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SARS-CoV-2 wastewater surveillance data and metadata in the Open Data Model format. Part 1: Québec City
<p>SARS-CoV-2 wastewater surveillance data and metadata in the Open Data Model format. Part 1: Québec City Authors</p> <ul> <li>Therrien, J-D<sup>1</sup></li> <li>Maere, T.<sup>1</sup></li> <li>Sanchez-Quete, F.<sup>2</sup></li> <li>Tsitouras, A.<sup>2</sup></li> <li>Goitom, E.<sup>3</sup></li> <li>Cloutier, F.<sup>4</sup></li> <li>Dufour, D.<sup>4</sup></li> <li>Proulx, F. <sup>4</sup></li> <li>Nicolaï, N.<sup>1</sup></li> <li>Philippe, R.<sup>1</sup></li> <li>Tohidi, M.<sup>1</sup></li> <li>Dorner, S.<sup>3</sup></li> <li>Frigon, D.<sup>2</sup></li> <li>Vanrolleghem, P.A.<sup>1</sup></li> </ul> <p>Affiliations</p> <ul> <li><sup>1</sup> model<em>EAU</em>, Département de génie civil et de génie des eaux, Université Laval</li> <li><sup>2</sup> Microbial Community Engineering Lab (MiCEL), Department of Civil Engineering, McGill University</li> <li><sup>3</sup> Polytechnique Montréal</li> <li><sup>4</sup> Ville de Québec</li> </ul> <p>General Remarks</p> <p>Wastewater-based surveillance of SARS-CoV-2 virus can detect between 1 and 30 infected individuals per 100,000 (including asymptomatic ones) by analyzing the population's sewage. As such, this method is very attractive since it costs only a fraction of clinical testing (as low as 1%). Human faeces may contain the virus a few days before a person becomes ill. Thus, this approach allows for detection of outbreaks 2-7 days before the increase in reported cases stemming from clinical screening tests (Bibby et al., 2021). Wastewater-based surveillance complements clinical testing by geolocating outbreaks, which may help targeting intensive screening programs. Moreover, it provides a quick indication of whether new public health measures (e.g., masks, social distancing, confinement, and curfew) are effective.</p> <p>Sampling</p> <p>The reported dataset contains open data collected in the province of Québec as part of the SARS-CoV-2 wastewater-based surveillance program <a href="https://www.centreau.ulaval.ca/en/covid/">CentrEau</a>-COVID. Four of the largest cities in the province (Montréal, Laval, Québec City, and Trois-Rivières), as well as the municipalities of four rural regions (Mauricie, Centre-du-Québec, Bas-St-Laurent, and Gaspésie) participated in the program. The entire dataset includes 31 sampling sites covering approximately half the population of the province of Québec (population size of 8.5 million). The timeframe covered by the dataset varies for each site. The earliest surveillance program was launched in March 2020, others followed soon after. Samples were collected using various methods, such as 24h composite samples, grab samples, and passive sampling using variations on the Moore swab method (Schang et al., 2020)</p> <p>Analysis</p> <p>Prior to the analysis of the samples for SARS-CoV-2, physiochemical parameters such as total suspended solids (TSS), turbidity, conductivity, ammonium concentration, and pH were measured. The samples were subsequently concentred by filtration using a MEC filter (0.45 um), followed by total RNA extraction using the Qiagen AllPrep PowerViral DNA/RNA Kit (Qiagen, USA) with some modifications (beta-mercaptoethanol concentration raised to 10% and lysis performed at 55 °C for 30 minutes) (Ahmed et al., 2020). SARS-CoV-2 viral RNA was detected by a one-step RT-qPCR. To assess the RNA recovery rate of the procedure, samples were spiked before extraction with a known concentration of Bovine Respiratory Syncytial Virus (BRSV) using the Zoetis INFORCE 3 vaccine (Zoetis, USA). In addition to SARS-CoV-2, samples were assessed for Pepper Mild Mottle Virus (PMMoV), the daily load of which is hypothesized to represent the fecal load contributions to the samples at a given site and time. PCR conditions and primer used to collect viral data are described in the files <code>primers.md</code> and <code>PCR conditions.md</code>.</p> <p>Compilation</p> <p>The measurements on wastewater samples carried out by the participating laboratories of this study are found in the <code>WWMeasure</code> table. The values provided by municipalities come from laboratories accredited by the Centre d'expertise en analyse environnementale du Québec (CEAEQ), in compliance with the latter's quality assurance protocols. The COVID-19-related public health data found in the <code>CPHD</code> table were collected from the Institut National de Santé Publique du Québec (INSPQ)'s public reports. Wastewater data taken in-situ at the sampling sites (e.g., the flow at pumping stations or water resource recovery facilities (WRRFs)) are found in the <code>SiteMeasure</code> table and were taken by the institutions responsible for managing the sites. All of the data, stemming from multiple sources, were combined into the <a href="https://github.com/Big-Life-Lab/ODM">Open Data Model (ODM)</a> standard format using the <a href="https://github.com/modelEAU/ODM-Import">ODM-Import python package</a> (see also Structure).</p> <p>Validation</p> <p>Wastewater and sample data were manually assessed for quality by our research collaborators. Data points for which the quality appeared to be uncertain were tagged with the value <code>True</code> in the <code>qualityFlag</code> column. Conversely, data deemed of good quality have a quality flag of <code>False</code>. Data that were not checked have a quality flag of <code>NA</code>. Textual comments describing the issues with the data points in more detail are also included in the dataset using the <code>notes</code> column of the relevant tables. Note that data validation was carried out by the data custodians responsible for each city in the dataset according to available resources. As the project continues and data validation is undertaken on more sections of the dataset, data may be re-analyzed, flagged, or commented as needed. Revisions to the dataset will be reported to the best of our ability.</p> <p>Structure</p> <p>The data contained in this dataset has been structured according to the <a href="https://github.com/Big-Life-Lab/ODM">Open Data Model (ODM) for Wastewater-Based Surveillance</a>. This model provides a standardized dictionary to collect and share data and metadata stemming from wastewater-based surveillance programs. By convention, it splits all data into 10+ thematic tables with each record representing a unique measurement, i.e., long format. For convenience, the <code>wide</code> folder presents the data found in all the other tables in a wide format, i.e., multiple measurements are aligned by <code>timestamp</code>, with each column representing a different parameter.</p> <p>Acknowledgements</p> <p>The authors would like to acknowledge that this dataset was collected thanks to the financial support of the Fonds de Recherche du Québec, the Molson Foundation, the Trottier Family Foundation, CentrEau and NSERC. The authors would also like to acknowledge the efforts of Douglas Manuel (Ottawa Hospital) and Howard Swerdfeger (Public Health Agency of Canada) for their original idea for the Open Data Model and continued development.</p> <p>References</p> <ol> <li> <p>Ahmed, W., Bertsch, P.M., Bivins, A., Bibby, K., Farkas, K., Gathercole, A., Haramoto, E., Gyawali, P., Korajkic, A., McMinn, B.R., Mueller, J.F., Simpson, S.L., Smith, W.J.M., Symonds, E.M., Thomas, K. v., Verhagen, R., Kitajima, M., 2020. Comparison of virus concentration methods for the RT-qPCR-based recovery of murine hepatitis virus, a surrogate for SARS-CoV-2 from untreated wastewater. Science of the Total Environment 739. <a href="https://doi.org/10.1016/j.scitotenv.2020.139960">https://doi.org/10.1016/j.scitotenv.2020.139960</a></p> </li> <li> <p>Bibby, K., Bivins, A., Wu, Z., North, D., 2021. Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19. Water Research 202, 117438. <a href="https://doi.org/10.1016/j.watres.2021.117438">https://doi.org/10.1016/j.watres.2021.117438</a></p> </li> <li> <p>Schang, C., Crosbie, N., Nolan, M., Poon, R., Wang, M., Jex, A., Scales, P., Schmidt, J., Thorley, B.R., Henry, R., Kolotelo, P., Langeveld, J., Schilperoort, R., Shi, B., Einsiedel, S., Thomas, M., Black, J., Wilson, S., McCarthy, D.T., 2020. Passive sampling of viruses for wastewater-based epidemiology: a case-study of SARS-CoV-2 [WWW Document]. URL <a href="https://www.researchgate.net/publication/347103410\_Passive\_sampling\_of\_viruses\_for\_wastewater-based\_epidemiology\_a\_case-study\_of\_SARS-CoV-2?channel=doi&linkId=5fd800f392851c13fe892393&showFulltext=true">https://www.researchgate.net/publication/347103410\_Passive\_sampling\_of\_viruses\_for\_wastewater-based\_epidemiology\_a\_case-study\_of\_SARS-CoV-2?channel=doi&linkId=5fd800f392851c13fe892393&showFulltext=true</a> (accessed 1.18.21).</p> </li> </ol>
Data sets used for: Urban runoff velocity measurement with consumer-grade surveillance cameras and surface structure image velocimetry
<p>Original videos and reference bulk velocity and water depth data sets used to develop the study: <em>Urban runoff velocity measurement with consumer-grade surveillance cameras and surface structure image velocimetry.</em></p> <p>The reference bulk velocity and water depth data sets were obtained with the Nivus OFR Radar and Nivus NivuCompact sensors, respectively.</p>
Data from: Acoustic surveillance of bats along the Green and Colorado Rivers
<p><em>Aim</em>: Emerging research shows how bioindicators, specifically bats, can serve as a means for monitoring conservation and management of riparian corridors for multiple taxonomic groups. To track changes in composition or abundance of bioindicator species, researchers must attain a baseline in species presence and relative activity. We examined the spatial and temporal patterns of bat community composition and activity along a 1,000-mile river corridor to determine species diversity trends by latitude and habitat.</p> <p><em>Location</em>: Colorado River Basin</p> <p><em>Methods</em>: Here we describe the results from an acoustic bat survey conducted opportunistically on the 2019 Sesquicentennial Colorado River Exploring Expedition. This broad, 1,000-mile survey provides a baseline for species distributions over a large geographic range.</p> <p><em>Results</em>: In total, we collected 63 nights of acoustic data over 70-days and recorded over 59,000 files equating to 45,363 call files (≥2 pulses). 18,490 (41% of call files) were identified to species (n = 19 bat species). We applied non-metric multidimensional scaling to characterize spatiotemporal patterns of activity between species, as well as compared bat activity among river features and local environmental conditions (i.e., temperature and time since sunset) using an information theoretic approach.</p> <p><em>Conclusion</em>: Species composition varied by physiographic region and adjacent river habitat, thus providing a quantifiable measure of determining habitat quality along this major river system and providing baseline information for using bats as bioindicators of habitat quality</p>
Region-based Annotation Data of Fire Images for Intelligent Surveillance System
<p>This data presents fire segmentation annotation data on 12 commonly used and publicly available “VisiFire Dataset” videos from <a href="http://signal.ee.bilkent.edu.tr/VisiFire/">http://signal.ee.bilkent.edu.tr/VisiFire/</a>. This annotations dataset was obtained by per-frame, manual hand annotation over the fire region with 2,684 total annotated frames. Since this annotation provides per-frame segmentation data, it offers a new and unique fire motion feature to the existing video, unlike other fire segmentation data that are collected from different still images. The annotations dataset also provides ground truth for segmentation task on videos. With segmentation task, it offers better insight on how well a machine learning model understood, not only detecting whether a fire is present, but also its exact location by calculating metrics such as Intersection over Union (IoU) with this annotations data. This annotations data is a tremendously useful addition to train, develop, and create a much better smart surveillance system for early detection in high-risk fire hotspots area. </p>
Data: Guiding the design of SARS-CoV-2 genomic surveillance by estimating the resolution of outbreak detection
<p>Contains data necessary to reproduce the quantitative results related to a SARS-CoV-2 outbreak in NSW, Australia in the associated paper.</p> <p><strong>icpmr_delta_gisaid.csv</strong><br> Tabular data containing the GISAID accession numbers, dates of collection and submission for all sequences used in the NSW outbreak analysis. The epi set is available on GISAID as EPI_SET_220919ef. The <code>wgs_cluster</code> column contains identifiers of genomic clusters defined at ICPMR, NSW Health Pathology. A value of "Other" means that the sequence either did not belong to a cluster or was part of a cluster that contained fewer than 30 sequences in the study period, and sequences with this value should not be considered to form a single cluster.</p> <p><strong>icpmr_delta_gisaid.dists.tsv.gz</strong><br> Compressed pairwise SNP distance matrix in the format output by snp-dists. The script that creates this file from sequence data is available in the linked code archive.</p>
Common guillemots in the Baltic Sea studied with video surveillance and object detection: raw data, annotations, model, and model outputs
<p>The data comes from common guillemots studied at Stora Karlsö, Sweden between 2019 and 2021. The common guillemots breed at an artificial cliff, and has been filmed continusly from above over three breeding seasons. Using the video material, a YOLOv5 model has been trained to detect adult birds, chicks and eggs. The dataset contains annotations (bounding boxes) used for training the model, the model itself, and outputs from the model (object detections).</p> <p>The data can be used and shared freely.</p>
Data from: Multisectoral approach in zoonotic disease surveillance
<p>Zoonoses are naturally transmissible between humans and animals. Globally, they account for more than 60% of human infections, 75% of emerging infections, 2.7 million human deaths, and 10% of the total DALYs lost yearly in Africa. In the last three decades, Kenya has had sporadic outbreaks of zoonoses. To increase the speed of reporting and efficiencies in detection and control, a multi-sectoral collaboration in zoonotic disease surveillance (MZDS) between human and animal health workers is essential. In an effort, Zoonotic disease unit (ZDU) in Kenya has been established at national and county levels. A cross sectional study was carried out to determine the level of utilization of multisectoral collaboration and its associated determinants in zoonotic disease surveillance among animal and human healthcare workers in Nakuru County. Quantitative data was gathered from 102 participants and quantitative data from 5 key informants. To test for significant differences, Chi-square and independent t-test were used. MZDS utilization level was 16% and the factors associated with higher utilization include; knowing what MZDS entails, education level, sector affiliation, trainings, supportive infrastructure and data storage. Lack of financing and poor coordination are hindrances to MZDS. In conclusion, there is need to finance MZDS activities, strengthen coordination mechanisms, carry out more sensitization and trainings among animal and human healthcare.</p>
Supplemental dataset for "Weather field reconstruction using aircraft surveillance data and a novel meteo-particle model"
<p>This dataset contains the source data used for the experiments of the paper titled "Weather field reconstruction using aircraft surveillance data and a novel meteo-particle model".</p>
Data from: Acoustic surveillance of bats along the Green and Colorado Rivers
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Data from: Multisectoral approach in zoonotic disease surveillance
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Common guillemots in the Baltic Sea studied with video surveillance and object detection: raw data, annotations, model, and model outputs
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Raw data related to: Randomised Clinical Trial: Calorie Restriction Regimen with Tomato Juice Supplementation Ameliorates Oxidative Stress and Preserves a Proper Immune Surveillance Modulating Mitochondrial Bioenergetics of T-Lymphocytes in Obese Children Affected by Non-Alcoholic Fatty Liver Disease (NAFLD)
<p><strong>Abstract</strong></p> <p>Fatty liver disease is a serious complication of childhood obesity. Calorie-restricted regimen (RCR) is one of the e ective therapy for this condition. Aim of the study was to evaluate the effect of lycopene-rich tomato sauce with oregano and basil extracts in obese children with fatty liver on RCR. 61 obese children with fatty liver were enrolled, 52 completed the study. A randomized cross over clinical trial was performed. Participants were assigned to RCR alone or with a supplement of lycopene-rich tomato juice for 60 days; subsequently, the groups were switched to the alternative regimen for the next 60 days. Reduction in BMI, HOMA-IR, cholesterol, triglycerides, liver size, and steatosis was more profound in tomato-supplemented group. Leptin decreased in both groups whereas adiponectin raised only after tomato supplementation. RCR is associated with the impaired engagement of T-cells glycolysis and proliferation, tomato-supplementation resulted in glycolytic metabolic activation of T-cells. Tomato juice ameliorates glucose and lipid metabolism in obese children, improve oxidative and inflammatory state and modulates the mitochondrial metabolism of T-cells contributing to a maintenance of a proper immune surveillance in children, impaired by RCR. The addition of tomato to RCR could be considered a protective and preventive support to obese child.</p> <p><strong>Progetto giovani ricercatori </strong>[GR-2016-02363725] dal titolo: "Immune Tolerance, Metabolism and Multiple Sclerosis: Novel Molecular Tools to Monitor Disease Pathogenesis and Progression"</p>
Data from: Avian disease surveillance on the island of San Cristóbal, Galápagos.
<p>Endemic island species face unprecedented threats, with many populations in decline or at risk of extinction. One important threat is the introduction of novel and potentially devastating diseases, made more pressing due to accelerating global connectivity, urban development, and climatic changes. In the Galápagos archipelago two important wildlife diseases: avian pox (<i>Avipoxvirus spp.</i>) and avian malaria (<i>Plasmodium spp.</i> and related Haemosporidia) challenge endemic species. San Cristóbal island has seen a paucity of disease surveillance in avian populations, despite the island's connectedness to the continent and the wider archipelago. To survey prevalence and better understand the dynamics of these two diseases on San Cristóbal, we captured 1,207 birds of 11 species on the island between 2016 and 2020. Study sites included urban and rural lowland localities as well as rural highland sites in 2019. Of 995 blood samples screened for avian haemosporidia none tested positive for infection. In contrast, evidence of past and active pox infection was observed in 97 birds and identified as strains Gal1 and Gal2. Active pox prevalence differed significantly with contemporary climatic conditions, being highest during El Niño events (~11% in 2016 and in 2019 versus <1% in the La Niña year of 2018). Pox prevalence was also higher at urban sites than rural (11% to 4%, in 2019) and prevalence varied between host species, ranging from 12% in Medium Ground Finches (<i>Geospiza fortis</i>)<i> </i>to 4% in Yellow Warblers (<i>Setophaga petechial aureola</i>). In the most common infected species (Small Ground Finch: <i>Geospiza fuliginosa</i>), birds recovered from pox had significantly longer wings, which may suggest a selective cost to infection. These results illustrate the threat future climate changes and urbanization may present in influencing disease dynamics in the Galápagos, while also highlighting unknowns regarding species-specific susceptibilities to avian pox and the transmission dynamics facilitating outbreaks within these iconic species.</p>
Acute hepatitis B in Poland, 2010-2014 surveillance data
<p>The data file contains the raw data of the routine surveillance of acute hepatitis B in Poland, run by Sanitary Inspection and National Institute of Public Health - National Institute of Hygiene, Warsaw, Poland. The dataset covers anonymized sociodemographic data, hepatitis markers test results and data on exposures on infection from acute HepB cases diagnosed and reported to surveillance system in Poland in 2010-2014.</p>
TSE surveillance and Atypical scrapie intensified monitoring data
<p>GENERAL_DATA_AS_REPORT.xls: statutory TSE surveillance data of sheep and goats 2013-2019 from 22 countries.</p> <p>MANDATE_DATA_RAW_AS_REPORT.xls: raw data collated by the EC for the mandate EFSA-Q-2020-00662, including the results of the intensified monitoring implemented in flocks/herds from 22 countries in which a case of atypical scrapie has been confirmed</p> <p>MANDATE_DATA_ANALYSIS_AS_REPORT.xls: : data collated by the EC for the mandate EFSA-Q-2020-00662, including the results of the intensified monitoring implemented in flocks/herds from 22 countries in which a case of atypical scrapie has been confirmed, aggregated for analysis.</p>
Supplementary data for "Timely vaccine strain selection and genomic surveillance improves evolutionary forecast accuracy of seasonal influenza A/H3N2"
<p>Supplementary materials associated with the manuscript by Huddleston and Bedford titled "Timely vaccine strain selection and genomic surveillance improves evolutionary forecast accuracy of seasonal influenza A/H3N2".</p>
Calibration of a pedestrian ingress model based on CCTV surveillance data using machine learning methods: data and code
<p>The package includes a dataset of trajectories obtained from a real-time pedestrian traffic detector at the vaccination centre and the code needed to validate the analyses described in the paper entitled Calibration of a pedestrian ingress model based on CCTV surveillance data using machine learning methods. Version 1.0.1 is a patch that corrects path to data.</p>
High prevalence does not necessarily equal maintenance species: Avoiding biased claims of disease reservoirs when using surveillance data
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Data for: Spatial-temporal analysis of natural hazards and disasters in the Greater Horn of Africa between 2010 and 2024 to inform disaster risk reduction, and surveillance and control strategies for climate and environmentally sensitive diseases
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Data from: Sepsis surveillance: an examination of parameter sensitivity and alert reliability
Objective: To examine performance of a sepsis surveillance system in a simulated environment where modifications to parameters and settings for identification of at-risk patients can be explored in-depth. Materials and Methods: This was a multiple center observational cohort study. The study population comprised 14 917 adults hospitalized in 2016. An expert-driven rules algorithm was applied against 15.1 million data points to simulate a system with binary notification of sepsis events. Three system scenarios were examined: a scenario as derived from the second version of the Consensus Definitions for Sepsis and Septic Shock (SEP-2), the same scenario but without systolic blood pressure (SBP) decrease criteria (near SEP-2), and a conservative scenario with limited parameters. Patients identified by scenarios as being at-risk for sepsis were assessed for suspected infection. Multivariate binary logistic regression models estimated mortality risk among patients with suspected infection. Results: First, the SEP-2-based scenario had a hyperactive, unreliable parameter SBP decrease >40 mm Hg from baseline. Second, the near SEP-2 scenario demonstrated adequate reliability and sensitivity. Third, the conservative scenario had modestly higher reliability, but sensitivity degraded quickly. Parameters differed in predicting mortality risk and represented a substitution effect between scenarios. Discussion: Configuration of parameters and alert criteria have implications for patient identification and predicted outcomes. Conclusion: Performance of scenarios was associated with scenario design. A single hyperactive, unreliable parameter may negatively influence adoption of the system. A trade-off between modest improvements in alert reliability corresponded to a steep decline in condition sensitivity in scenarios explored.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.