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11 results for “Wastewater-Based Epidemiology”
Dataset on drug use in 2020 (COVID-19 lockdown) in Spain and Portugal by wastewater-based epidemiology
<div><strong>This datase contains the metadata associated with this publication:</strong></div> <div> </div> <div><em>A. Estévez-Danta, L. Bijlsma, R. Capela, R. Cela, A. Celma, F. Hernández, U. Lertxundi, J. Matias, R. Montes, G. Orive, A. Prieto, M.M. Santos, R. Rodil, J.B. Quintana</em></div> <div><em>Use of illicit drugs, alcohol and tobacco in Spain and Portugal during the COVID-19 crisis in 2020 as measured by wastewater-based epidemiology</em></div> <div><em>Science of the Total Environment, 2022, 836, 155697</em></div> <div><a href="https://doi.org/10.1016/j.scitotenv.2022.155697" target="_blank" rel="noopener">https://doi.org/10.1016/j.scitotenv.2022.155697</a></div> <div> </div> <div>The data is deposited in ZENODO:</div> <div><a href="../doi/10.5281/zenodo.10829752">https://zenodo.org/doi/10.5281/zenodo.10829752</a></div> <div> </div> <div><strong>If you reuse the data, please cite the publication and ZENODO deposit mentioned above</strong></div> <div> </div> <div><strong>Explanation of the different sheets of the Excel file (All_Data_STOTEN_2022_155697) or different individual CSV files (named as below):</strong></div> <ul> <li><em>WWTP_details</em>: explanation of wastewater treatment plats (WWTPs) sampled, flow rates, etc.</li> <li><em>Concentrations</em>: concentrations measured in the samples</li> <li><em>PNDL</em>: population normalized daily loads calculated per each sample</li> <li><em>Consumption</em>: estimated drug use (see the publication for correction factors)</li> <li><em>EF</em>: enantiomeric fraction, expressed as fraction of the R-enantiomer for the samples analyzed</li> </ul> <div> </div> <div><strong>Abreviations</strong></div> <ul> <li>AMP Amphetamine</li> <li>MAMP Methamphetamine</li> <li>MDMA 3,4-Methylenedioxymethamphetamine</li> <li>BE Benzoylecgonine</li> <li>COC Cocaine</li> <li>THC-COOH 11-Nor-9-carboxy-Δ9-tetrahydrocannabinol</li> <li>THC Δ9-Tetrahydrocannabinol</li> <li>COT Cotinine</li> <li>OH-COT Trans-3'-Hydroxycotinine</li> <li>NIC Nicotine</li> <li>EtS Ethyl sulfate</li> </ul>
Dataset of concentrations of bisphenol A, F and S sulfates in wastewater from Spain and Portugal and back-calculation of human exposure by wastewater-based epidemiology
<p>Dataset of concentrations of bisphenol A, F and S sulfates in wastewater from Spain and Portugal and back-calculation of human exposure by wastewater-based epidemiology.</p> <p>Data is provided in MS Excel (xlsx) and CSV formats and contains details on WWTP characteristics, concentrations of bisphenols sulfates and extrapolated population-normalizad daily loads and different extrapolations of human exposure to bisphenols.</p> <p><strong>Further details are provided in the associated publication:</strong></p> <p><em>A. Estévez-Danta, R. Montes, A. Prieto, M.M. Santos, G. Orive, U. Lertxundi, J.B. Quintana, R. Rodil. </em><em>Wastewater-Based Epidemiology Methodology To Investigate Human Exposure To Bisphenol A, Bisphenol F and Bisphenol S.<br>Water Research 2024, 122016. DOI: 10.1016/j.watres.2024.122016.<br><a href="https://doi.org/10.1016/j.watres.2024.122016" target="_blank" rel="noopener">https://doi.org/10.1016/j.watres.2024.122016 </a><br></em></p> <div>The data is deposited in ZENODO:</div> <div><a href="../doi/10.5281/zenodo.10459047">https://zenodo.org/doi/10.5281/zenodo.10459047</a></div> <div> </div> <div><strong>If you reuse the data, please cite the publication and ZENODO deposit mentioned above</strong></div>
Toileting behaviours of the UK public: insights for reducing gender bias wastewater-based epidemiology sampling strategies
<p>Cross-sectional survey results from a toileting behaviour survey conducted between the 27th to the 28th of June 2022. Participants (<em>n</em> = 2109) were aged 18 years or older and were living in the UK. The survey consisted of 17 closed-ended questions, with 7 of the questions addressing specific demographic topics and 10 questions addressed toileting behaviour. The questionnaire was designed by a team consisting of environmental microbiologists, public health specialists, wastewater-based epidemiologists, and social scientists, based on the study objectives and incorporating information from previous studies on the same topic. First, self-report questions were asked on typical frequency of urination and defecation, followed by self-reports of frequency of urination and defecation at a variety of locations including at home, at work, educational buildings, transport hubs, and in public toilets. The comfort in urination/defecation at these locations for defecation and urination was also measured. Other questions about toileting behaviour and health monitoring were measured by statements with a 5-point Likert scale (e.g., strongly disagree to strongly agree). </p>
Data from: Priority setting for global WASH challenges in the age of wastewater-based epidemiological surveillance
<p>Background: It is not known how the number of deaths due to COVID-19 compare to the number of deaths due to "unsafe water, sanitation, and handwashing" during the COVID-19 global health emergency.</p> <p>Methods: A dataset of deaths due to COVID-19 was downloaded from the World Health Organization. A dataset summarizing deaths due to unsafe water, sanitation, and handwashing was obtained from the Institute for Health Metrics and Evaluation (IHME). </p> <p>Results indicate that COVID-19 deaths in Africa and South East Asia regions exceeded those due to unsafe water, sanitation, and hygiene. </p>
Data from: Priority setting for global WASH challenges in the age of wastewater-based epidemiological surveillance
Open the record for dataset details and reuse information.
Improving inference in wastewater-based epidemiology by modelling the statistical features of digital PCR
<p>This repository contains the simulation code, data, and analysis scripts of the study "Improving inference in wastewater-based epidemiology by modelling the statistical features of digital PCR". The code can be used to reproduce all figures and numerical results in the paper.</p>
Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals (II)
<p>Metagenomic analysis of viruses in wastewater from sewers representing different age group populations</p>
Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals (V)
<p>Metagenomic analysis of viruses in wastewater from sewers representing different age group populations</p>
Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals (IV)
<p>Metagenomic analysis of viruses in wastewater from sewers representing different age group populations</p>
Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals (III)
<p>Metagenomic analysis of viruses in wastewater from sewers representing different age group populations</p>
Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals (I)
<p>Metagenomic analysis of viruses in wastewater from sewers representing different age group populations</p>
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International Brain Laboratory public data
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OpenNeuro
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