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1,173 results for “Pandemic”

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zenodo44/100

The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - B. Data for 2020 - 2026 - Covid scenario

opencc-by-4.0Nov 2021View details →

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The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - A. Code and data for 2016-2019

The SPIN covid19 RMRIO dataset is a time series of MRIO tables covering years from 2016-2026 on a yearly basis. The dataset covers 163 sectors in 155 countries. This repository includes data for years from 2016 to 2019 (hist scenario) and the corresponding labels. Data for years 2020 to 2026 are stored in the corresponding repositories: <ul> <li>covid: <a href="https://doi.org/10.5281/zenodo.5713825">10.5281/zenodo.5713825</a></li> <li>counterfactual: <a href="https://doi.org/10.5281/zenodo.5713839">10.5281/zenodo.5713839</a></li> </ul> Tables are generated using the <a href="https://github.com/TBeaufils/SPIN">SPIN method</a>, based on the <a href="https://doi.org/10.5281/ZENODO.3993659">RMRIO tables</a> for the year 2015, GDP, imports and exports data from the <a href="https://data.imf.org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b">International Financial Statistics</a> (IFS) and the World Economic Outlooks (WEO) of <a href="https://www.imf.org/en/Publications/WEO/weo-database/2019/October">October 2019</a> and <a href="https://www.imf.org/en/Publications/WEO/weo-database/2021/April">April 2021</a>. From 2020 to 2026, the dataset includes two diverging scenarios. The covid scenario is in line with April 2021 WEO's data and includes the macroeconomic effects of Covid 19. The counterfactual scenario is in line with October 2019 WEO's data and simulates the global economy without Covid 19. Tables from 2016 to 2019 are labelled as hist. The Projections folder includes the generated tables for years from 2016 to 2019 (hist scenario) and the corresponding labels. The Sources folder contains the data records from the IFS and WEO databases. The Method data contains the data files used to generate the tables with the SPIN method and the following Python scripts: <ul> <li>SPIN_covid19_MRIO_files_preparation.py generates the data files from the source data.</li> <li>SPIN_covid19_RMRIO runs.py is the command to run the SPIN method and generate the dataset.</li> <li>figures.py is a script to produce figures reflecting the consistency of the projected tables and the evolution of macroeconomic figures in the 2016-2026 period for a selection of countries.</li> </ul> All tables are labelled in 2015 US$ and valued in basic prices.

opencc-by-4.0Nov 2021View details →

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The SPIN covid19 RMRIO dataset: Global trade network data for the years 2016-2026 reflecting macroeconomic effects of the covid19 pandemic - C. Data for 2020 - 2026 - Counterfactual scenario

opencc-by-4.0Nov 2021View details →

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Effect of the Increased Nursing Attrition Rate on Nursing Administration Process during the Covid-19 Pandemic in a Selected Tertiary Care Hospital

During the COVID-19 outbreak, healthcare professionals, particularly nurses, were more prone to diseases. Globally attrition rate was high among nurses and during the pandemic, it increased because of various reasons such as the risk of infection, occupational and psychological stress, causing risk to their loved ones. This led to a chaotic situation where nurse managers were forced to implement specific strategic plans to deal with increased nurse attrition. This study aims to describe the impact of nurse attrition rate on nursing administration during COVID-19 at a selected tertiary care hospital. The research approach adopted in this study is descriptive cross-sectional. A total sample of 66 nurses involved in nursing administration. The data is collected through a structured questionnaire and the nurse attrition data during the COVID-19 pandemic period was collected from the interview method during the survey. Statistical tests used were frequency, percentage, mean, Standard Deviation (S.D). The study showed that there is a moderate impact of increased nurse attrition on nursing administration during the COVID-19 pandemic. The study led to the identification of gaps that need to be addressed in a similar crisis.

opencc-by-4.0Aug 2024View details →

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Short-lived air pollutants and climate forcers through the lens of the COVID-19 pandemic

The data in this repository is part of the paper titled "Short-lived air pollutants and climate forcers through the lens of the COVID-19 pandemic". The data is required to obtain a detrended lockdown effects on air quality. The raw data was downloaded from the European Centre for Medium-Range Weather Forecasts Atmospheric Composition Reanalysis 4 (EAC4) product portal. More details of the data are listed below: "ozone_data.nc": Global mixing ratio of ozone (monthly) "pm_data.nc":  Global mass concentration of fine particulate matters, and aerosol optical depth (AOD) at 550 nm (monthly) "BAU_clean_latest.csv": The pollution level under a business-as-usual (BAU) scenario, inferred from the historical pollution data by Theil-Sen linear regression (monthly)

opencc-by-4.0Oct 2024View details →

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Monitoring knowledge, risk perceptions, preventive behaviours and trust to inform pandemic outbreak response.

The study is part of the large project promoted by WHO Regional Office for Europe called “Monitoring knowledge, risk perceptions, preventive behaviours and trust to inform pandemic outbreak response” and carried out in over 30 countries of the WHO European Region (Registered ISRCTN on 11/05/2021, ID: ISRCTN26200758). In Italy, the survey was conducted administering an online questionnaire developed ad hoc by the WHO in four waves (January-May 2021) to a sample of 10.000 individuals aged 18-70 years. A detailed sampling plan was developed to obtain a representative sample of the Italian adult population. The following variables were taken into account for stratification of the participants: gender by age (four age groups: 18-34 years, 35-44 years, 45-54 years, 55-70 years); geographical area (four areas: North West, North East, Centre, South and Islands); size of living centers (two classes: above and below 100,000 inhabitants); level of education (up to lower middle school, beyond lower middle school); and employment situation (employed, not employed). At the end of each survey’s wave, a weighting procedure has been applied to accurately restore the proportionality of the total sample examined with the reference population, according to the most recent data of the Italian Statistics Institute (ISTAT, 12/31/2019). In particular, data have been weighted for the main socio-demographic and geographic variables (e.g., sex by age by geographical area, occupation, educational qualification, geographical area by size of living centers). The sample size made it possible to maintain a sampling error of less than 2% (at the significance level of 95%) and to control the error of estimates within groups or subgroups of interest. The interviews were conducted by Doxa S.p.a. and carried out with the CAWI technique (Computer Assisted Web Interviewing) on an online panel and on the Confirmit software platform used by Doxa S.p.a. The average administration time was about 18-20 minutes. This study was approved by the Ethics Committee of the IRCCS San John of God Fatebenefratelli of Brescia (n° 72-2020), and all participants provided written informed consent. The primary objectives are to: ● Monitor variables that are critical for population behaviour to control transmission of the novel coronavirus, including risk perceptions, knowledge, self-efficacy, confidence in institutions, behaviours, rumours, affect, worry, resilience, trust in/use of information sources and more. ● Document changes over time in these factors to understand the effect of the pandemic process, new developments, events or measures taken. ● Monitor possible issues, e.g. related to misinformation or distrust, as they emerge, to allow early response. ● Identify relationships between variables to identify levers for effective and appropriate responses. ● Explore the relationship of psychological variables (e.g. worry, resilience, trust, affect) with the epidemiological situation and the events and measures taken. ● Identify gaps between perceived and actual knowledge. ● Evaluate the effectiveness of pandemic response measures, and the acceptance and effectiveness of policies and restrictions implemented, including the easing of such restrictions. The secondary objectives are to: ● Contribute to post-outbreak evaluation, thereby contributing to the continued regional/global efforts to better understand mechanisms of crisis response. ● If additional research capacity is available, the data can be triangulated with data on media reporting, COVID-19 cases and other.● If additional research capacity is available, the data can be triangulated with data on media reporting, imported or confirmed cases, etc.: The relationship between psychological variables and characteristics of the outbreak situation can be explored (i.e. how closely the perceived risk mirrors reported cases, relative import risk, media reports). This approach allows a citizen-centred approach where insights into population perceptions and behaviours inform COVID-19 actions, alongside epidemiological data and considerations of economic, cultural, ethical, structural political nature and other. The WHO questionnaire includes 21 different thematic areas noteworthy for the investigation of COVID-19 experience. The questionnaire was translated into specific country language by each recruiting site, following the WHO’s guidelines for translations of tools into other languages. The process included the following steps: forward translation, panel experts, back-translation, pre-test and cognitive interviews and, finally, development of the final version. Variables being surveyed include the following: • Socio-demography; • COVID-19 personal experience; • Health literacy; • COVID-19 risk perception; • Probability and Severity; • Preparedness and Perceived self-efficacy; • Prevention – own behaviours; • Affect; • Trust in sources of information; • Use of sources of information; • Frequency of Information; • Trust in institutions (perceptions); • Policies, interventions (perceptions); • Conspiracies (perceptions); • Resilience (perceptions); • Testing and tracing; • Fairness (perceptions); • Lifting restrictions (pandemic transition phase); • Unwanted behaviour; • Wellbeing; • COVID-19 vaccine.

opencc-by-4.0Dec 2020View details →

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Model-driven mitigation measures for reopening schools during the COVID-19 pandemic.

Complete simulation-generated datasets analyzed in McGee et al. (2021) Model-driven mitigation measures for reopening schools during the COVID-19 pandemic. PNAS. In press at time of upload. (medRxiv 2021.01.22.21250282). Data is uploaded in tab-separated .csv files which have been compressed using gzip. Descriptions of data columns can be found in the column_descriptions.csv file.

opencc-by-4.0Aug 2021View details →

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Extended data for "TeenCovidLife: A resource to understand the impact of the Covid-19 pandemic on adolescents in Scotland"

Extended data for "TeenCovidLife:  A resource to understand the impact of the Covid-19 pandemic on adolescents in Scotland" Wellcome Open Research submission

opencc-by-4.0Sep 2021View details →

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Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021

These are data from the CorporateMix US study rounds 1-4. Below is a description of the files: 1. participants: this contains a list of all the study participants for each round. EaA unique participant  identified by the participant_id and round. 2. contacts: this contains the individuals with whom a participant had a contact. 3.df_all: this is generated by merging the participant and contacts dataframes using the participant_id and round as primary keys. 4. day_rd1: this is data for round 1 day of survey. The survey design for round 1 was different, so these data are important to distinguish between day 1 and day 2 contacts.

opencc-by-4.0Dec 2022View details →

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Datasets used in the study "Trends in medication use after the onset of the COVID-19 pandemic in the Republic of Ireland: an interrupted time series study"

This record contains datasets analysed as part of the study "Trends in medication use after the onset of the COVID-19 pandemic in the Republic of Ireland: an interrupted time series study". Two datasets were used, one relating to therapeutic subgroups defined by ATC codes (atc_wide_freq_avg.csv) and one relating to individual medications (drugs_wide_freq_avg.csv). Datasets were collated by combining monthly data reported by HSE Primary Care Reimbursement Services in Ireland relating to dispensing on the General Medical Services scheme at https://www.sspcrs.ie/portal/annual-reporting/ Code used to collate datasets and for data management is included in Stata format (compile_data_export_for_analysis_final.do). The study protocol is available at https://doi.org/10.17605/OSF.IO/B4RTM

opencc-by-4.0Jun 2023View details →

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Timeline of government interventions and events regarding the COVID-19 pandemic in Sweden December 31, 2019, to May 5, 2023.

The Swedish approach to managing the COVID-19 pandemic has received significant attention in international scholarly work and the press. For this dataset, we have reviewed governmental and media archives to build a detailed timeline that chronicles significant policies, interventions, and events in the Swedish management of COVID-19. The dataset contains summary descriptions of what took place, when it happened, and who the principal actors involved were. Links to primary sources are provided for each entry. Because of the level of detail and saturation, the dataset offers a detailed account of Swedish pandemic governance and will benefit anyone working on Swedish pandemic management or doing comparative work between Sweden and other jurisdictions. The dataset contains details on the date an event took place (column 1), tags to facilitate navigation (column 2), details on the principal actors involved in the event (column 3), a summary description of what took place and who was involved (column 4), and links to primary materials (e.g., archival entries) (columns 4-12). Through a structured and detailed outline, the dataset provides a saturated account of policy interventions and events in Sweden during the COVID-19 pandemic for the period 2020-2023 until it was no longer considered a public health emergency of international concern by the WHO and complements existing and less detailed timelines published at earlier points in the period.

opencc-by-4.0Jun 2023View details →

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3DNIV/3DNIV: A Novel Dual Non-Invasive Ventilator Continuous Positive Airway Pressure Non-Aerosolization Circuit for Emergency Use in the COVID-19 Pandemic

The COVID19 pandemic is a public health emergency of unprecedented scale. The surge in clinical cases of patients with severe respiratory illness has overwhelmed the traditional capacity of healthcare systems worldwide. Continuous Positive Airway Pressure (CPAP) delivered through Non-Invasive Ventilation (NIV) has been shown to be useful in caring for patients with COVID19. In particular patients with early stage milder acute hypoxemic respiratory failure can benefit from NIV CPAP therapy, though there is an acknowledged risk of COVID19 aerosolization with traditional circuit use. Furthermore, given the surge in clinical care demand, there is an acute global shortage of ventilators, including NIV devices and therefore innovative methods are needed to increase NIV capacity and ameliorate infectious aerosolization. This work outlines an emergency use modified dual NIV CPAP Circuit that uses a 3D printed splitter designed to work with traditional international NIV CPAP tubing standards and a 3D printed respiratory face mask knuckle to allow for distal expiratory breath exhalation through a viral filter rather than through an open to air proximal valve, which is the traditional NIV CPAP configuration. We expect that this work will increase global NIV CPAP capacity and ameliorate aerosolization of COVID19 in patients undergoing therapy in an emergency scenario.

openother-openMay 2020View details →

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Datasets for How is the Pandemic Affecting AGU Journal Article Submissions?

These files provide tabular data on gender, age, and country of corresponding authors (the person submitting the manuscript to the peer review system) of American Geophysical Union (AGU) journals from January 2018 through April 2020. They supplement the article 'How is the Pandemic Affecting AGU Journal Article Submissions?' in Eos (https://eos.org/).

opencc-by-4.0May 2020View details →

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TweetsCOV19 - A Semantically Annotated Corpus of Tweets About the COVID-19 Pandemic (Part 1, October 2019 - April 2020)

<a href="https://data.gesis.org/tweetscov19/">TweetsCOV19</a> is a semantically annotated corpus of Tweets about the COVID-19 pandemic. It is a subset of <a href="https://data.gesis.org/tweetskb">TweetsKB</a> and aims at capturing online discourse about various aspects of the pandemic and its societal impact. Metadata information about the tweets as well as extracted entities, sentiments, hashtags, user mentions, and resolved URLs are exposed in RDF using established RDF/S vocabularies*. We also provide a tab-separated values (tsv) version of the dataset. Each line contains features of a tweet instance. Features are separated by tab character ("\t"). The following list indicate the feature indices: <ol> <li>Tweet Id: Long.</li> <li>Username: String. Encrypted for privacy issues*.</li> <li>Timestamp: Format ( "EEE MMM dd HH:mm:ss Z yyyy" ).</li> <li>#Followers: Integer.</li> <li>#Friends: Integer.</li> <li>#Retweets: Integer.</li> <li>#Favorites: Integer.</li> <li>Entities: String. For each entity, we aggregated the original text, the annotated entity and the produced score from <a href="https://github.com/yahoo/FEL">FEL</a> library. Each entity is separated from another entity by char ";". Also, each entity is separated by char ":" in order to store "original_text:annotated_entity:score;". If FEL did not find any entities, we have stored "null;".</li> <li>Sentiment: String. <a href="http://sentistrength.wlv.ac.uk/">SentiStrength</a> produces a score for positive (1 to 5) and negative (-1 to -5) sentiment. We splitted these two numbers by whitespace char " ". Positive sentiment was stored first and then negative sentiment (i.e. "2 -1").</li> <li>Mentions: String. If the tweet contains mentions, we remove the char "@" and concatenate the mentions with whitespace char " ". If no mentions appear, we have stored "null;".</li> <li>Hashtags: String. If the tweet contains hashtags, we remove the char "#" and concatenate the hashtags with whitespace char " ". If no hashtags appear, we have stored "null;".</li> <li>URLs: String: If the tweet contains URLs, we concatenate the URLs using ":-: ". If no URLs appear, we have stored "null;"</li> </ol> This dataset consists of 8,151,524 tweets in total, posted by 3,664,518 users and reflects the societal discourse about COVID-19 on Twitter in the period of October 2019 until April 2020. To extract the dataset from <a href="https://data.gesis.org/tweetskb">TweetsKB</a>, we compiled a seed list of 268 COVID-19-related <a href="https://data.gesis.org/tweetscov19/keywords.txt">keywords</a>. * For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.

opencc-by-4.0Jun 2020View details →

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Global Macroeconomic Scenarios of the COVID-19 Pandemic: Epidemiological Assumptions

Epidemiological Assumptions used for modelling the Global Macroeconomic Scenarios of the COVID-19 Pandemic

opencc-by-4.0Jun 2020View details →

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Supplementary Material - Maritime Cargo Prioritisation during a prolonged pandemic lockdown using an integrated TOPSIS-Knapsack technique

Supplementary Material - Maritime Cargo Prioritisation during a prolonged pandemic lockdown using an integrated TOPSIS-Knapsack technique: A Case Study on Small Island Developing States – the Rodrigues Island Results and Sensitivity analysis

opencc-byAug 2020View details →

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The Psychological Burden of the COVID-19 Pandemic and Its Associated Factors among the Frontline Doctors of Bangladesh: A Cross-sectional Study-Extended Data

Using this document, we tried to assess the mental health status of the frontline doctors of Bangladesh during Coronavirus 2019 pandemic.

opencc-bySep 2020View details →

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Well-being and Productivity of Software Professionals during a Pandemic

The COVID-19 pandemic has forced governments worldwide to impose movement restrictions on their citizens. Although critical to reducing the virus' reproduction rate, these restrictions come with far-reaching social and economic consequences. In this paper, we investigate the impact of these restrictions on an individual level among software engineers currently working from home. Although software professionals are accustomed to working with digital tools in their day-to-day work, the abrupt and enforced work-from-home context has resulted in an unprecedented scenario for the software engineering community. In a two-wave longitudinal study (N = 192), we covered over 50 psychological, social, situational, and physiological factors that have previously been associated with well-being or productivity. Examples include anxiety, distractions, psychological and physical needs, office set-up, stress, and work motivation. This design allowed us to identify those variables that explain unique variance in well-being and productivity. Results include (1) the quality of social contacts predicted positively, and stress predicted an individual's well-being negatively when controlling for other variables consistently across both waves; (2) boredom and distractions predicted productivity negatively; (3) productivity was less strongly associated with all predictor variables at time two compared to time one, suggesting that software engineers adapted to the lockdown situation over time; and (4) the longitudinal study did not provide evidence that any predictor variable causal explained variance in well-being and productivity.  Overall, we conclude that working from home was per se not a significant challenge for software engineers. Our study can assess the effectiveness of current work-from-home and general well-being and productivity support guidelines and provide tailored insights for software professionals.

opencc-by-4.0Jul 2020View details →

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The COVID Transmission: How Scientists and Science Journalists Are Communicating During the Pandemic

In this episode we talk to Wiebke Hollersen, a science journalist and editor from the German newspaper Welt, and Dr Emanuel Wyler, a molecular biologist at the Max Delbrück Center for Molecular Medicine, about their approaches, collaborations, and concerns about communicating about the Coronavirus and science communication in general.    Episode Links:  <a href="https://www.mdc-berlin.de/person/dr-emanuel-wyler">Emanuel Wyler</a> <ul> <li><a href="https://twitter.com/ewyler">Twitter</a></li> <li><a href="https://emanuelwyler.wordpress.com/">Blog (German Language)</a></li> </ul> <a href="https://www.welt.de/autor/wiebke-hollersen/">Wiebke Hollersen</a> <ul> <li><a href="https://twitter.com/wiebkehollersen">Twitter</a></li> </ul>

opencc-by-4.0Nov 2020View details →

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Vector sequences in early WIV SRA sequencing data of SARS-CoV-2 inform on a potential large-scale security breach at the beginning of the COVID-19 pandemic

DESCRIPTION Sequences identified as Influenza A virus, Spodoptera frugiperda rhabdovirus and Nipah henipavirus have been previously identified within the early HiSeq 1000 and HiSeq 3000 sequencing data of SARS-CoV-2, SRR11092059,SRR11092060,SRR11092061 and SRR11092062, and were being used to support the hypothesis that a "simultaneous outbreak of multiple zoonotic viruses" have happened in the Huanan Seafood market. https://doi.org/10.31219/osf.io/s4td6 However, a closer examination of these sequences revealed that they were not sequences of actual wild viruses, but were in stead fragments left behind from PCR products and cloning vectors harboring both cDNA clones and infectious clones of such viruses, with evidence of viral sequences being joined directly to DNA sequences of vector and non-human origin within the same short reads. Here are the vector sequences and PCR product-like sequences recovered from the earliest WIV SRA sequencing data of Human SARS-CoV-2 from dataset SRR11092059,SRR11092060,SRR11092061,SRR11092062. Sequences associated with Vectors and PCR products from 3 distinct viral species have been obtained: The 3'-end of a Nipah Henipahvirus with fusion to a Hepatitis D virus Ribozyme, a T7 terminator and a Tetracycline resistance gene, The 5'-end of the same Nipah Henipahvirus with fusion to sequences found in diverse vectors, A complete vector genome encoding the HA gene of Influenza A virus subtype H7N9 under a CMV promoter and a bgH polyA terminator, and 221 Contiguous sequences corresponding to the Spodoptera frugiperda rhabdovirus reference genome fused to sequences that were homologous to multiple Plastid sequences and Notably Mitochondrial sequences of Rodents. As sequences corresponding to a rescued infectious clone of a BSL-4 organism (Nipah Henipahvirus) were found in sample sequences that supposedy represents patient samples that were obtained from Hospital ICU and sequenced in a pathogen diagnosis laboratory (which is separate from the Virology Research laboratory which is implied by the context of an Infectious Clone of such an organism, evident by the 3'-HDV ribozyme and T7 terminator fused directly to the 3'-terminus of the Nipah Henipahvirus reads), The discovery of artifact-containing sequences of at least 3 different pathogen species that are phylogenetically and methodologically distinct from each other in samples that were supposedly submitted by a laboratory that is Separate from the virological research laboratories that could have hosted such clone sequences imply extensive crosstalk and cross-contamination between the various laboratories within the Wuhan Institute of Virology, which includes at least one BSL-4 laboratory with evidence of containment breach of a BSL-4 organism and it's subsequent introduction into RNA-seq samples that were processed by a laboratory of distinct and separate purposes than the basic virological research evidenced by the Infectious Clone of the Hipah Henipahvirus. Such a discovery therefore likely imply a major security breach happening within the Wuhan institute of Virology at the time when the first sequences of SARS-CoV-2 was sampled and sequenced, which have important implications on the origins of the SARS-CoV-2 virus itself. METHODS The metagenomic sequencing datasets, SRR11092059,SRR11092060,SRR11092061 and SRR11092062 were first analyzed using the NCBI phylogenetic analysis tool, which identified viral sequences that is not related to SARS-CoV-2 itself. These include Influenza A virus (IAV, subtype H7N9), Spodoptera frugiperda rhabdovirus and Nipah Henipahvirus. The datasets were then subjected to BLAST search using MEGABLAST against the reference sequences of such viruses to verify the existence of the viral sequences and determine the exact sybtype of such viruses and the closest sequences on GenBank that corresponds to the reads. There seuqences are MH926031.1 for the  Spodoptera frugiperda rhabdovirus,  KY199425.1 for the Influenza A virus and AY988601.1 for the Nipah Henipahvirus. A second round BLAST analysis with these identified sequences were then performed, which unexpectedly revealed numerous reads corresponding to Cloning vectors and non-human Mitochondrial and Plastid sequences being fused directly to the sequences of the identified viral species. Reads were then downloaded and subjected to assembly using the CAP3 sequence assembly program and the EGASSEMBLER tool. Contig sequences were then queried against the NCBI nr/nt database which unanimously identified the original sample sequences as viral sequences inserted into cloning vectors. The complete sequence of the Influenza A virus Haemagluttinin (HA) gene clone was obtained from SRR11092061,SRR11092062 using multiple rounds of BLAST search and sequence assembly expansion on the existing vector-virus junction contigs, and a partial sequence corresponding the 3'-end of Nipah Henipahvirus AY988601.1 fused to a 3'-HDV ribozyme, T7 terminator and a Tet resistance gene was obtained from SRR11092059. In addition, 221 Contig sequences corresponding to the Rhabdovirus MH926031.1 fused to Chloroplast sequence MN524635.1 and Rodent Mitochondrial sequence MT241668.1 have been recovered from SRR11092061. We then performed a BLAST search using the identified vector sequences on SRR11092059,SRR11092060,SRR11092061 and SRR11092062, which confirms the existence of these two vetor sequences in all 4 datasets.

opencc-by-4.0Dec 2020View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record