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
Background: Performance characteristics of SARS-CoV-2 nucleic acid detection assays are understudied within contexts of low pre-test probability, including screening asymptomatic persons without epidemiological links to confirmed cases, or asymptomatic surveillance testing. SARS-CoV-2 detection without symptoms may represent resolved infection with persistent RNA shedding, presymptomatic or asymptomatic infection, or a false positive test. This study assessed clinical specificity of SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) assays by retesting positive specimens from five pre-test probability groups ranging from high to low with an alternate assay. Materials and Methods: A total of 122 rRT-PCR positive specimens collected from unique patients between March and July 2020 were retested using a laboratory-developed nested RT-PCR assay targeting the RNA-dependent RNA polymerase (RdRp) gene followed by Sanger sequencing. Results: Significantly less positive results in the lowest pre-test probability group (facilities with institution-wide screening having [≤]3 positive asymptomatic cases) were reproduced with the nested RdRp gene RT-PCR assay than in all other groups combined (5/32, 15.6% vs 61/90, 68%; p <0.0001), and in each subgroup with higher pre-test probability (individual subgroup range 50.0% to 85.0%). Conclusions: A higher proportion of false-positive test results are likely with lower pre-test probability. Positive SARS-CoV-2 PCR results should be interpreted within the context of patient history, clinical setting, known exposure, and estimated community disease prevalence. Large-scale SARS-CoV-2 screening testing initiatives among low pre-test probability populations should be evaluated thoroughly prior to implementation given the risk of false positives and consequent potential for harm at the individual and population level.
Subject(s)
COVID-19ABSTRACT
Background: Travel-related dissemination of SARS-CoV-2 continues to contribute to the global pandemic. A novel SARS-CoV-2 lineage (B.1.177) reportedly arose in Spain in the summer of 2020, with subsequent spread across Europe linked to travel by infected individuals. Surveillance and monitoring through the use of whole genome sequencing (WGS) offers insights into the global and local movement of pathogens such as SARS-CoV-2 and can detect introductions of novel variants. Methods: We analyzed the genomes of SARS-CoV-2 sequenced for surveillance purposes from specimens received by Public Health Ontario (Sept 6 - Oct 10, 2020), collected from individuals in eastern Ontario. Taxonomic lineages were identified using pangolin (v2.08) and phylogenetic analysis incorporated publicly available genomes covering the same time period as the study sample. Epidemiological data collected from laboratory requisitions and standard reportable disease case investigation was integrated into the analysis. Results: Genomic surveillance identified a COVID-19 case with SARS-CoV-2 lineage B.1.177 from an individual in eastern Ontario in late September, 2020. The individual had recently returned from Europe. Genomic analysis with publicly available data indicate the most closely related genomes to this specimen were from Southern Europe. Genomic surveillance did not identify further cases with this lineage. Conclusions: Genomic surveillance allowed for early detection of a novel SARS-CoV-2 lineage in Ontario which was deemed to be travel related. This type of genomic-based surveillance is a key tool to measure the effectiveness of public health measures such as mandatory self-isolation for returned travellers, aimed at preventing onward transmission of newly introduced lineages of SARS-CoV-2.