ABSTRACT
In Canada, lower income households and essential workers and were disproportionately at risk of SARS-CoV-2. Early in the pandemic, stay-at-home restriction policies were used to limit virus transmission. There remains an evidence gap in how changes in mobility, in response to the policies, varied across socioeconomic measures in Canada. The study objective was to describe the variability in mobility change to two restrictions, by neighborhood-level income and by proportion essential workers across five regions in Ontario, Canada. The first restriction was implemented on March 17, 2020 in all five regions; and the second restriction was implemented in November 23, 2020 in two of the regions. Using cell-phone mobility data aggregated to the census tract, we compared the average mobility (% of devices that travelled outside their "primary location") three weeks before and after each restriction. We defined the adjusted mobility change via pre-restriction mobility subtracted from post-restriction, adjusted for 2019 levels. We used difference-in-differences analysis to quantify effect modification of the second restrictions effect by socioeconomic measures. With the first restriction, crude mobility fell from 77.7% to 41.6% across the five regions. The adjusted mobility change to the first restriction was largest in the highest-income neighborhoods (-43.3% versus -38.4%) and in neighborhoods with the fewest essential workers (-44.5% versus -37.6%). The overall adjusted mobility change to the second restriction was small: -0.96% (95% confidence intervals, -1.53 to -0.38%). However, there was evidence of effect modification by socioeconomic measures (less pronounced decrease in lower-income neighborhoods and more essential workers). The findings suggest a temporal saturation effect of restrictions over subsequent waves, and a saturation effect by income and occupation, leading to prevention gaps across populations by socioeconomic measures. Findings highlight the need for tailored approaches at the intersections of income and occupation when addressing epidemics of novel and resurging respiratory pathogens.
Subject(s)
COVID-19ABSTRACT
BackgroundComplete reporting of seroepidemiologic studies (e.g. sampling and measurement methods, immunoassay characteristics) are critical to their interpretation, comparison, and utility in evidence synthesis. The Reporting of Seroepidemiologic studies--SARS_JCoV_J2 (ROSES-S) guideline is a reporting checklist that aims to improve the quality and transparency of reporting in SARS-CoV-2 seroepidemiological studies. While the synthesis of seroepidemiologic studies played a crucial role in public health decision-making during the COVID-19 pandemic, adherence of SARS-CoV-2 seroepidemiologic studies to the ROSES-S guideline has not yet been evaluated. ObjectivesTo evaluate the completeness of SARS-CoV-2 seroepidemiologic study reporting over the first two years of the COVID-19 pandemic by assessing adherence to the ROSES-S reporting guideline, determine whether publication of the ROSES-S guideline was associated with changes in reporting completeness, and identify study characteristics associated with reporting completeness. MethodsA stratified random sample of SARS-CoV-2 seroepidemiologic studies from the SeroTracker living systematic review database was evaluated for adherence to the ROSES-S guideline. We categorized study adherence to each reporting item in the guideline as "reported", "not reported", or "not applicable". For each reporting item we calculated the percentage of studies that were adherent. We also calculated the median and interquartile range (IQR) adherence across all items and by item domain. Piecewise and multivariable beta regression analyses were used to determine whether publication date of the ROSES-S guideline was associated with changes in the overall adherence scores and to identify study characteristics associated with overall adherence scores. Results199 studies were included and analyzed. The median adherence to reporting items was 48.1% (IQR 40.0%-55.2%) per study. Adherence to reporting items ranged from 8.8% to 72.7% per study. The laboratory methods domain (e.g. description of testing algorithm) had the lowest median adherence (33.3% [IQR 25.0%-41.7%%]), while the discussion domain had the highest median adherence (75.0% [IQR 50.0%-100.0%])). There were no significant changes in reporting adherence to ROSES-S before and after guideline publication. Article publication source (p<0.001), study risk of bias (p=0.001), and sampling method (p=0.004) were significantly associated with adherence to the ROSES-S guideline. ConclusionsThe completeness of reporting in SARS-CoV-2 seroepidemiologic studies was suboptimal, especially in laboratory methods, and was associated with key study characteristics. Publication of the ROSES-S guideline was not associated with changes in reporting practices. Given that reporting is necessary to improve the standardization and utility of seroprevalence data in evidence synthesis, authors should improve adherence to the ROSES-S guideline with support from stakeholders.
Subject(s)
COVID-19ABSTRACT
Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this technology has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021-April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p[≤]0.01). Real-time contact tracing data was used to confirm an association between wastewater SARS-CoV-2 burden and clinically confirmed cases proving the potential of WBS as a tool for disease monitoring across worksites. Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.
Subject(s)
COVID-19ABSTRACT
Wastewater-based surveillance (WBS) is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19 impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with local workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.3 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5% (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4,524 unrelated absences COVID-19 cases were recorded. Employee absences significantly increased as wastewater signal increased through pandemic waves. Strong correlations between COVID-19-confirmed absences and wastewater SARS-CoV-2 signals (N1 gene: r=0.824, p<0.0001 and N2 gene: r=0.826, p<0.0001) were observed. Linear regression with adjusted R2-value demonstrated a robust association (adjusted R2=0.783), when adjusted by 7 days, indicating wastewater provides a one-week leading signal. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P<0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.
Subject(s)
COVID-19 , Skull Base NeoplasmsABSTRACT
Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.3 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December, 2020) and the third-wave of the COVID-19 pandemic (mid-April to May, 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06 percent (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 and N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgarys three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.
Subject(s)
COVID-19ABSTRACT
Background: Many studies have examined the effectiveness of non-pharmaceutical interventions (NPIs) on SARS-CoV-2 transmission worldwide. However, less attention has been devoted to understanding the limits of NPIs across the course of the pandemic and along a continuum of their stringency. In this study, we explore the relationship between the growth of SARS-CoV-2 cases and a stringency index across Canada prior to accelerated vaccine roll-out.Methods: We conducted an ecological time-series study of daily SARS-CoV-2 case growth in Canada from February 2020 to February 2021. Our outcome was a back-projected version of the daily growth ratio in a stringency period (i.e., a 10-point range of the stringency index) relative to the last day of the previous period. We examined the trends in case growth using a linear mixed effects model accounting for stringency period, province, and mobility in public domains.Results: Case growth declined, rapidly, by 37–50% and began plateauing within the first two weeks of the first wave, irrespective of the starting values of the stringency index. Across individual stringency periods, there was a lag of 11·3 days, on average, to observe the largest cumulative decline in relative growth. The largest decreasing trends from our mixed effects model occurred over the first stringency period in each province, at a mean index value of 25·2 out of 100.Conclusions: There was a negative correlation between NPI stringency and growth of SARS-CoV-2 that attenuated throughout the course of Canada’s epidemic. We suggest that individual- and network-level risk factors need to guide the use of NPIs in future epidemics.
Subject(s)
Intestinal PolyposisABSTRACT
Background: There is a growing recognition that strategies to reduce SARS-CoV-2 transmission should be responsive to local transmission dynamics. Studies have revealed inequalities along social determinants of health, but little investigation was conducted surrounding geographic concentration within cities. We quantified social determinants of geographic concentration of COVID-19 cases across sixteen census metropolitan areas (CMA) in four Canadian provinces. Methods: We used surveillance data on confirmed COVID-19 cases at the level of dissemination area. Gini (co-Gini) coefficients were calculated by CMA based on the proportion of the population in ranks of diagnosed cases and each social determinant using census data (income, education, visible minority, recent immigration, suitable housing, and essential workers) and the corresponding share of cases. Heterogeneity was visualized using Lorenz (concentration) curves. Results: Geographic concentration was observed in all CMAs (half of the cumulative cases were concentrated among 21-35% of each city's population): with the greatest geographic heterogeneity in Ontario CMAs (Gini coefficients, 0.32-0.47), followed by British Columbia (0.23-0.36), Manitoba (0.32), and Quebec (0.28-0.37). Cases were disproportionately concentrated in areas with lower income, education attainment, and suitable housing; and higher proportion of visible minorities, recent immigrants, and essential workers. Although a consistent feature across CMAs was concentration by proportion visible minorities, the magnitude of concentration by social determinants varied across CMAs. Interpretation: The feature of geographical concentration of COVID-19 cases was consistent across CMAs, but the pattern by social determinants varied. Geographically-prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to SARS-CoV-2's resurgence.
Subject(s)
COVID-19ABSTRACT
Objective: To track uptake of workplace SARS-CoV-2 testing programs using publicly-available data (e.g., press releases), supplementing findings from employer surveys. Methods: We tracked testing programs reported by 1,159 Canadian and 1,081 international employers across sectors from March 1, 2020 to March 31, 2021. We analyzed trends in uptake of testing programs, including over time and by workplace setting. Results: 9.5% (n=110) of Canadian employers and 24.6% (n=266) of international employers tracked reported testing. The prevalence of reported testing programs was less than 20% in some settings associated with high risk of transmission including retail and customer-facing environments, and indoor and mixed blue collar workplaces. Conclusions: Publicly-available data suggest that fewer employers are testing than indicated by surveys. Workplace safety in high-risk workplaces could be further improved by implementing testing strategies that deploy both screening and diagnostic tests.
ABSTRACT
Background: Inequities in the burden of COVID-19 observed across Canada suggest heterogeneity within community transmission. Objectives: To quantify the magnitude of heterogeneity in the wider community (outside of long-term care homes) in Toronto, Canada and assess how the magnitude in concentration evolved over time (January 21 to November 21, 2020). Design: Retrospective, population-based observational study using surveillance data from Ontario's Case and Contact Management system. Setting: Toronto, Canada. Participants: Laboratory-confirmed cases of COVID-19 (N=33,992). Measurements: We generated epidemic curves by SDOH and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 cases by social determinants of health (SDOH) and estimated the crude Gini coefficient. We examined the correlation between SDOH using Pearson correlation coefficients. Results: The Gini coefficient of cumulative cases by population size was 0.41 (95% CI: 0.36-0.47) and were estimated for: household income (0.20, 95%CI: 0.14-0.28); visible minority (0.21, 95%CI: 0.16-0.28); recent immigration (0.12, 95%CI: 0.09-0.16); suitable housing (0.21, 95%CI: 0.14-0.30); multi-generational households (0.19, 95%CI: 0.15-0.23); and essential workers (0.28, 95% CI: 0.23-0.34). Most SDOH were highly correlated. Locally acquired cases were concentrated in higher income neighbourhoods in the early phase of the epidemic, and then concentrated in lower income neighbourhoods. Mirroring the trajectory of epidemic curves by income, the Lorenz curve shifted over time from below to above the line of equality with a similar pattern across SDOH. Limitations: Study relied on area-based measures of the SDOH and individual case counts of COVID-19. We cannot infer concentration of cases by specific occupational exposures given limitation to broad occupational categories. Conclusion: COVID-19 is increasingly concentrated by SDOH given socioeconomic inequities and structural racism. Primary Funding Source: Canadian Institutes of Health Research.
Subject(s)
COVID-19ABSTRACT
Insomnia and sleep disturbances are common in pregnancy and have potentially significant consequences for both maternal and infant health. There is limited research examining the effectiveness of cognitive behavioural therapy for insomnia (CBT-I) during pregnancy. With increased distress and limited access to services during the COVID-19 pandemic, there is also an unprecedented need for telehealth delivery of treatment programs for pregnant women. The primary aim of the trial is to evaluate the impact of in-person or telehealth cognitive behavioural therapy for insomnia (CBT-I) versus a treatment as usual (TAU) control group in reducing symptoms of insomnia experienced in pregnancy. We hypothesize that participants who receive CBT-I delivered in person or via telehealth will report fewer insomnia symptoms. The secondary aims are to investigate if CBT-I versus TAU increases gestational length and reduces symptoms of depression. We hypothesize that receiving CBT-I will be associated with longer gestational length (as confirmed by public health records) and lower depressive symptoms.
Subject(s)
COVID-19ABSTRACT
BackgroundStudies reporting estimates of the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies have rapidly emerged. We aimed to synthesize seroprevalence data to better estimate the burden of SARS-CoV-2 infection, identify high-risk groups, and inform public health decision making. MethodsIn this systematic review and meta-analysis, we searched publication databases, preprint servers, and grey literature sources for seroepidemiological study reports, from January 1, 2020 to August 28, 2020. We included studies that reported a sample size, study date, location, and seroprevalence estimate. Estimates were corrected for imperfect test accuracy with Bayesian measurement error models. We conducted meta-analysis to identify demographic differences in the prevalence of SARS-CoV-2 antibodies, and meta-regression to identify study-level factors associated with seroprevalence. We compared region-specific seroprevalence data to confirmed cumulative incidence. PROSPERO: CRD42020183634. FindingsWe identified 338 seroprevalence studies including 2.3 million participants in 50 countries. Seroprevalence was low in the general population (median 3.2%, IQR 1.0-6.4%) and slightly higher in at-risk populations (median 5.4%, IQR 1.5-18.4%). Median seroprevalence varied by WHO Global Burden of Disease region (p < 0.01), from 1.0% in Southeast Asia, East Asia and Oceania to 18.8% in South Asia. National studies had lower seroprevalence estimates than local (p = 0.02) studies. Compared to White persons, Black persons (prevalence ratio [RR] 2.34, 95% CI 1.60-3.43) and Asian persons (RR 1.56, 95% CI 1.22-2.01) were more likely to be seropositive. Seroprevalence was higher among people ages 18-64 compared to 65 and over (RR 1.26, 95% CI 1.04-1.52). Health care workers had a 1.74x (95% CI: 1.18-2.58) higher risk compared to the general population. There was no difference in seroprevalence between sexes. There were 123 studies (36%) at low or moderate risk of bias. Seroprevalence estimates from national studies were median 11.9 (IQR 8.0 - 16.6) times higher than the corresponding SARS-CoV-2 cumulative incidence. InterpretationMost of the population remains susceptible to SARS-CoV-2 infection. Public health measures must be improved to protect disproportionately affected groups, including non-White people and adults. Measures taken in SE Asia, E Asia and Oceania, and Latin America and Caribbean may have been more effective in controlling virus transmission than measures taken in other regions. FundingPublic Health Agency of Canada through the COVID-19 Immunity Task Force.
Subject(s)
Coronavirus Infections , COVID-19ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have resulted in a number of severe cases of COVID-19 and deaths worldwide. However, knowledge of SARS-CoV-2 infection, diseases and therapy remains limited, underlining the urgency of fundamental studies and drug development. Studies have shown that induction of autophagy and hijacking of autophagic machinery are essential for infection and replication of SARS-CoV-2; however, the mechanism of this manipulation and function of autophagy during SARS-CoV-2 infection remain unclear. In the present study, we identified ORF3 as an inducer of autophagy and revealed that ORF3 localizes to the ER and induces FAM134B-related ERphagy through the HMGB1-Beclin1 pathway. As a consequence, ORF3 induces ER stress and inflammatory responses through ERphagy and sensitizes cells to ER stress-induced cell death, suggesting that SARS-CoV-2 ORF3 hijacks ERphagy and then harms ER homeostasis to induce inflammatory responses through excessive ER stress. These findings reveal a sequential induction of ERphagy, ER stress and acute inflammatory responses during SARS-CoV-2 infection and provide therapeutic potential for ERphagy and ER stress-related drugs for COVID-19 treatment and prevention. ImportanceSARS-CoV-2 infection and replication require autophagosome-like double-membrane vacuoles. Inhibition of autophagy suppresses viral replication, indicating the essential role of autophagy in SARS-CoV-2 infection. However, how SARS-CoV-2 hijacks autophagy and the function of autophagy in the disease progression remain unknown. Here, we reveal that SARS-CoV-2 ORF3 induces ERphagy and consequently induces ER stress to trigger acute inflammatory responses and enhance sensitivity to ER stress-induced apoptosis. Our studies uncover ERphagy-induced inflammatory responses during SARS-CoV-2 infection and provide a promising therapeutic approach for treating SARS-CoV-2 infection and inflammatory responses in COVID-19 by manipulating autophagy and ER stress.
Subject(s)
Coronavirus Infections , COVID-19ABSTRACT
Although the profile of immune cells changes during the natural course of SARS-CoV-2 inflection in human patients, few studies have used a longitudinal approach to reveal their dynamic features. Here, we performed single-cell RNA sequencing of bronchoalveolar lavage fluid cells longitudinally obtained from SARS-CoV-2-infected ferrets. Landscape analysis of the lung immune microenvironment showed dynamic changes in cell proportions and characteristics in uninfected control, at 2 days post-infection (dpi) (early stage of SARS-CoV-2 infection with peak viral titer), and 5 dpi (resolution phase). NK cells and CD8+ T cells exhibited activated subclusters with interferon-stimulated features, which were peaked at 2 dpi. Intriguingly, macrophages were classified into 10 distinct subpopulations, and their relative proportions changed over the time. We observed prominent transcriptome changes among monocyte-derived infiltrating macrophages and differentiated M1/M2 macrophages, especially at 2 dpi. Moreover, trajectory analysis revealed gene expression changes from monocyte-derived infiltrating macrophages toward M1 or M2 macrophages and identified the distinct macrophage subpopulation that had rapidly undergone SARS-CoV-2-mediated activation of inflammatory responses. Finally, we found that different spectrums of M1 or M2 macrophages showed distinct patterns of gene modules downregulated by immune-modulatory drugs. Overall, these results elucidate fundamental aspects of the immune response dynamics provoked by SARS-CoV-2 infection.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible of coronavirus disease 2019 (COVID-19), has devastated public health services and economies worldwide. Despite global efforts to contain the COVID-19 pandemic, SARS-CoV-2 is now found in over 200 countries and has caused an upward death toll of over 1 million human lives as of November 2020. To date, only one Food and Drug Administration (FDA)-approved therapeutic drug (Remdesivir) and a monoclonal antibody, MAb (Bamlanivimab), but no vaccines, are available for the treatment of SARS-CoV-2. As with other viruses, studying SARS-CoV-2 requires the use of secondary approaches to detect the presence of the virus in infected cells. To overcome this limitation, we have generated replication-competent recombinant (r)SARS-CoV-2 expressing fluorescent (Venus or mCherry) or bioluminescent (Nluc) reporter genes. Vero E6 cells infected with reporter-expressing rSARS-CoV-2 can be easily detected via fluorescence or luciferase expression and display a good correlation between reporter gene expression and viral replication. Moreover, rSARS-CoV-2 expressing reporter genes have comparable plaque sizes and growth kinetics to those of wild-type virus, rSARS-CoV-2/WT. We used these reporter-expressing rSARS-CoV-2 to demonstrate their feasibility to identify neutralizing antibodies (NAbs) or antiviral drugs. Our results demonstrate that reporter-expressing rSARS-CoV-2 represent an excellent option to identify therapeutics for the treatment of SARS-CoV-2, where reporter gene expression can be used as valid surrogates to track viral infection. Moreover, the ability to manipulate the viral genome opens the feasibility of generating viruses expressing foreign genes for their use as vaccines for the treatment of SARS-CoV-2 infection. ImportanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), has significantly impacted the human health and economic status worldwide. There is an urgent need to identify effective prophylactics and therapeutics for the treatment of SARS-CoV-2 infection and associated COVID-19 disease. The use of fluorescent- or luciferase-expressing reporter expressing viruses has significantly advanced viral research. Here, we generated recombinant (r)SARS-CoV-2 expressing fluorescent (Venus and mCherry) or luciferase (Nluc) reporter genes and demonstrate that they represent an excellent option to track viral infections in vitro. Importantly, reporter-expressing rSARS-CoV-2 display similar growth kinetics and plaque phenotype that their wild-type counterpart (rSARS-CoV-2/WT), demonstrating their feasibility to identify drugs and/or neutralizing antibodies (NAbs) for the therapeutic treatment of SARS-CoV-2. Henceforth, these reporter-expressing rSARS-CoV-2 can be used to interrogate large libraries of compounds and/or monoclonal antibodies (MAb), in high-throughput screening settings, to identify those with therapeutic potential against SARS-CoV-2.
Subject(s)
Coronavirus Infections , Virus Diseases , COVID-19ABSTRACT
An inexpensive readily manufactured COVID-19 vaccine that protects against severe disease is needed to combat the pandemic. We have employed the LVS {Delta}capB vector platform, previously used successfully to generate potent vaccines against the Select Agents of tularemia, anthrax, plague, and melioidosis, to generate a COVID-19 vaccine. The LVS {Delta}capB vector, a replicating intracellular bacterium, is a highly attenuated derivative of a tularemia vaccine (LVS) previously administered to millions of people. We generated vaccines expressing SARS-CoV-2 structural proteins and evaluated them for efficacy in the golden Syrian hamster, which develops severe COVID-19 disease. Hamsters immunized intradermally or intranasally with a vaccine co-expressing the Membrane (M) and Nucleocapsid (N) proteins, then challenged 5-weeks later with a high dose of SARS-CoV-2, were protected against severe weight loss and lung pathology and had reduced viral loads in the oropharynx and lungs. Protection by the vaccine, which induces murine N-specific interferon-gamma secreting T cells, was highly correlated with pre-challenge serum anti-N TH1-biased IgG. This potent vaccine against severe COVID-19 should be safe and easily manufactured, stored, and distributed, and given the high homology between MN proteins of SARS-CoV and SARS-CoV-2, has potential as a universal vaccine against the SARS subset of pandemic causing {beta}-coronaviruses.
Subject(s)
Severe Acute Respiratory Syndrome , Weight Loss , COVID-19 , Tularemia , MelioidosisABSTRACT
Background: The SARS-CoV-2 disease 2019 (COVID-19) pandemic has spread across the world with varying impact on health systems and outcomes. We assessed how the type and timing of public- health interventions impacted the course of the outbreak in Alberta and other Canadian provinces. Methods: We used publicly-available data to summarize rates of laboratory data and mortality in relation to measures implemented to contain the outbreak and testing strategy. We estimated the transmission potential of SARS-CoV-2 before the state of emergency declaration for each province (R0) and at the study end date (Rt). Results: The first cases were confirmed in Ontario (January 25) and British Columbia (January 28). All provinces implemented the same health-policy measures between March 12 and March 30. Alberta had a higher percentage of the population tested (3.8%) and a lower mortality rate (3/100,000) than Ontario (2.6%; 11/100,000) or Quebec (3.1%; 31/100,000). British Columbia tested fewer people (1.7%) and had similar mortality as Alberta. Data on provincial testing strategies were insufficient to inform further analyses. Mortality rates increased with increasing rates of lab- confirmed cases in Ontario and Quebec, but not in Alberta. R0 was similar across all provinces, but varied widely from 2.6 (95% confidence intervals 1.9-3.4) to 6.4 (4.3-8.5), depending on the assumed time interval between onset of symptoms in a primary and a secondary case (serial interval). The outbreak is currently under control in Alberta, British Columbia and Nova Scotia (Rt <1). Interpretation: COVID-19-related health outcomes varied by province despite rapid implementation of similar health-policy interventions across Canada. Insufficient information about provincial testing strategies and a lack of primary data on serial interval are major limitations of existing data on the Canadian COVID-19 outbreak.