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599 results for “health data”

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dryad40/100

Data from: Tool use increases mechanical foraging success and tooth health in southern sea otters (Enhydra lutris nereis)

<p>Although it is well documented that tool use can enable the utilization of novel resources, the fitness benefits associated with this innovative behavior are difficult to test. Using longitudinal data from 196 radio-tagged southern sea otters, we found that individuals, particularly females, with frequent tool use gained access to harder, larger prey items. In turn, the mechanical advantages of tool use during food processing translated to reduced tooth damage in tool users. We also found that tool use diminishes trade-offs between access to different prey types, tooth health, and caloric intake that are highly dependent on the relative availability of prey in the environment. Overall, tool use allows individuals to maintain caloric requirements through the processing of alternative prey that are otherwise inaccessible without the use of tools, indicating that this innovative behavior is a necessity for the survival of southern sea otters in environments with depleted preferred prey.</p>

opencc-zeroApr 2024View details →
zenodo40/100

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Norway

<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Luxembourg

<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

Animal disease data complementing the European Union One Health 2020 Zoonoses Report

<p>This dataset contains the mandatory annual data reported for bovine tuberculosis and for bovine and ovine and caprine brucellosis based on Directive 2003/99 that cites in Recital 7 the Council Directives 64/432/EEC and 91/68/EEC. The relevant Commission Decisions relating to the officially free (OF) MS and MS&#39; regions and related reporting are: Decision 2003/467/EC for bovine tuberculosis and bovine brucellosis, and Decision 93/52/EC for sheep and goat brucellosis (B. melitensis). REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: Disease_status_data_2020_20211109: &gt;&gt;</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

Prevalence data complementing the European Union One Health 2020 Zoonoses Report

<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: Prev_data_2020&nbsp;&gt;&gt;</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - the United kingdom

<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Finland

<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Sweden

<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>

opencc-by-4.0Dec 2021View details →
zenodo40/100

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

<p>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.</p>

opencc-by-4.0Jan 2022View details →
zenodo40/100

Is Open Data Strategy for Covid-19 used for other global health threats? A systematic review of the literature

<p>Dataset result of the literature review run between march and may 2022 on PubMed, Cinahl, Scopus and Google Scholar about&nbsp;open data and&nbsp;growing trend in scientific research about infection risk comparing Covid-19, Anti Microbial Resistance (AMR), and Health Assistance Correlated Infections&nbsp;(HAIs).</p>

opencc-by-4.0Jun 2022View details →
zenodo40/100

Supplementary Data: OpenCOVID model output underlaying Figures 1 and 2 of "Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden"

<p>Supplementary data files&nbsp;<strong>Figure_1.xlsx</strong>&nbsp;and&nbsp;<strong>Figure_2.xlsx</strong>&nbsp;contain&nbsp;the model simulation outcomes for Figures 1 and 2&nbsp;of <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al</em></a>&nbsp;&quot;<strong>Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden</strong>&quot; (2022)</p> <ul> <li><strong>Figure 1</strong>:&nbsp;Peak daily hospital occupancy (number of beds&nbsp;per 100,000 population over the six-month simulation period)&nbsp;for three&nbsp;variant properties; infectivity (relative to Delta), immune evading capacity (%), and severity (relative to Delta)<br> &nbsp;</li> <li><strong>Figure 2</strong>: Percentage of COVID-19 infections and deaths averted by third-dose vaccines for adults and vaccinating 5-11-year-olds with doses one and two.<br> &nbsp;</li> <li>Open access source-codes of the associated plotting functions are&nbsp;published <a href="http://zenodo.org/record/6532404#.Yqw7cezMKdb">here</a> on Zenodo.<br> &nbsp;</li> <li>Open access source-codes for the OpenCOVID model of all analyses as presented in&nbsp;<a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock&nbsp;<em>et al.</em>&nbsp;(2022)</a>&nbsp;are publicly available at&nbsp;<a href="https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src">https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src</a>.<br> &nbsp;</li> <li>Detailed model descriptions and model equations of individual-based transmission model&nbsp;<strong>OpenCOVID</strong>&nbsp;are described in&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/34923396/">Shattock&nbsp;<em>et al</em>. (2022)</a>&nbsp;and&nbsp;<a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock&nbsp;<em>et al.</em>&nbsp;(2022).</a></li> </ul>

opencc-by-4.0Jun 2022View details →
zenodo40/100

Network Theme: Can blood sampling become a new data source in the role of self-monitoring and self-management of health? - Dr Mark Elliott (University of Warwick)

<p>This video is the fourth talk from our Future Blood Testing Network Plus Launch that took place on the 23/11/2021.</p> <p>Network Theme: Can blood sampling become a new data source in the role of self-monitoring and self-management of health? - Dr Mark Elliott (University of Warwick)</p> <p>Bio: <strong><a href="https://warwick.ac.uk/fac/sci/wmg/people/profile/?wmgid=1147">Dr Mark Elliott</a>&nbsp;</strong>Mark is an Associate Professor at the Institute of Digital Healthcare, WMG, University of Warwick (UoW). Mark&rsquo;s core research focuses on human movement and physiology analytics. His research uses signal processing and data science approaches to monitor, measure and model human movement and physiology to infer health status. He is the PI of the WMG Motion Capture Laboratory. His work further extends into the broader area of using wearable and on-the- body sensing devices to make objective measures of human behaviour and behaviour change. Much of Dr Elliott&rsquo;s research is highly applied and involves collaborating with commercial and NHS partners. He has received funding from EPSRC, Innovate UK and SBRI Healthcare, as well as direct industrial funding. He is currently Data Analytics Theme Lead for the EPSRC funded OATech+ Network and on the steering committee for the EPSRC funded VSimulators facilities at Bath and Exeter.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/23-11-21-future-blood-testing-network-launch/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link:&nbsp;https://youtu.be/ChdbggScUgo</p>

opencc-by-4.0Nov 2021View details →
zenodo40/100

Data on the occurrence of Vibrio spp. of public health importance (i.e. Vibrio parahaemolyticus, Vibrio vulnificus, and Vibrio cholerae non-O1/non-O139) in seafood in European countries (Jan 2010-Sept 2023)

<p><span>This file contains data on &nbsp;the occurrence of <em><span>Vibrio</span></em><span>&nbsp;spp. of public health importance (<em>i.e</em>.&nbsp;<em>Vibrio parahaemolyticus</em>,&nbsp;<em>Vibrio vulnificus,</em>&nbsp;and&nbsp;<em>Vibrio cholerae&nbsp;</em>non-O1/non-O139) in seafood produced and/or commercialized in Europe, </span>covering studies published between January 2010 and September 2023. </span><span>The systematic review protocol used to identify and extract the information is available at <a href="../doi/10.5281/zenodo.10282513"><span>https://zenodo.org/doi/10.5281/zenodo.10282513</span></a> .</span></p>

opencc-by-4.0Jun 2024View details →
dryad40/100

Data from: Impacts of weathered microplastic ingestion on gastrointestinal microbial communities and health endpoints in fathead minnows (Pimephales promelas)

<p>Microplastics are a ubiquitous presence in the world's aquatic environments and their threat to aquatic biota is poorly understood, especially in freshwater ecosystems. In the environment, microbial biofilms can form on the surface of microplastics, and these plastics have the potential to adsorb harmful toxins. Because lab-based studies on microplastics are often conducted with clean polymers, in ecologically unrealistic conditions and concentrations, the impact of these weathered microplastics on aquatic organisms in ecologically realistic conditions is still unclear. To help address the need for ecologically relevant microplastic exposure data, we incubated 500 μm polyethylene microplastic beads in Muskegon Lake, Michigan, USA and used them to conduct a 28-day ingestion study with male and female fathead minnows (<em>Pimephales promelas</em>). We examined the effects of microplastic ingestion on the fish gut microbial community along with hepatic gene expression and health parameters. We found that microplastic ingestion had statistically significant impacts on growth in male fathead minnows. Microplastic treatment did not significantly alter the beta diversity of the gut microbial community for either males or females, but there were clear differences between sexes and over time, indicating that these factors may outweigh the impacts of microplastic ingestion on beta diversity in the gut. The expression of immune response genes was not altered in males. It did, however, cause some changes to alpha diversity metrics in both sexes and there were several differentially abundant taxa among treatments. These data suggest that microplastic ingestion has health effects, but these effects may be sex specific across certain species and they are likely not being solely driven by changes in gut microbial communities.</p>

opencc-zeroJul 2024View details →
zenodo40/100

Impact of public health expenditure on malnutrition among Peruvians during the period 2010-2020: A panel data analysis

<p><strong><span>Background: </span></strong><a name="_Hlk170909708"></a><span>The study analyzes the impact of public health spending on malnutrition among Peruvians, using data from the National Household Survey, the Central Reserve Bank of Peru, the National Institute of Statistics and Informatics and the Ministry of Economy and Finance from 2010. -2020. Previous studies have revealed the existing relationship of health spending with the reduction of malnutrition</span><span>.</span></p> <p><strong><span>Methods:</span></strong><span> A quantitative approach is considered, with an explanatory type of research using panel data methodology considering the bidimensionality of the data, which allows quantifying this effect for the Peruvian case using the National Household Survey, data from the Central Reserve Bank of Peru, as well as information from the National Institute of Statistics and Informatics and the</span><strong><span> </span></strong><span>Transparency Portal of the Ministry of Economy and Finance in the period 2010-2020.</span><strong><span> </span></strong></p> <p><strong><span>Results: </span></strong><span>The results show that public expenditure on health has a negative relationship with malnutrition; the rural sector has a positive relationship with malnutrition given the limitations present for access to adequate food. Similarly, the unemployment rate shows a positive relationship with malnutrition, given that being unemployed leads to a higher cause of malnutrition in the population, and the gross domestic product has a negative relationship with malnutrition, given that greater economic growth produces an impact on reducing malnutrition, with the greatest impact being on the rural population and the gross domestic product. </span></p> <p><strong><span>Conclusions:</span></strong><span> In the analysis period 2010-2020 in Peru, based on the panel data analysis, the impact of public health expenditure on reducing malnutrition is observed in 10 departments, achieving a reduction in malnutrition; while in 14 departments, this indicator has not been reduced.</span></p>

opencc-zeroJun 2024View details →
zenodo40/100

Using the Socialise app to collect smartphone sensor data for mental health research: A feasibility study

<p>To investigate the feasibility of collecting smartphone sensor data for mental health research, we tested the Socialise app that was developed at the Black Dog Institute in a&nbsp;group of people with a lived experience of mental health challenges (n=32). Bluetooth, GPS and battery status data were collected at regular intervals (3, 4, 5 or 8 minutes) for 4 weeks. In addition, survey data was collected using the app to investigate the views of participants on user experience and the acceptability of passive data collection for mental health research.&nbsp;No mental health data was collected as part of the feasibility study.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Guidelines for Data Management Plan implementation of One Health EJP projects: Webinar held on the 19th December 2018

<p>Webinar held on the 19th December 2018 to introduce Data Management Plan to scientists involved in the research and integrative projects of One Health European Joint Program.</p>

opencc-by-4.0Dec 2018View details →
zenodo40/100

Data supporting the "Health Libraries Sharing Game"

<p>This dataset provides the necessary files to reproduce the &quot;Health libraries sharing game&quot;. This game was created for the workshop &quot;Health libraries: sharing through gaming&quot; held in Basel on Wednesday the 19th of June 2019, as part of the EAHIL conference.</p> <p>Inspired by the game &quot;Bucket of Doom&quot;, this game aims to help health librarians address challenging professional situations (based on real situations experienced by the authors). The players will have to be creative to overcome each challenge.&nbsp;</p> <p>The game is composed of cards that include possible situations to resolve, some tools, as well as&nbsp;resources available to solve those&nbsp;questions. The cards are accompanied by a &quot;How to play&quot; file explaining the rules of the game and a &quot;Name sheet&quot; file with the combination of funny names that participants can choose at the beginning of the game. The README.txt file describes the files and the content of the different folders of the dataset.</p> <p>Please consult the following article for further information about the creation of the game:</p> <p>G&oacute;mez-S&aacute;nchez, A., Kerdelhue, G., Isabel-G&oacute;mez, R., Gonz&aacute;lez-Cantalejo, M., Iriarte, P., &amp; Muller, F. (2019). Health libraries: sharing through gaming. Journal of EAHIL, 15(3), 8-11. https://doi.org/10.32384/jeahil15329&nbsp;</p>

opencc-by-4.0Aug 2019View details →
zenodo40/100

Details of offspring and source data for analysis of metabolic health and dietary preference in a rat model of acute alcohol exposure.

<p>This Excel file contains information on the number of offspring used to examine each outcome and the raw data for each data Table and Figure within a manuscript submitted to Journal of Physiology.&nbsp;</p>

opencc-by-4.0Apr 2019View details →
zenodo40/100

Plant health data from Belgian Plant Sentinel Network

<p>The enclosed files contain the questions (in Dutch, English &amp;&nbsp;French) and the responses from tree surveys conducted under the Belgian Plant Sentinel Network.</p> <p>Background to the project</p> <p>Botanic gardens and arboreta possess outstanding scientific collections of a wide diversity of plants, frequently growing outside their natural geographical range. These can be used as sentinels for both early detection of emerging pests and for potentially invasive pests. This is&nbsp;why the International Plant Sentinel Network&nbsp;was launched by EUPHRESCO (EUropean PHytosanitary RESearch COordination), an international network of organisations funding research projects and coordinating national research programmes in the phytosanitary area. International&nbsp;Network developed a transnational network consisting of gardens, diagnostic laboratories and National Plant Protection Organisations, working together in order to provide an early warning system for new and emerging plant pests and diseases. It focused on developing tools and took place in a limited number of countries.</p> <p>Belgium did not participate in the first phase of International Plant Sentinel Network, even though there are many botanic gardens and arboreta in the country. The largest of them is Meise Botanic Garden, which is one of the largest botanic gardens in the world (92 ha).&nbsp; Besides Meise there are several gardens with diverse and unique collections spread all over the country. Among these gardens&nbsp;many have staff members with good knowledge of plant protection, which assure the control of pests and diseases in the collections of the gardens. On the other hand, up to now there have been only limited interactions between the gardens and the National Reference Laboratories for plant pests and diseases. It would be interesting to strengthen these interactions, both for the gardens and arboreta, for a better management and protection of their living collections, and for the Reference Laboratories, in order to gather more data on the presence of pests and diseases in the country.</p> <p>That is why we have created a Belgian network similar to international network, aiming at supporting national plant health policy by early warning of new pest threats, and meanwhile operating in the new transnational initiative of the international network. Together they can form a dense Belgian network to gather data and expand the surveillance of emerging pests over the entire national territory. They also hold most of the plant diversity present in the whole country.</p> <p>Standardized methods and tools for making the plant health surveys have been developed by the International Plant Sentinel Network during its first phase from 2013 to 2016. One of these tools is the Plant Health Checker, a form for making standardized surveys of trees. Two versions are available, one for surveying deciduous trees and one for conifers, as the symptoms to watch for differ between these two groups in some cases. Each form is available in English as a paper form with two sides. Moreover, a reference guide with instructions on how to use the checker&nbsp;had also been made with it, as well as a guide to taking photographs for diagnostic purposes.</p> <p>For the Belgian project we adapt these forms in order to facilitate their use. We translated them to&nbsp;French and&nbsp;Dutch, the two main languages of the country, so that all gardeners could&nbsp;use them. A second goal was to adapt them to the test cases selected for the project. Indeed, some symptoms that are important for these organisms are not included in the original plant heath checker, mainly concerning the symptoms on roots for the root-knot nematode and <em>Phytoplasma</em> case. A third aim was to investigate whether the forms could be simplified for making the surveys in the field. For the latter, however, it was decided to await the user experience of the first year, so as to make an evaluation and suggest eventual amendments.</p> <p>It is also planned to develop an electronic version of the checker form, so as to be able to input the survey data directly in digital format and thus skipping a second and tedious step of entering the data from paper forms into the computer. Moreover, it is preferable to have a system which can easily make the data available to a central data system. That is why we chose to use Google Forms within Google Drive, because it can be utilized as a central data system and flexible, and has many functionalities such as sharing the data. This system also allows the direct input of data with an internet connection.</p>

opencc-by-4.0Apr 2019View details →

ScienceDex guides

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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