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9,674 results for “COVID-19”
Coronavirus Twitter Data: A collection of COVID-19 tweets with automated annotations
<p>This dataset contains tweets related to COVID-19. The dataset contains Twitter ids, from which you can download the original data directly from Twitter. Additionally, we include the date, keywords related to COVID-19 and the inferred geolocation. Check detailed information at <a href="http://twitterdata.covid19dataresources.org/index">http://twitterdata.covid19dataresources.org/index</a>.</p>
Water pollution in Höfen and COVID-19 cases in Austria
<p>Dataset used for the project "Analysis of correlation between water pollution in Höfen and Covid-19 cases in Austria, 2020"</p>
Analysis of correlation between water pollution in Höfen and Covid-19 cases in Austria, in 2020 dataset
<p>Dataset about water pollution in Höfen and COVID-19 cases in Austria, in 2020. The measured water pollution corresponds to the daily COVID-19 cases and deaths.</p>
Consensus recommendations for opioid agonist treatment following the introduction of emergency clinical guidelines in Ireland during the COVID-19 pandemic: A national Delphi study
<p>Anonymous Delphi survey likert scale responses (round 1 (S1-S32) and 2 (R2S1-R2S15)) <a href="https://zenodo.org/api/files/92371fe3-6af6-4044-ba3f-83a26b2fe471/Delphi_likert_responses_ano.csv?versionId=7c3aaa7b-8b43-43da-bfeb-fe644f33d3e2">Delphi_likert_responses_ano.csv</a> and corresponding statements in <a href="https://zenodo.org/api/files/92371fe3-6af6-4044-ba3f-83a26b2fe471/STATEMENTS_REPO.csv?versionId=ada85e7c-ba48-4f61-8e1a-d90dab9b4f05">STATEMENTS_REPO.csv</a>.</p>
Open microdata registers from the Brazilian COVID-19 vaccination campaign
<p>This repository provides the Brazilian Ministry of Health’s (MoH) open microdata registers from the national COVID-19 vaccination campaign used in the paper <em>Age reporting for the oldest old in the Brazilian COVID-19 vaccination database: what can we learn from it?</em></p> <p>The dataset was downloaded on 14 March 2022 and was initially available at openDataSus <a href="https://opendatasus.saude.gov.br/dataset/covid-19-vacinacao">Campanha Nacional de Vacinação contra Covid-19</a> under a <a href="http://creativecommons.org/licenses/by/4.0/?ref=chooser-v1">CC BY 4.0</a> license.</p> <p>The reproducible <em><code>R</code></em> code and other datasets for the paper are available on GitHub at <a href="https://github.com/demographyandme/covid-19-datasus-vacina">Age reporting for the oldest old in the Brazilian COVID-19 vaccination database: what can we learn from it?</a> </p>
Database of COVID-19 Seroprevalence in Oran, Algeria - January 2021
<p>This is a database related to the seroprevalence survey conducted in Oran, Algeria during the month of January in the year 2021, just before the commencement of the anti-COVID-19 vaccination.</p>
Regra de três: teorias da conspiração sobre Covid-19 no YouTube
<p>Material suplementar do artigo "Regra de três: teorias da conspiração sobre Covid-19 no YouTube"</p>
Behavioral responses of terrestrial mammals to COVID-19 lockdowns
<p>COVID-19 lockdowns in early 2020 reduced human mobility, <span>providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable, with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns, 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12%, and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.</span></p>
EDN IITC et l'IRPF du ΔNO2 (Fig. 5a). Relation entre EDNP IITC et IRPF_ΔNO2 dans les départements du Grand Est pendant trois périodes de confinement induites par le COVID-19 (Fig. 5b)
<p>Il s'agit de la figure 5 (Fig. 5), qui se réfère au chapitre 4 de l'ouvrage intitulé «L'effet positif des mesures anti-COVID-19 sur la qualité de l'air, en particulier sur le NO2. Nouvelles méthodes d'estimation quantitative appliquées à la région Grand Est».</p> <p>Source des données utilisées pour l'estimation de la densité de noyau (EDN) de l'intensité des infrastructures de transport et de circulation (IITC) : OpenStreetMap (OSM).</p>
Comparison of children's physical activity profiles before and after COVID-19 lockdowns - dataset
<p>This dataset represents a subset of the Active-6 data used to produce the children's activity profiles reported in the manuscript 'Comparison of children's physical activity profiles before and after COVID-19 lockdowns: a latent profile analysis'. Included in this repository is the dataset and a data dictionary.</p> <p>This dataset has been made available so that future researchers can replicate the study findings using the data. If you wish to use the data for any purpose other than replicating the study findings, please contact the Principal Investigator Professor Russ Jago (russ.jago@bristol.ac.uk) to discuss this.</p>
COVID-19 Misinformation Dataset
<p>The dataset and the annotation codebook from "Categorising Fine-to-Coarse Grained Misinformation: An Empirical Study of the COVID-19 Infodemic" (accepted at RANLP 2023)</p>
Data used in the study "mRNA vaccination boosts spike-specific T cell memory and promotes expansion of CD45RAint TEMRA-like CD8+ T cells in COVID-19 recovered individuals"
<p>Data associated with an original research study examining T cell responses to mRNA vaccination in COVID-19 recovered individuals. 10X Cell Ranger outputs, bulk TCR sequencing data, and T cell functional (ICS) data in this study have been deposited. Authors KMB and HR contributed equally to this effort. Address correspondence to EWN.</p>
COVID-19 medical image datasets
<p>This repository contains three curated datasets for the medical image classification described in the paper entitled "Explainable deep transfer learning fine-tunning with domain adaptation enables trustworthy COVID-19 prediction".</p>
Spatiotemporal impacts of ideology and social vulnerability on COVID-19 for the United States
<p><span>In early 2020, the Coronavirus Disease 19 (COVID-19) rapidly spread across the United States, exhibiting significant geographic </span><span>variability. While several studies have examined the predictive relationships of differing factors on COVID-19 deaths, few have </span><span>looked at spatiotemporal variation at refined geographic scales. The objective of this analysis is to examine county-level </span><span>spatiotemporal variation of COVID-19 deaths in association with socioeconomic, health, demographic, and political factors, </span><span>using regionalized multivariate regression as well as nationwide geographically weighted random forest (GWRF) models. </span><span>Regionalized regression results across three time windows—pandemic onset until May 2021, May 2021 through November </span><span>2021, and December 2021 until April 2022—suggest that existing measures of social vulnerability for disaster preparedness </span><span>(SVI) are associated with a higher degree of mortality from COVID-19. In comparison, GWRF models provide a more robust </span><span>evaluation of feature importance and prediction, exposing the importance of local features, such as obesity, which is obscured </span><span>by regional delineation. Overall, GWRF results indicate this more nuanced modeling strategy is useful for capturing the diverse </span><span>spatial and temporal nature of the COVID-19 pandemic.</span></p>
Covid-19 UK government, winter 2020, Tiered restrictions data
<p>During the COVID-19 pandemic, several countries took the approach of tiered restrictions. The UK Government’s Winter 2020 Plan looked to take a data driven approach to decision making. They proposed a set of factors (criteria) that would be used to determine what level of restrictions of movement (Tier) should be imposed on different geographical areas in England. Restrictions were tiered from Tier-1 to Tier-4, with Tier-1 being the most relaxed set of restrictions and Tier-4 representing the most constrained level of restrictions. The set of criteria, to determine which Tier from 1 to 4 an area should be placed in were, (1) case detection rate in all age groups, (2) case detection in people aged 60 or above, (3) how quickly case rates were rising or falling, (4) ratio of positive cases in the general population, (5) pressure on the healthcare service. England is geographically made up of 9 Regions which each contains a set of Lower Tier Local Authority (LTLA) areas. Each observation in the dataset denotes information for an LTLA and date pair. For each observation, there is data relating to the values of the set of 5 criteria, for that LTLA, on that day, along with the accompanying Tier value the LTLA was in on that day. Data relating to the set of 5 criteria represent 7-day rolling averages, as a common practice, to alleviate discrepancies in the reporting velocity at different days of the week. For example, it is the case that the number of reported cases around weekends were invariably lower than the cases on other days.</p>
Classifying COVID-19 vaccine narratives
<p>We release the augmented Twitter dataset of 355 vaccine-related narratives, created for the following paper. The tweets are labelled as one of four classes: <em>Conspiracy (Cons), Moral, Religious, and Ethical Concerns (MRE), Liberties and Freedom (LF), and Animal Vaccines (AnimalVac)</em>.</p> <pre>@article{li2022classifying, title={Classifying COVID-19 vaccine narratives}, author={Li, Yue and Scarton, Carolina and Song, Xingyi and Bontcheva, Kalina}, journal={arXiv preprint arXiv:2207.08522}, year={2022} }</pre> <p>The paper has been accepted by RANLP 2023.</p> <p> </p> <p> </p>
Global health science leverages established collaboration network to fight COVID-19
<p>Compressed file containing the data for the <a href="https://arxiv.org/abs/2102.00298">Global health science leverages established collaboration network to fight COVID-19</a> paper.</p> <p>For simplicity of use you can find pubmed__2019_cleaned.rar at https://zenodo.org/record/5011448#.Ykb2PDU68mA which contains the cleaned data used for the analysis. However we do not own the data and The following 6 data sources have been used.</p> <p><br> 1. Publication data</p> <p>source: PubMed API (download 26.06.2023).</p> <p>Output: country_pub_info.csv and edge_list.csv</p> <p><br> 2. Covid cases (download 26.06.2023)</p> <p>file: owid-covid-data.csv</p> <p>website: https://github.com/owid/covid-19-data/tree/master/public/data</p> <p>original source (for some variables): COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University</p> <p><br> 3. Covid policy restrictions (last download 21.06.2021)</p> <p>website: https://ourworldindata.org/policy-responses-covid</p> <p>data file: OxCGRT_latest.csv</p> <p>Oxford Covid-19 Government Response Tracker</p> <p><br> cit: Thomas Hale, Noam Angrist, Rafael Goldszmidt, Beatriz Kira, Anna Petherick, Toby Phillips, Samuel Webster, Emily Cameron-Blake, Laura Hallas, Saptarshi Majumdar, and Helen Tatlow. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker).” Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01079-8</p> <p> </p> <p>4. Economic wealth</p> <p>Penn World Table version 10.0</p> <p>cit: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt</p> <p><br> 5. Economic/social development</p> <p>Human Development Index (HDI) from http://hdr.undp.org/en/content/download-data</p> <p> </p>
Replication Package of Pandemic Pedagogy: Evaluating Remote Education Strategies during COVID-19
<p>The COVID-19 pandemic precipitated an abrupt shift in the educational landscape, compelling universities to transition from in-person to online instruction. This sudden shift left many university instructors grappling with the intricacies of remote teaching. Now, with the pandemic behind us, we present a retrospective study aimed at understanding and evaluating the remote teaching practices employed during that period. Drawing from a cross-sectional analysis of 300 computer science students who underwent a full year of online education during the lockdown, our findings indicate that while remote teaching practices moderately influenced students' learning outcomes, they had a pronounced positive impact on student satisfaction. Remarkably, these outcomes were consistent across various demographics, including country, gender, and educational level. As we reflect on the lessons from this global event, this research offers evidence-based recommendations that could inform educational strategies in unwelcoming future scenarios of a similar nature, ensuring both student satisfaction and effective learning outcomes in online settings.</p>
RESISTIRÉ Dataset: Narratives on inequalities caused by policy and societal responses to Covid-19 in Europe – second cycle
<p>This dataset contains 295 narratives, including keywords and specifically telling quotes. It is the second of three sets of narratives collected and analysed in RESISTIRÉ. The narrative interviews were conducted in national languages by the consortium partners and a network of national researchers covering the EU27 (except Malta), and Iceland, Serbia, and the UK in December 2021-February 2022. Narrative interviewing is a qualitative research method that involves inviting participants to tell their own stories and experiences in their own words. The technique is used to collect and share a person’s story which entails both a research methodology and a mechanism for storytelling i.e. both a way of telling a story, and a way of knowing. Narratives as a technique can make visible how multiple sources of inequalities intersect, as well as the situational and contextual nature of inequalities from a single person’s perspective. </p>
Factors Driving Vaccine Hesitancy rrelated to vaccination of children with Covid-19 vaccine among Albanian parents
<p>A validated questionnaire composed of 33 elements was used for the purpose of this study</p> <p>The subjects of this study were parents of children aged 0-18 years old .</p> <p>Inclusion criteria were:albanian parents who understood and spoke well albanian, parents of children aged 0-18 years old, parents aged 18 years old and over. Exclusion criteria were: parents aged less than 18 years old, albanian parents who didn’t understand well albanian language, parents of children aged more than 18 years old.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.