The effect of seasonal respiratory virus transmission on syndromic surveillance for COVID-19 in Ontario, Canada.
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ABSTRACT:
SUBMITTER: Maharaj AS
PROVIDER: S-EPMC7993926 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
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The effect of seasonal respiratory virus transmission on syndromic surveillance for COVID-19 in Ontario, Canada.
Maharaj Arjuna S AS Parker Jennifer J Hopkins Jessica P JP Gournis Effie E Bogoch Isaac I II Rader Benjamin B Astley Christina M CM Ivers Noah N Hawkins Jared B JB VanStone Nancy N Tuite Ashleigh R AR Fisman David N DN Brownstein John S JS Lapointe-Shaw Lauren L
The Lancet. Infectious diseases 20210325 5
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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.
| S-EPMC8233625 | biostudies-literature
Project description:IntroductionDetection of community respiratory syncytial virus (RSV) infections informs the timing of immunoprophylaxis programs and hospital preparedness for surging pediatric volumes. In many jurisdictions, this relies upon RSV clinical test positivity and hospitalization (RSVH) trends, which are lagging indicators. Wastewater-based surveillance (WBS) may be a novel strategy to accurately identify the start of the RSV season and guide immunoprophylaxis administration and hospital preparedness.MethodsWe compared citywide wastewater samples and pediatric RSVH in Ottawa and Hamilton between August 1, 2022, and March 5, 2023. 24-h composite wastewater samples were collected daily and 5 days a week at the wastewater treatment facilities in Ottawa and Hamilton, Ontario, Canada, respectively. RSV WBS samples were analyzed in real-time for RSV by RT-qPCR.ResultsRSV WBS measurements in both Ottawa and Hamilton showed a lead time of 12 days when comparing the WBS data set to pediatric RSVH data set (Spearman's ρ = 0.90). WBS identify early RSV community transmission and declared the start of the RSV season 36 and 12 days in advance of the provincial RSV season start (October 31) for the city of Ottawa and Hamilton, respectively. The differing RSV start dates in the two cities is likely associated with geographical and regional variation in the incidence of RSV between the cities.DiscussionQuantifying RSV in municipal wastewater forecasted a 12-day lead time of the pediatric RSVH surge and an earlier season start date compared to the provincial start date. These findings suggest an important role for RSV WBS to inform regional health system preparedness, reduce RSV burden, and understand variations in community-related illness as novel RSV vaccines and monoclonal antibodies become available.
| S-EPMC10566629 | biostudies-literature
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.
| S-EPMC8213179 | biostudies-literature
Project description:The number of confirmed COVID-19 cases reached over 1.3 million in Ontario, Canada by June 4, 2022. The continued spread of the virus underlying COVID-19 has been spurred by the emergence of variants since the initial outbreak in December, 2019. Much attention has thus been devoted to tracking and modelling the transmission of COVID-19. Compartmental models are commonly used to mimic epidemic transmission mechanisms and are easy to understand. Their performance in real-world settings, however, needs to be more thoroughly assessed. In this comparative study, we examine five compartmental models-four existing ones and an extended model that we propose-and analyze their ability to describe COVID-19 transmission in Ontario from January 2022 to June 2022.
| S-EPMC10497623 | biostudies-literature
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.
| S-EPMC7787508 | biostudies-literature
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.
| S-EPMC7531838 | biostudies-literature
Project description:BackgroundIn temperate climates, invasive meningococcal disease (IMD) incidence tends to coincide with or closely follow peak incidence of influenza virus infection; at a seasonal level, increased influenza activity frequently correlates with increased seasonal risk of IMD.MethodsWe evaluated 240 cases of IMD reported in central Ontario, Canada, from 2000 to 2006. Associations between environmental and virological (influenza A, influenza B and respiratory syncytial virus (RSV)) exposures and IMD incidence were evaluated using negative binomial regression models controlling for seasonal oscillation. Acute effects of weekly respiratory virus activity on IMD risk were evaluated using a matched-period case-crossover design with random directionality of control selection. Effects were estimated using conditional logistic regression.ResultsMultivariable negative binomial regression identified elevated IMD risk with increasing influenza A activity (per 100 case increase, incidence rate ratio?=?1.18, 95% confidence interval (CI): 1.06, 1.31). In case-crossover models, increasing weekly influenza A activity was associated with an acute increase in the risk of IMD (per 100 case increase, odds ratio (OR) ?=?2.03, 95% CI: 1.28 to 3.23). Increasing weekly RSV activity was associated with increased risk of IMD after adjusting for RSV activity in the previous 3 weeks (per 100 case increase, OR?=?4.31, 95% CI: 1.14, 16.32). No change in disease risk was seen with increasing influenza B activity.ConclusionsWe have identified an acute effect of influenza A and RSV activity on IMD risk. If confirmed, these finding suggest that influenza vaccination may have the indirect benefit of reducing IMD risk.
| S-EPMC2984510 | biostudies-literature
Project description:BackgroundThe ongoing coronavirus disease 2019 (COVID-19) pandemic has resulted in implementation of public health measures worldwide to mitigate disease spread, including; travel restrictions, lockdowns, messaging on handwashing, use of face coverings and physical distancing. As the pandemic progresses, exceptional decreases in seasonal respiratory viruses are increasingly reported. We aimed to evaluate the impact of the pandemic on laboratory confirmed detection of seasonal non-SARS-CoV-2 respiratory viruses in Canada.MethodsEpidemiologic data were obtained from the Canadian Respiratory Virus Detection Surveillance System. Weekly data from the week ending 30th August 2014 until the week ending the 13th March 2021 were analysed. We compared trends in laboratory detection and test volumes during the 2020/2021 season with pre-pandemic seasons from 2014 to 2019.FindingsWe observed a dramatically lower percentage of tests positive for all seasonal respiratory viruses during 2020-2021 compared to pre-pandemic seasons. For influenza A and B the percent positive decreased to 0•0015 and 0•0028 times that of pre-pandemic levels respectively and for RSV, the percent positive dropped to 0•0169 times that of pre-pandemic levels. Ongoing detection of enterovirus/rhinovirus occurred, with regional variation in the epidemic patterns and intensity.InterpretationWe report an effective absence of the annual seasonal epidemic of most seasonal respiratory viruses in 2020/2021. This dramatic decrease is likely related to implementation of multi-layered public health measures during the pandemic. The impact of such measures may have relevance for public health practice in mitigating seasonal respiratory virus epidemics and for informing responses to future respiratory virus pandemics.FundingNo additional funding source was required for this study.
| S-EPMC8285668 | biostudies-literature
Project description:Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global Moran's I spatial autocorrelation, and Local Moran's I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results: This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities). Conclusions: Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing.
| S-EPMC9130760 | biostudies-literature
Project description:BackgroundData on household transmission of carbapenemase-producing Enterobacterales (CPE) remain limited. We studied risk of CPE household co-colonization and transmission in Ontario, Canada.MethodsWe enrolled CPE index cases (identified via population-based surveillance from January 2015 to October 2018) and their household contacts. At months 0, 3, 6, 9, and 12, participants provided rectal and groin swabs. Swabs were cultured for CPE until September 2017, when direct polymerase chain reaction (PCR; with culture of specimens if a carbapenemase gene was detected) replaced culture. CPE risk factor data were collected by interview and combined with isolate whole-genome sequencing to determine likelihood of household transmission. Risk factors for household contact colonization were explored using a multivariable logistic regression model with generalized estimating equations.ResultsNinety-five households with 177 household contacts participated. Sixteen (9%) household contacts in 16 (17%) households were CPE-colonized. Household transmission was confirmed in 3/177 (2%) cases, probable in 2/177 (1%), possible in 9/177 (5%), and unlikely in 2/177 (1%). Household contacts were more likely to be colonized if they were the index case's spouse (odds ratio [OR], 6.17; 95% confidence interval [CI], 1.05-36.35), if their index case remained CPE-colonized at household enrollment (OR, 7.00; 95% CI, 1.92-25.49), or if they had at least 1 set of specimens processed after direct PCR was introduced (OR, 6.46; 95% CI, 1.52-27.40).ConclusionsNine percent of household contacts were CPE-colonized; 3% were a result of household transmission. Hospitals may consider admission screening for patients known to have CPE-colonized household contacts.
| S-EPMC8662791 | biostudies-literature