Find research datasets worth reusing

List of all proteins and chemicals mentioned in COVID-19 clinical trials

A record of all COVID-19 related clinical trials is provided in the database hosted at https://ClinicalTrials.gov. This is an important resource that tracks worldwide research efforts directed towards improvements in treating the pandemic. To help unlock the insights buried in this database, in this work we have created an automated text mining pipeline that dynamically tags chemical, protein, and gene names in all COVID-19 related database entries, as the database is updated. We plan to publish further details in a subsequent publication.

The knowledge, attitudes and perceptions towards the Covid-19 vaccine among dental staff at the University of the Western Cape, South Africa

Background: Despite the well-known increased risk of exposure to the Covid-19 virus in a dental setting, vaccination rates among staff members are low. This study was aimed at understanding the knowledge, attitudes and perceptions of staff towards the Covid-19 vaccine. This information, as well as the possible associations to demographic profiles, are necessary for authorities to adequately address specific concerns and uncertainties; (2) Methods: A descriptive cross-sectional study was conducted by means of an anonymous, online, validated questionnaire.; (3) Results: 105 staff members participated. Majority of staff have received the Covid-19 vaccine but stated that they would not take the booster vaccination. Significant associations between the level of education and the knowledge, attitudes and perceptions of staff were found.; (4) Conclusions: Majority of the staff members had a positive attitude towards the Covid-19 vaccine. However, specific concerns and uncertainties were identified and will need to be addressed in order to improve vaccination rates among staff members.

Brazilian COVID-19 data (08-11-2021)

Data from SIVEP-Gripe (Sistema de Informação de Vigilância Epidemiológica da Gripe—Flu Epidemiological Surveillance System), a system for recording cases of SARS in Brazil, including data from COVID-19, maintained by the Ministry of Health (https://opendatasus.saude.gov.br/dataset/bd-srag-2021)

opencc-by-4.0Sep 2021View details →

Viral Communication: Longitudinal Survey Data on the Social Dimensions of the COVID-19 Pandemic

This dataset represents the anonymised data collected as part of the Viral Communication (Understand-ELSED) project, which focussed on the social and ethical dimensions of the COVID-19 pandemic in Germany. It includes the three measurements; Phase I (30 October 2020 and 14 December 2020), Phase II (2 March 2021 and 22 March 2021) and Phase III. The first phase built the foundation for the wider suite of data collection approaches and research methods used in the Viral Communication project by allowing respondents to opt-in to multiple research pathways. Overall sample frame (Phase I): N = 1480 Phase II sample frame: N = 482 Phase III sample frame: N = 426 Computed variables such as weights, groupings (experimental set-ups), and composite scores are included in the dataset.

openother-pdDec 2021View details →

Portugues Twitter Covid-19 - mar/2020 & mar/2021

Este é um dataset de tuítes únicos em português relacionados à COVID-19. Os tuítes compartilhados aqui possuem apenas o ID, devido aos termos e condições do Twitter para redistribuir dados do Twitter APENAS para propósito de pesquisa. Eles precisam ser hidratados para ser usados. Os conjuntos de dados contém tuítes dos meses de março de 2020 e 2021. Após a hidratação, serão 936.866 tuítes de mar/2020 e 599.638 tuítes de mar/ 2021. Este conjunto é um subproduto do trabalho de Banda et al. (2021). Link: https://zenodo.org/record/4603998#.YbkUIb3MJPa -------------- This is a dataset with portuguese unique tweets related to COVID-19. Tweets shared here only have the ID, due to Twitter's terms and conditions to redistribute Twitter data for research purposes ONLY. They need to be hydrated to be used. The datasets contain tweets for the months of March 2020 and 2021. After hydration, there will be 936,866 tweets from Mar/2020 and 599,638 tweets from Mar/2021. This dataset is a by-product of the work by Banda et al. (2021). Link: https://zenodo.org/record/4603998#.YbkUIb3MJPa

Use of outdoor spaces during COVID-19 in Copenhagen

This dataset was collected during the first phase of Covid19 lockdown in Copenhagen, Denmark. The target was 5/10 districts in the municipality of Copenhagen (the urban core of the capital region). Respondents were recruited through the five districts volunteer citizen panels by use of the PPGIS platform Maptionnaire. The data includes responses from 4339 valid respondents who mapped 7276 visitation points. Respondents were asked to map outdoor spaces used regularly.

Supplementary Data for "Sequencing the Pandemic: Rapid and High-Throughput Processing and Analysis of COVID-19 Clinical Samples for 21st Century Public Health"

Supplementary material for F1000 methods manuscript. Includes raw sequencing metrics for two COVID sequencing methodologies, as well as a complete cost breakdown for each methodology.

Dataset: Interleukin (IL)-1 blocking agents for the treatment of COVID-19 A living systematic review

This dataset is used in the analyses reported in the review entitled "Interleukin (IL)-1 blocking agents for the treatment of COVID-19 A living systematic review" IL-1 blockers are beneficial in inflammation-associated pathologies, such as rheumatoid arthritis (Mertens 2009) and possibly also in the subgroup of patients with severe sepsis where the inflammasome pathway is involved (Shakoory 2016). Similar benefits were reported in children with secondary macrophage activation syndrome, including cases triggered by viral infections (Mehta 2020b). In this review we aimed to assess the effectiveness of IL-1 blocking agents compared to placebo, standard of care or no treatment on outcomes in patients with COVID-19. This review is part of a larger project: the COVID-NMA project. We set-up a platform (<a href="https://covid-nma.com/">https://covid-nma.com</a>) where all our results are made available and updated bi-weekly.

FaCov Dataset: COVID-19 Viral News and Rumors Fact-Check Articles Dataset

The data were collected by web-scraping pages from the websites collected earlier, using the <a href="https://webscraper.io/">Web Scraper browser extension</a>. More specifically, the sections of these websites that dealt exclusively with COVID-19 related content were scraped. In cases where the website did not have such a specified section, the search functionality within the website was used to query terms related to COVID-19 and the articles in the search results were scraped. Also in some cases, all articles were scraped and those unrelated to COVID-19 were filtered out in the pre-processing stage. All the samples collected were then put together into one CSV The following information was extracted along with the articles: Title of the fact check article URL of the fact check article Claim being discussed in the article (if available) Summary of the fact check article (if available) Content of the fact check article• Label assigned by the article to the claim Author of the fact check article (if available) Date of publication of the article (if available)

covid-19 news stories China, South Korea and the U.S.

This dataset is news stories on the COVID-19 pandemic published by national news agencies in China, Korea, and the U.S. The news stories were collected on Factiva by keyword searching, published within a one-month time frame after a national break in each country.

opencc-by-4.0Sep 2021View details →

Datasets for "Effects of the COVID-19 Pandemic on Authors and Reviewers of American Geophysical Union Journals"

These files include summary data on demographics of people submitting journal articles and reviewing manuscripts submitted to American Geophysical Union (AGU) journals. The date range is January 2018 through February 2021, divided by two years before the pandemic and during the pandemic ("year grouping"): March 2018- February 2019; March 2019- February 2020, and March 2020- February 2021 ("year of the COVID-19 pandemic"). Author-related files only include demographics of the submitting, or "corresponding" author. These datasets supplement the under-review manuscript and pre-print submission to ESSOAr (Earth and Space Science Open Archive) "Effects of the COVID-19 Pandemic on Authors and Reviewers of American Geophysical Union Journals."

Dataset from "Merging Digital Humanities and Discourse Analysis in the Study of COVID-19 Vaccine Distribution in Norwegian Newspapers" (Sverdljuk et al. 2022)

Contains URNs (identifiers) for the newspapers used in the corpus study "Merging Digital Humanities and Discourse Analysis in the Study of COVID-19 Vaccine Distribution in Norwegian Newspapers". For each subcorpus there is an Excel file containing references to the objects used, together with basic metadata. The corpus definitions can be used in various webapps of the DH-LAB at the National Library of Norway, e.g.: <a href="https://beta.nb.no/dhlab/concordances/">https://beta.nb.no/dhlab/concordances/</a> <a href="https://beta.nb.no/dhlab/collocations/">https://beta.nb.no/dhlab/collocations/</a> See more at <a href="https://www.nb.no/dh-lab/">https://www.nb.no/dh-lab/</a>

Audio recordings of COVID-19 positive individuals from the prospective Predi-COVID cohort study with their fatigue status

We uploaded 3544 audio recordings originating from 296 distinct participants with COVID-19 in the prospective Predi-COVID cohort study recruited between May 2020 and May 2021. The audios have been converted from their original format into WAV files and normalized. The audio name structure integrates the participant ID, the recording date and time of the audio recording, the type of audio (Type 1: text reading, Type2: holding the [a] vowel without breathing), the original audio format, the gender (W: women, M: Men), and the fatigue status of the participant (1: Fatigue, 0: No fatigue) as such: Predi-COVID_{participant ID}{recording date and time}{type of audio}{original format}{gender}{fatigue status}.wav

opencc-by-4.0Nov 2021View details →

An epidemiological Study to Assess Household Transmission & Associated Risk Factors for COVID-19 Disease amongst Residents of Delhi, India.

Executive summary: Studying the spread and epidemiological characteristics of COVID-19 virus specially in household settings are needed to prepare our self-better in preventing and controlling this epidemic. In this study we proposed a conceptual framework of four level of determinates and tried to understand the transmission dynamics of COVID-19 among household contacts along with clinical, epidemiological and virologic characteristics of the infection.  Aims & Objectives: <ol> <li>the proportion of asymptomatic cases and symptomatic cases;</li> <li>the incubation period of COVID-19 and the duration of infectiousness and of detectable shedding;</li> <li>the serial interval of COVID-19 infection; </li> <li>clinical risk factors for COVID-19, and the clinical course and severity of disease; </li> <li>high-risk population subgroups;</li> <li>the secondary infection rate and secondary clinical attack rate of COVID-19 infection among household contacts; and</li> <li>the associations of various factors across four dimensions interaction associated with risk of transmission</li> </ol> Methodology: This was a case-ascertained study where all susceptible contacts of a laboratory confirmed COVID-19 case were studied prospective for four weeks after their enrolment. It was done in New Delhi, during the end of first wave as well as whole second wave from December 2020 to July 2021. The study team collected the key information by questionnaire along with blood and oro-nasal swab during the household visits. Follow-up was done on day 7, 14 and 28 for observing the disease characteristic and symptomatology along with confirmation by serum and oro-nasal swab testing. Daily characteristics of the infection were noted by the participants on symptoms diary. Results: We enrolled 99 households, each having one laboratory-confirmed COVID-19 index case along with their 318 susceptible contacts. By the end of the follow-up, secondary infection rate was seen at 55.5%, while seroconversion in 46.6%.  Hospitalization and case fatality rate was 3.83% and 1.7% respectively. Among epidemiological characteristics we observed serial interval of 8.0 ± 6.7 days, generation time 3.8  ± 6.4, while secondary attack rate was 54.9%. The predictors of secondary infection among individual contact level were being female (OR:2.13, 95% CI:1.27 - 3.57), age of the household contact (1.01;1.00 - 1.03), symptoms at baseline (3.39; 1.61- 7.12) and during follow-up (3.18; 1.64 - 6.19), while only symptoms during follow-up (3.81: 1.43 - 10.14) and being RT-PCR positive (8.32; 3.22 -21.54) was significantly and independently associated with seroconversion among household contacts. Among index case-level age of the primary case (1.03; 1.01 -1.04) and any symptoms during follow-up (6.29; 1.83-21.63) significantly and independently associated with secondary infection while any symptoms during follow-up was associated with seroconversion among household contacts. Among household-level characteristics having more rooms (4.44; 2.16 - 9.13) independently associated with secondary infection, while more rooms (3.98; 1.23 -12.90) along with overcrowding (0.37; 0.16 - 0.82) associated with seroconversion. Among contact pattern only taking care of the index case (2.02;1.21- 3.38) was significantly and independently associated with secondary infection, while none was associated with seroconversion. Conclusion: A high secondary cases and secondary attack rate was seen in our study. This highlights the need to adopts strict measure and advocate COVID appropriate behaviours in order to break the transmission chain at household level. The targeted approach at household contacts with higher risk would be efficient in limiting the development of infection among susceptible contacts.

Reliability of citations of medRxiv preprints in articles published on COVID-19 in the world leading medical journals

Articles published on COVID in 2020 in the BMJ, The Lancet, the JAMA and the NEJM were manually screened to identify all articles citing at least one preprint from medRxiv. We searched PubMed, Google and Google Scholar to assess if the preprint had been published in a peer-reviewed journal, and when. Published articles were screened to assess if the title, data or conclusions were identical to the preprint version.

Dataset - The cGAS-STING pathway drives type I IFN immunopathology in COVID-19

Dataset corresponding to the LoC studies in the manuscript titled The cGAS-STING pathway drives type I IFN immunopathology in COVID-19. The following data are included: BioEM.zip: Volumetric electron microscopy - representative movies of volumetric scans of fields of view of the vascular face of uninfected control and SARS-CoV-2 infected LoCs. Blender file containing reconstruction of mitochondria. Cleaved-caspase3.zip: Imaris files for analysis of 3D stacks from two- and three-component LoCs immunostained for cleaved-caspase 3. IFN beta.zip: Imaris files for analysis of 3D stacks from two- and three-component LoCs immunostained for IFN beta. PhosphoSTING.zip: Imaris files for analysis of 3D stacks from two component LoCs immunostained for phosphoSTING. Proteomics_R_code.Rmd: Annotated custom scripts in R for the analysis of the proteomics data.

Entrepreneurial Leadership toward Global Management of COVID-19, Is it always being used during Pandemic? A Bibliometric Study

Entrepreneurial Leadership toward Global Management of COVID-19, Is it always being used during Pandemic? A Bibliometric Study entitled manuscript all of the metadata had taken from Scopus.

Response to COVID-19: Clients' perspectives on the utilization of reproductive, maternal and child health care services in Nigeria

This dataset was a part of a cross-sectional descriptive study in 320 rural communities in 32 Local Government Areas (LGAs) across the Federal Capital Territory (FCT), Abuja, and 9 out of the 36 Nigerian States in 2020. The dataset contains views of women who used primary health care centres in the selected LGAs for maternal and child health care, and family planning services before, during, and after the COVID-19 pandemic lockdown in Nigeria. The sample size was determined using the Yamane sample size formula. The estimated sample size per State was 384 (3,840 for nine States and FCT), with a 10% adjustment for non-response, the total sample size was 422 per State or location (4220 for the nine States and FCT). The data are stored in SPSS format.  The study was an initiative of UNFPA Nigeria. They coordinated it under the One UN Basket fund to respond to COVID-19 and implemented it under the supervision of three national NGOs: The Women’s Health and Action Research Centre (WHARC), Education as a Vaccine (EVA), and the Planned Parenthood Federation of Nigeria (PPFN).

opencc-by-4.0Aug 2021View details →

Covid Data Analytics: Repositório de Dados Provenientes de Múltiplas Fontes sobre a Pandemia de COVID-19 no Brasil

Uma estratégia para melhor compreender as diversas facetas e possíveis impactos da pandemia de COVID-19 na sociedade consiste na extração de informação e conhecimento a partir de dados provenientes de diversas fontes oficiais e não oficiais. A importância desse tema fomentou a publicação de diversos artigos científicos que investigam aspectos relacionados à pandemia de COVID-19 no Brasil por meio de análises de dados. Alguns trabalhos, por exemplo, fornecem caracterizações e descrições da evolução da doença no país~\cite{ranzani2021characterisation}, considerando, inclusive, a subnotificação de casos pelas agências oficiais. Outros modelam e preveem a evolução da COVID-19, utilizando dados referentes aos primeiros meses da pandemia e empregando diferentes métodos ou mesmo utilizando dados de geolocalização e de dinâmica populacional. Nesse contexto, é importante que, sempre que possível, os dados utilizados para as pesquisas sejam disponibilizados à comunidade científica, seja para fins de  replicabilidade dos resultados encontrados, seja para a promoção de novas investigações. Os dados disponibilizados no repositório CDA  se referem ao período entre 23 de fevereiro de 2020 e 8 de maio de 2021. Esse repositório agrega 1.508 arquivos, classificados em dois tipos principais: (i) bases de dados e tabelas extraídas das fontes descritas anteriormente; e (ii) artigos, relatórios, mapas e gráficos produzidos pelos integrantes do projeto a partir da análise dos dados coletados Dados de Fontes Externas Estes arquivos representam 8\% do total de arquivos que compõem o repositório e estão distribuídos da seguinte maneira: <ul> <li>Séries temporais com indicadores econômicos das Unidades Federativas do Brasil e da União em formato .csv, com aproximadamente 18.400 registros;</li> <li>7 scripts de tratamento de dados em formato .py.</li> <li>5 arquivos com a contagem do número de tweets e retweets coletados semanalmente utilizando 13 palavras-chave (“corona”, “covid”, “coronavirus”, “covid19”, “quarentena”,“hidroxicloroquina”, “cloroquina”, “confinamento”, “distanciamento social”, “aglomeração”, “aglomerações”, “sars” e “covid-19”) formato .csv </li> <li>3 arquivos do Google Trends no formato .csv com 249 registros contendo 124 termos pré-selecionados que têm relação com a pandemia e o percentual relativo de buscas na web nos níveis regional e nacional. %\ana{de novo, o que tem nestes csvs?}.</li> <li>7 arquivos como dados anonimizados do Instagram no formato .csv com 90.787 hashtags contendo os termos \#demito, \#demitida, \#desempregada, \#desempregado, \#desemprego, \#falido, \#reduçãodejornada.</li> <li>Análises e Relatórios</li> <li>Os arquivos com as análises e relatórios representam 92\% do total de arquivos do repositório. Além de documentos de texto, também foram disponibilizados materiais visuais, como mapas e gráficos, em diversos formatos. Os arquivos estão distribuídos da seguinte maneira.</li> </ul>      <ul> <li>23 gráficos comparativos de indicadores sociais e econômicos, análises descritivas dos ocupados em atividades essenciais e não essências por regiões em formato .svg;</li> <li>409 gráficos de novos casos e óbitos (02 a 09 de setembro) em formato .png;</li> <li> 522 mapas e gráficos de linhas e barras acerca dos casos e óbitos acumulados de COVID-19 em todo o país entre as semanas epidemiológicas 9 e 32 de 2020 (23/02/2020 a 08/08/2020) em formato .png;</li> <li>15 arquivos de medidas provisórias em formato .pdf;</li> <li>1 gráfico interativo gerado a partir do cálculo da mortalidade (óbitos acumulados por 100 mil habitantes) no Brasil em formato .html;</li> <li>25 animações mostrando a evolução da letalidade (mortes acumuladas / casos acumulados) em \% em todos estados do Brasil a cada semana epidemiológica da 9ª à 31ª em formato .gif;</li> <li>1 relatório sobre análises das informações disponíveis para coleta na ferramenta Google Trends em formato .pdf;</li> <li>4 relatórios sobre análises das informações disponíveis dos grupos de pesquisa em formato .pdf;  </li> </ul> Limitações nas Bases de Dados Disponibilizadas Devido a questões de privacidade, algumas bases de dados, obtidas através da extração de informações das redes sociais online não foram integralmente disponibilizadas no repositório. Nestes casos, disponibilizamos análises extraídas a partir destas bases, realizadas com o propósito de responder algumas das perguntas de pesquisa do projeto. As análises realizadas durante o projeto estão disponíveis em  \url{https://covid.dcc.ufmg.br/}. A disponibilização dos dados ocorreu por meio do  padrão Open Data Standards e, a partir dele, foram criados e organizados os arquivos, de acordo com o respectivo formato e tipo de informação. Eles foram integrados ao drive do grupo tecnológico por intermédio de um formulário, e utilizaram-se de um script para transformar os dados do formulário em um arquivo XML. Como resultado, pôde-se modelar e preencher o banco de dados a partir do arquivo XML e, por fim, integrá-lo a um <a href="https://covid.dcc.ufmg.br/buscador.php">buscador</a> criado em Wordpress, que fica disponível para download no portal do projeto CDA maiores informações: <a href="https://covid.dcc.ufmg.br/linhas/dados">https://covid.dcc.ufmg.br/linhas/dados/ </a>