Project description:BackgroundThe COVID-19 pandemic has continued to pose a major global public health risk. The importance of public health surveillance systems to monitor the spread and impact of COVID-19 has been well demonstrated. The purpose of this study was to describe the development and effectiveness of a real-time public health syndromic surveillance system (ACES Pandemic Tracker) as an early warning system and to provide situational awareness in response to the COVID-19 pandemic in Ontario, Canada.MethodsWe used hospital admissions data from the Acute Care Enhanced Surveillance (ACES) system to collect data on pre-defined groupings of symptoms (syndromes of interest; SOI) that may be related to COVID-19 from 131 hospitals across Ontario. To evaluate which SOI for suspected COVID-19 admissions were best correlated with laboratory confirmed admissions, laboratory confirmed COVID-19 hospital admissions data were collected from the Ontario Ministry of Health. Correlations and time-series lag analysis between suspected and confirmed COVID-19 hospital admissions were calculated. Data used for analyses covered the period between March 1, 2020 and September 21, 2020.ResultsBetween March 1, 2020 and September 21, 2020, ACES Pandemic Tracker identified 22,075 suspected COVID-19 hospital admissions (150 per 100,000 population) in Ontario. After correlation analysis, we found laboratory-confirmed hospital admissions for COVID-19 were strongly and significantly correlated with suspected COVID-19 hospital admissions when SOI were included (Spearman's rho = 0.617) and suspected COVID-19 admissions when SOI were excluded (Spearman's rho = 0.867). Weak to moderate significant correlations were found among individual SOI. Laboratory confirmed COVID-19 hospital admissions lagged in reporting by 3 days compared with suspected COVID-19 admissions when SOI were excluded.ConclusionsOur results demonstrate the utility of a hospital admissions syndromic surveillance system to monitor and identify potential surges in severe COVID-19 infection within the community in a timely manner and provide situational awareness to inform preventive and preparatory health interventions.
Project description:BackgroundQuantifying the impact of environmental factors on COVID-19 transmission is crucial in preventing more cases. Ultraviolet (UV) radiation and ozone (O3) have reported antimicrobial properties but few studies have examined associations with community infectivity of COVID-19. Research suggests UV light can be preventative while the effect of O3 is contested. We sought to determine the relationship between UV, O3, and COVID-19 incidence in Ontario, Canada.MethodsIn our time series analyses, we calculated daily incidence rates and reproductive number (Rt) from 34,975 cases between January and June 2020 across 34 Ontario Public Health Units. We used generalised linear models, adjusting for potential confounders, to calculate point estimates (PE) and 95% confidence intervals (CI) for UV and O3. Analyses were further stratified by age groups and outbreaks at institutions versus community.ResultsWe found that 1-week averaged UV was significantly associated with a 13% decrease (95% CI: 0.80-0.96) in overall COVID-19 Rt, per unit increase. A negative association with UV was also significant among community outbreaks (PE: 0.88, 95% CI: 0.81-0.96) but not institutional outbreaks (PE: 0.94, 95% CI: 0.85-1.03). A positive association of O3 with COVID-19 incidence is strongly suggested among institutional outbreak cases (PE: 1.06, 95% CI: 1.00-1.13).ConclusionOur study found evidence to support the hypothesis that higher UV reduced transmission of COVID-19 and some evidence that ground-level O3 positively influenced COVID-19 transmission. Setting of infection should be strongly considered as a factor in future research. UV and O3 may explain some of COVID-19's seasonal behaviour.
Project description:BackgroundSyndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada.MethodsThis was a cross-sectional study using three distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups.ResultsWe found that over March- April 2020, 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month. Across the three surveys, SARS-CoV-2-testing was reported in 2-9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Métis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath.InterpretationThe low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of SARS-CoV-2 testing rates.
Project description:BackgroundThe province of Ontario, Canada, has instituted indefinite school closures (SC) as well as other social distancing measures to mitigate the impact of the novel coronavirus disease 2019 (COVID-19) pandemic. We sought to evaluate the effect of SC on reducing attack rate and the need for critical care during COVID-19 outbreaks, while considering scenarios with concurrent implementation of self-isolation (SI) of symptomatic cases.MethodsWe developed an age-structured agent-based simulation model and parameterized it with the demographics of Ontario stratified by age and the latest estimates of COVID-19 epidemiologic characteristics. Disease transmission was simulated within and between different age groups by considering inter- and intra-group contact patterns. The effect of SC of varying durations on the overall attack rate, magnitude and peak time of the outbreak, and requirement for intensive care unit (ICU) admission in the population was estimated. Secondly, the effect of concurrent community-based voluntary SI of symptomatic COVID-19 cases was assessed.ResultsSC reduced attack rates in the range of 7.2-12.7% when the duration of SC increased from 3 to 16 weeks, when contacts among school children were restricted by 60-80%, and in the absence of SI by mildly symptomatic persons. Depending on the scenario, the overall reduction in ICU admissions attributed to SC throughout the outbreak ranged from 3.3 to 6.7%. When SI of mildly symptomatic persons was included and practiced by 20%, the reduction of attack rate and ICU admissions exceeded 6.3% and 9.1% (on average), respectively, in the corresponding scenarios.ConclusionOur results indicate that SC may have limited impact on reducing the burden of COVID-19 without measures to interrupt the chain of transmission during both pre-symptomatic and symptomatic stages. While highlighting the importance of SI, our findings indicate the need for better understanding of the epidemiologic characteristics of emerging diseases on the effectiveness of social distancing measures.
Project description:The emergence and rapid global spread of SARS-CoV-2 demonstrates the importance of infectious disease surveillance, particularly during the early stages. Viral genomes can provide key insights into transmission chains and pathogenicity. Nasopharyngeal swabs were obtained from thirty-two of the first SARS-CoV-2 positive cases (March 18-30) in Kingston Ontario, Canada. Viral genomes were sequenced using Ion Torrent (n?=?24) and MinION (n?=?27) sequencing platforms. SARS-CoV-2 genomes carried forty-six polymorphic sites including two missense and three synonymous variants in the spike protein gene. The D614G point mutation was the predominate viral strain in our cohort (92.6%). A heterozygous variant (C9994A) was detected by both sequencing platforms but filtered by the ARTIC network bioinformatic pipeline suggesting that heterozygous variants may be underreported in the SARS-CoV-2 literature. Phylogenetic analysis with 87,738 genomes in the GISAID database identified global origins and transmission events including multiple, international introductions as well as community spread. Reported travel history validated viral introduction and transmission inferred by phylogenetic analysis. Molecular epidemiology and evolutionary phylogenetics may complement contact tracing and help reconstruct transmission chains of emerging diseases. Earlier detection and screening in this way could improve the effectiveness of regional public health interventions to limit future pandemics.
Project description:ObjectiveTo analyze workplace outbreaks by industry sector in the first wave of the pandemic, and associated household cases.MethodsNumber, size, and duration of outbreaks were described by sector, and outbreak cases were compared to sporadic cases in the same time frame. Address matching identified household cases with onset ≥2 days before, ≥2 days after, or within 1 day of the workplace outbreak case.ResultsThere were 199 outbreaks with 1245 cases, and 68% of outbreaks and 80% of cases belonged to (1) Manufacturing, (2) Agriculture, Forestry, Fishing, Hunting, (3) Transportation and Warehousing. There were 608 household cases associated with 339 (31%) outbreak cases, increasing the burden of illness by 56%.ConclusionsWorkplace outbreaks primarily occurred in three sectors. Prevention measures should target industry sectors at risk to prevent spread in and out of the workplace.
Project description:BackgroundVarious public health measures have been implemented globally to counter the coronavirus disease 2019 (COVID-19) pandemic. The purpose of this study was to evaluate respiratory virus surveillance data to determine the effectiveness of such interventions in reducing transmission of seasonal respiratory viruses.MethodWe retrospectively analysed data from the Respiratory Virus Detection Surveillance System in Canada, before and during the COVID-19 pandemic, by interrupted time series regression.ResultsThe national level of infection with seasonal respiratory viruses, which generally does not necessitate quarantine or contact screening, was greatly reduced after Canada imposed physical distancing and other quarantine measures. The 2019-2020 influenza season ended earlier than it did in the previous year. The influenza virus was replaced by rhinovirus/enterovirus or parainfluenza virus in the previous year, with the overall test positivity remaining at approximately 35%. However, during the 2019-2020 post-influenza period, the overall test positivity of respiratory viruses during the COVID-19 was still low (7.2%). Moreover, the 2020-2021 influenza season had not occurred by the end of February 2021.ConclusionRespiratory virus surveillance data may provide real-world evidence of the effectiveness of implemented public health interventions during the current and future pandemics.
Project description:In March of 2020, the province of Ontario declared a State of Emergency (SOE) to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease (COVID-19). This disruption to the economy provided an opportunity to measure change in air pollution when the population spends more time at home with fewer trips. Hourly air pollution observations were obtained for fine particulate matter, nitrogen dioxide, nitrogen oxides and ozone from the Ontario air monitoring network for 2020 and the previous five years. The analysis is focused on a five-week period during the SOE with a previous five-week period used as a control. Fine particulate matter did not show any significant reductions during the SOE. Ozone concentrations at 12 of the 32 monitors were lower than any of the previous five-years; however, four locations were above average. Average ozone concentrations were 1 ppb lower during the SOE, but this ranged at individual monitors from 1.5 ppb above to 4.2 ppb below long-term conditions. Nitrogen dioxide and nitrogen oxides demonstrated a reduction across Ontario, and both pollutants displayed their lowest concentrations for 22 of 29 monitors. Individual monitors ranged from 1 ppb (nitrogen dioxide) and 5 ppb (nitrogen oxides) above average to 4.5 (nitrogen dioxide) and 7.1 ppb (nitrogen oxides) below average. Overall, both nitrogen dioxide and nitrogen oxides demonstrated a reduction across Ontario in response to the COVID-19 SOE, ozone concentrations suggested a possible reduction, and fine particulate matter has not varied from historic concentrations.