ABSTRACT
BackgroundEpidemic waves of COVID-19 strained hospital resources. We describe temporal trends in mortality risk and length of stay in intensive cares units (ICUs) among COVID-19 patients hospitalized through the first three epidemic waves in Canada. MethodsWe used population-based provincial hospitalization data from Ontario and Quebec to examine mortality risk and lengths of ICU stay. For each province, adjusted estimates were obtained using marginal standardization of logistic regression models, adjusting for patient-level characteristics and hospital-level determinants. ResultsUsing all hospitalizations from Ontario (N=26,541) and Quebec (N=23,857), we found that unadjusted in-hospital mortality risks peaked at 31% in the first wave and was lowest at the end of the third wave at 6-7%. This general trend remained after controlling for confounders. The odds of in-hospital mortality in the highest hospital occupancy quintile was 1.2 (95%CI: 1.0-1.4; Ontario) and 1.6 (95%CI: 1.3-1.9; Quebec) times that of the lowest quintile. Variants of concerns were associated with an increased in-hospital mortality. Length of ICU stay decreased over time from a mean of 16 days (SD=18) to 15 days (SD=15) in the third wave but were consistently higher in Ontario than Quebec by 3-6 days. ConclusionIn-hospital mortality risks and lengths of ICU stay declined over time in both provinces, despite changing patient demographics, suggesting that new therapeutics and treatment, as well as improved clinical protocols, could have contributed to this reduction. Continuous population-based monitoring of patient outcomes in an evolving epidemic is necessary for health system preparedness and response.
Subject(s)
COVID-19ABSTRACT
The role of inhaled corticosteroids for outpatient COVID-19 is evolving. We meta-analyzed reported clinical trials and estimated probability of any effect and number needed to treat of 50 or 20 for symptom resolution by day 14 [100%, 99.8%, 93.1%] and hospitalization [89.3%, 72.9%, 26.7%] respectively.
Subject(s)
COVID-19ABSTRACT
Background: There are currently no effective treatments for outpatients with coronavirus disease. 2019 (COVID-19). Interferon-lambda-1 is a Type III interferon involved in the innate antiviral response with activity against respiratory pathogens.Methods: In this double-blind, placebo-controlled trial, outpatients with laboratory-confirmed COVID-19 were randomized to a single subcutaneous injection of peginterferon-lambda 180μg or placebo within 7 days of symptom onset or first positive swab if asymptomatic. The primary endpoint was proportion negative for SARS-CoV-2 RNA on Day 7 post-injection.Results: There were 30 patients per arm, with median baseline SARS-CoV-2 viral load of 6.71 (IQR 1.3-8.0) log copies/mL. The decline in SARS-CoV-2 RNA was greater in those treated with peginterferon-lambda than placebo (p=0.04). On Day 7, 24 participants (80%) in the peginterferon-lambda group had an undetectable viral load compared to 19 (63%) in the placebo arm (p=0.15). After controlling for baseline viral load, peginterferon-lambda treatment resulted in a 4.12-fold (95CI 1.15-16.7, p=0.029) higher likelihood of viral clearance by Day 7. Of those with baseline viral load above 10E6 copies/mL, 15/19 (79%) in the peginterferon-lambda group were undetectable on Day 7 compared to 6/16 (38%) in the placebo group (p=0.012). Adverse events were similar between groups with only mild reversible transaminase elevations more frequently observed in the peginterferon-lambda group.Conclusion: Peginterferon-lambda accelerated viral decline in outpatients with COVID-19 resulting in a greater proportion with viral clearance by Day 7, particularly in those with high baseline viral load. Peginterferon-lambda may have potential to prevent clinical deterioration and shorten duration of viral shedding.Trial Registration: NCT04354259Funding Statement: This study was supported by the Toronto COVID-19 Action Initiative, University of Toronto and the Ontario First COVID-19 Rapid Research Fund. Medication was supplied by Eiger BioPharma. Declaration of Interests: JJF reports research support unrelated to this work from Eiger BioPharmaceuticals. BC has received research support unrelated to this work from Nubiyota LLC and Sanofi. IC and CH are employees of Eiger BioPharmaceuticals. JSG is a board member and founder of Eiger BioPharmaceuticals, Inc., in which he has an equity interest, and is an inventor on a patent application for the use of interferon lambda to treat coronavirus infections. All other authors have nothing to declare. Ethics Approval Statement: The Research Ethics Boards of all participating institutions approved the study, which was conducted under a Clinical Trial Application approved by Health Canada.
Subject(s)
COVID-19 , Coronavirus InfectionsABSTRACT
Background: Post-exposure prophylaxis (PEP) is a well-established strategy for the prevention of infectious diseases, in which recently exposed people take a short course of medication to prevent infection. The primary objective of the COVID-19 Ring-based Prevention Trial with lopinavir/ritonavir (CORIPREV-LR) is to evaluate the efficacy of a 14-day course of oral lopinavir/ritonavir as PEP against COVID-19 among individuals with a high-risk exposure to a confirmed case. Methods: : This is an open-label, multicenter, 1:1 cluster-randomized trial of LPV/r versus no intervention, using an adaptive approach to sample size calculation. Participants will be individuals aged >6 months with a high-risk exposure to a confirmed COVID-19 case within the past 7 days. A combination of remote and in-person study visits at days 1, 7, 14, 35 and 90 include comprehensive epidemiological, clinical, microbiologic and serologic sampling. The primary outcome is microbiologically confirmed COVID-19 infection within 14 days after exposure, defined as a positive respiratory tract specimen for SARS-CoV-2 by polymerase chain reaction. Secondary outcomes include safety, symptomatic COVID-19, seropositivity, hospitalization, respiratory failure requiring ventilator support, mortality, psychological impact, and health-related quality of life. Additional analyses will examine the impact of LPV/r on these outcomes in the subset of participants who test positive for SARS-CoV-2 at baseline. To detect a relative risk reduction of 40% with 80% power at α=0.05, assuming p 0 =15%, 5 contacts per case and intra-class correlation coefficient (ICC)=0.05, we require 110 clusters per arm, or 220 clusters overall and approximately 1220 enrollees after accounting for 10% loss-to-follow-up. We will modify the sample size target after 60 clusters, based on preliminary estimates of p0, ICC and cluster size and consider switching to an alternative drug after interim analyses and as new data emerges. The primary analysis will be a generalized linear mixed model with logit link to estimate the effect of LPV/r on the probability of infection. Discussion: Harnessing safe, existing drugs such as LPV/r as PEP could provide an important tool for control of the COVID-19 pandemic. Novel aspects of our design include the ring-based prevention approach, and the incorporation of remote strategies for conducting study visits and biospecimen collection. Trial registration: This trial was registered at www.clinicaltrials.gov (NCT04321174) on March 25, 2020. https://clinicaltrials.gov/ct2/show/NCT04321174
Subject(s)
COVID-19 , Respiratory Insufficiency , Communicable DiseasesABSTRACT
Background: There are currently no effective treatments for outpatients with coronavirus disease 2019 (COVID-19). Interferon-lambda-1 is a Type III interferon involved in the innate antiviral response with activity against respiratory pathogens. Methods: In this double-blind, placebo-controlled trial, outpatients with laboratory-confirmed COVID-19 were randomized to a single subcutaneous injection of peginterferon-lambda 180mcg or placebo within 7 days of symptom onset or first positive swab if asymptomatic. The primary endpoint was proportion negative for SARS-CoV-2 RNA on Day 7 post-injection. Findings: There were 30 patients per arm, with median baseline SARS-CoV-2 viral load of 6.71 (IQR 1.3-8.0) log copies/mL. The decline in SARS-CoV-2 RNA was greater in those treated with peginterferon-lambda than placebo (p=0.04). On Day 7, 24 participants (80%) in the peginterferon-lambda group had an undetectable viral load compared to 19 (63%) in the placebo arm (p=0.15). After controlling for baseline viral load, peginterferon lambda treatment resulted in a 4.12-fold (95CI 1.15-16.7, p=0.029) higher likelihood of viral clearance by Day 7. Of those with baseline viral load above 10E6 copies/mL, 15/19 (79%) in the peginterferon-lambda group were undetectable on Day 7 compared to 6/16 (38%) in the placebo group (p=0.012). Adverse events were similar between groups with only mild reversible transaminase elevations more frequently observed in the peginterferon-lambda group. Interpretation: Peginterferon-lambda accelerated viral decline in outpatients with COVID-19 resulting in a greater proportion with viral clearance by Day 7, particularly in those with high baseline viral load. Peginterferon-lambda may have potential to prevent clinical deterioration and shorten duration of viral shedding. (NCT04354259)
Subject(s)
COVID-19ABSTRACT
Importance: Optimizing the public health response to reduce coronavirus disease 2019 (COVID-19) burden necessitates characterizing population-level heterogeneity of COVID-19 risks. However, heterogeneity in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing may introduce biased estimates depending on analytic design. Objective: Characterizing individual, environmental, and social determinants of SARS-CoV-2 testing and COVID-19 diagnosis. Design: We conducted cross-sectional analyses among 14.7 million people comparing individual, environmental, and social determinants among individuals who were tested versus not yet tested. Among those diagnosed, we used three analytic designs to compare predictors of: 1) individuals testing positive versus negative; 2) symptomatic individuals testing positive versus negative; and 3) individuals testing positive versus individuals not testing positive (i.e. testing negative or not being tested). Analyses included tests conducted between March 1 and June 20, 2020. Setting: Ontario, Canada. Participants: All individuals with [≥]1 healthcare system contact since March 2012, excluding individuals deceased before, or born after, March 1, 2020, or residing in a long-term care facility. Exposures: Individual-level characteristics (age, sex, underlying health conditions, prior healthcare use), area-based environmental (air pollution) exposures, and area-based social determinants of health (income, education, housing, marital status, race/ethnicity, and recent immigration). Main Outcomes and Measures: Odds of SARS-CoV-2 test, and of COVID-19 diagnosis. Results: Of a total of 14,695,579 individuals, 758,691 had been tested, of whom 25,030 (3.3%) tested positive. The further the odds of testing from the null, the more variability observed in the odds of diagnosis across analytic design, particularly among individual factors. There was less variability in testing by social determinants across analytic design. Residing in areas with highest household density (adjusted odds ratio: 2.08; 95%CI: 1.95-1.21), lowest educational attainment (adjusted odds ratio: 1.52; 95%CI: 1.44-1.60), and highest proportion of recent immigrants (adjusted odds ratio: 1.12; 95%CI: 1.07-1.16) were consistently related to increased odds of COVID-19 across analytic designs. Conclusions and Relevance: Where testing is limited, risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding and systemic racism.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
Currently, more than 33 million peoples have been infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more than a million people died from coronavirus disease 2019 (COVID-19), a disease caused by the virus. There have been multiple reports of autoimmune and inflammatory diseases following SARS-CoV-2 infections. There are several suggested mechanisms involved in the development of autoimmune diseases, including cross-reactivity (molecular mimicry). A typical workflow for discovering cross-reactive epitopes (mimotopes) starts with a sequence similarity search between protein sequences of human and a pathogen. However, sequence similarity information alone is not enough to predict cross-reactivity between proteins since proteins can share highly similar conformational epitopes whose amino acid residues are situated far apart in the linear protein sequences. Therefore, we used a hidden Markov model-based tool to identify distant viral homologs of human proteins. Also, we utilized experimentally determined and modeled protein structures of SARS-CoV-2 and human proteins to find homologous protein structures between them. Next, we predicted binding affinity (IC50) of potentially cross-reactive T-cell epitopes to 34 MHC allelic variants that have been associated with autoimmune diseases using multiple prediction algorithms. Overall, from 8,138 SARS-CoV-2 genomes, we identified 3,238 potentially cross-reactive B-cell epitopes covering six human proteins and 1,224 potentially cross-reactive T-cell epitopes covering 285 human proteins. To visualize the predicted cross-reactive T-cell and B-cell epitopes, we developed a web-based application "Molecular Mimicry Map (3M) of SARS-CoV-2" (available at https://ahs2202.github.io/3M/). The web application enables researchers to explore potential cross-reactive SARS-CoV-2 epitopes alongside custom peptide vaccines, allowing researchers to identify potentially suboptimal peptide vaccine candidates or less ideal part of a whole virus vaccine to design a safer vaccine for people with genetic and environmental predispositions to autoimmune diseases. Together, the computational resources and the interactive web application provide a foundation for the investigation of molecular mimicry in the pathogenesis of autoimmune disease following COVID-19.
Subject(s)
COVID-19 , Autoimmune Diseases , Severe Acute Respiratory SyndromeABSTRACT
Coronaviruses have caused three major outbreaks of infectious disease since the beginning of 21st century. Broad-spectrum strategies that can be utilized in both current and future coronavirus outbreaks and mutation-tolerant are sought after. Here we report a monoclonal antibody 3E8 targeting human angiotensin-converting enzyme 2 (ACE2) neutralized pseudo-typed coronaviruse SARS-CoV-2, SARS-CoV-2-D614G, SARS-CoV and HCoV-NL63, without affecting physiological activities of ACE2 or causing toxicity in mouse model. 3E8 also blocked live SARS-CoV-2 infection in vitro and in a mouse model of COVID-19. Cryo-EM studies revealed the binding site of 3E8 on ACE2 and identified Histone 34 of ACE2 as a critical site of anti-viral epitope. Overall, our work has provided a potential pan coronavirus management strategy and disclosed a pan anti-coronavirus epitope on human ACE2 for the first time.
Subject(s)
COVID-19 , Drug-Related Side Effects and Adverse Reactions , Communicable DiseasesABSTRACT
Background: A hospital-level pandemic response involves anticipating local surge in healthcare needs. Methods: We developed a mechanistic transmission model to simulate a range of scenarios of COVID-19 spread in the Greater Toronto Area. We estimated healthcare needs against 2019 daily admissions using healthcare administrative data, and applied outputs to hospital-specific data on catchment, capacity, and baseline non-COVID admissions to estimate potential surge by day 90 at two hospitals (St. Michaels Hospital [SMH] and St. Josephs Health Centre [SJHC]). We examined fast/large, default, and slow/small epidemics, wherein the default scenario (R0 2.4) resembled the early trajectory in the GTA. Results: Without further interventions, even a slow/small epidemic exceeded the citys daily ICU capacity for patients without COVID-19. In a pessimistic default scenario, for SMH and SJHC to remain below their non-ICU bed capacity, they would need to reduce non-COVID inpatient care by 70% and 58% respectively. SMH would need to create 86 new ICU beds, while SJHC would need to reduce its ICU beds for non-COVID care by 72%. Uncertainty in local epidemiological features was more influential than uncertainty in clinical severity. If physical distancing reduces contacts by 20%, maximizing the diagnostic capacity or syndromic diagnoses at the community-level could avoid a surge at each hospital. Interpretation: As distribution of the citys surge varies across hospitals over time, efforts are needed to plan and redistribute ICU care to where demand is expected. Hospital-level surge is based on community-level transmission, with community-level strategies key to mitigating each hospitals surge. Keywords: COVID-19, pandemic preparedness, mathematical model, transmission model