardised epidemiological data and putative transmission links. FindingsBetween March and October 2020, approximately 1,240 HCW COVID-19 infection cases were identified; 765 are included here. Genomic sequencing was successful for 612 (80%) cases. Thirty-six investigations were undertaken across 12 HCFs. Genomic analysis revealed that multiple introductions of COVID-19 into facilities (31/36) were more common than single introductions (5/36). Major contributors to HCW acquisitions included mobility of staff and patients between wards and facilities, and characteristics and behaviours of individual patients including super-spreading events. Key limitations at the HCF level were identified. InterpretationGenomic epidemiological analyses enhanced understanding of HCW infections, revealing unsuspected clusters and transmission networks. Combined analysis of all HCWs and patients in a HCF should be conducted, supported by high rates of sequencing coverage for all cases in the population. Established systems for integrated genomic epidemiological investigations in healthcare settings will improve HCW safety in future pandemics. FundingThe Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.

Immune responses in COVID-19 respiratory tract and blood reveal mechanisms of disease severity (preprint)

Although the respiratory tract is the primary site of SARS-CoV-2 infection and the ensuing immunopathology, respiratory immune responses are understudied and urgently needed to understand mechanisms underlying COVID-19 disease pathogenesis. We collected paired longitudinal blood and respiratory tract samples (endotracheal aspirate, sputum or pleural fluid) from hospitalized COVID-19 patients and non-COVID-19 controls. Cellular, humoral and cytokine responses were analysed and correlated with clinical data. SARS-CoV-2-specific IgM, IgG and IgA antibodies were detected using ELISA and multiplex assay in both the respiratory tract and blood of COVID-19 patients, although a higher receptor binding domain (RBD)-specific IgM and IgG seroconversion level was found in respiratory specimens. SARS-CoV-2 neutralization activity in respiratory samples was detected only when high levels of RBD-specific antibodies were present. Strikingly, cytokine/chemokine levels and profiles greatly differed between respiratory samples and plasma, indicating that inflammation needs to be assessed in respiratory specimens for the accurate assessment of SARS-CoV-2 immunopathology. Diverse immune cell subsets were detected in respiratory samples, albeit dominated by neutrophils. Importantly, we also showed that dexamethasone and/or remdesivir treatment did not affect humoral responses in blood of COVID-19 patients. Overall, our study unveils stark differences in innate and adaptive immune responses between respiratory samples and blood and provides important insights into effect of drug therapy on immune responses in COVID-19 patients.

Staff to staff transmission as a driver of healthcare worker infections with COVID-19 (preprint)

Objectives: To investigate the COVID-19 infections among staff at our institution and determine the interventions required to prevent subsequent staff infections. Design: Retrospective cohort study Participants and setting: Staff working at a single tertiary referral hospital who returned a positive test result for SARS-CoV-2 between 25 January 2020 and 25 November 2020. Main outcome measures: 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 Austin Health. 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-staff transmission, including 10 healthcare workers (HCWs) linked to a single ward that cared for COVID-19 patients. Investigation of the outbreak identified the staff tearoom 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. Conclusions: 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.

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

Due to the ongoing COVID-19 pandemic and increased pressure on testing resources, understanding the clinical and epidemiological features closely associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is vital at point of care to enable risk stratification. We demonstrate that an internally derived and validated clinical decision rule, COVID-MATCH65, has a high sensitivity (92.6%) and NPV (99.5%) for SARS-CoV-2 and could be used to aid COVID-19 risk-assessment and resource allocation for SARS-CoV-2 diagnostics.

Validation of a Single-step, Single-tube Reverse Transcription-Loop-Mediated Isothermal Amplification Assay for Rapid Detection of SARS-CoV-2 RNA (preprint)

2.IntroductionThe SARS-CoV-2 pandemic of 2020 has resulted in unparalleled requirements for RNA extraction kits and enzymes required for virus detection, leading to global shortages. This has necessitated the exploration of alternative diagnostic options to alleviate supply chain issues. AimTo establish and validate a reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for the detection of SARS-CoV-2 from nasopharyngeal swabs. MethodologyWe used a commercial RT-LAMP mastermix from OptiGene Ltd in combination with a primer set designed to detect the CDC N1 region of the SARS-CoV-2 nucleocapsid (N) gene. A single-tube, single-step fluorescence assay was implemented whereby as little as 1 L of universal transport medium (UTM) directly from a nasopharyngeal swab could be used as template, bypassing the requirement for RNA purification. Amplification and detection could be conducted in any thermocycler capable of holding 65{degrees}C for 30 minutes and measure fluorescence in the FAM channel at one-minute intervals. ResultsAssay evaluation by assessment of 157 clinical specimens previously screened by E-gene RT-qPCR revealed assay sensitivity and specificity of 87% and 100%, respectively. Results were fast, with an average time-to-positive (Tp) for 93 clinical samples of 14 minutes (SD {+/-}7 minutes). Using dilutions of SARS-CoV-2 virus spiked into UTM, we also evaluated assay performance against FDA guidelines for implementation of emergency-use diagnostics and established a limit-of-detection of 54 Tissue Culture Infectious Dose 50 per ml (TCID50 mL-1), with satisfactory assay sensitivity and specificity. A comparison of 20 clinical specimens between four laboratories showed excellent interlaboratory concordance; performing equally well on three different, commonly used thermocyclers, pointing to the robustness of the assay. ConclusionWith a simplified workflow, N1-STOP-LAMP is a powerful, scalable option for specific and rapid detection of SARS-CoV-2 and an additional resource in the diagnostic armamentarium against COVID-19. 3. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.