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230 results for “public health”

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zenodo36/100

Fully synthetic longitudinal real-world data from hearing aid wearers for public health policy modeling

<p>Real-world data from hearing aids and Bluetooth&nbsp;connected smartphones. The associated data report can be found here:&nbsp;<a href="https://doi.org/10.3389/fnins.2019.00850">https://doi.org/10.3389/fnins.2019.00850</a></p>

opencc-by-4.0May 2019View details →
zenodo36/100

Code + simulated + publically accessable data for "Evaluating health facility access using Bayesian spatial models and location analysis methods"

<p># README</p> <p>These files contain r data objects and R files that represent the key details of the paper, &quot;Evaluating health facility access using Bayesian spatial models and location analysis methods&quot;.</p> <p>The following datasources are available for simulation of some of the ideas in the paper.</p> <p>- dat_grid_sim: simulated data of the grid and grid cells<br> - dat_ohca_cv_sim: simulated data containing the cross validated test/training sets of OHCA data<br> - dat_ohca_sim: simulated OHCA event data<br> - dat_aed_sim: simulated AED location data<br> - dat_bldg_sim: simulated building location data<br> - dat_municipality_sim: simulated municipality information<br> - table_1: Table 1 information containing key demographic data</p> <p>These data were produced using the code in 01-create-sim-data.R, and one of the statistical models is demonstrated in 02-demo-inla-model.R</p> <p>In terms of the paper itself, the functions and code used in the manuscript are located in:</p> <p>* 01_tidy.Rmd - analysis code used to tidy up the data</p> <p>* 02_fit_fixed_all_cv.Rmd - analysis code used to place AEDs</p> <p>* 02_model.Rmd - analysis code used to fit the model in INLA</p> <p>* 03_manuscript.Rmd - Full code and text used to create the paper</p> <p>* 04_supp_materials.Rmd - full code and text used to create the supplementary materials</p> <p>The following files are a part of an R package &quot;swatial&quot; that was developed along with the paper. These files are:</p> <p>* DESCRIPTION</p> <p>* NAMESPACE</p> <p>* LICENSE</p> <p>* LICENSE.md</p> <p>* decay.R</p> <p>* spherical-distance.R</p> <p>* test-figure-data-matches.R</p> <p>* test-table-data-matches.R</p> <p>* testthat.R</p> <p>* tidy-inla.R</p> <p>* tidy-posterior-coefs.R</p> <p>* tidy-predictions.R</p> <p>* utils-pipe.R</p> <p>* All files that end in .Rd are documentation files for the functions.</p> <p>## Regarding data sources</p> <p>Census information for Ticino was transcribed from the Annual Statistical Report of Canton Ticino from years 2010 to 2015. This data was taken from their publicly accessible annual reports - for example: (https://www3.ti.ch/DFE/DR/USTAT/allegati/volume/ast_2015.pdf). The raw data was extracted from these annual reports, and placed into the file: &quot;swiss_census_popn_2010_2015.xlsx&quot;. These data are put into analysis ready format in the file &ldquo;01_tidy.Rmd&rdquo;</p> <p>Housing and other relevant geospatial data can be accessed via http://map.housing-stat.ch/ and https://data.geo.admin.ch/. The maps of buildings from the REA (Register of Buildings and Dwellings) can be found here: https://map.geo.admin.ch/?zoom=11&amp;bgLayer=ch.swisstopo.pixelkarte-grau&amp;lang=en&amp;topic=ech&amp;layers=ch.bfs.gebaeude_wohnungs_register,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.bfs.volkszaehlung-gebaeudestatistik_gebaeude,ch.bfs.volkszaehlung-gebaeudestatistik_wohnungen,ch.swisstopo.swissbuildings3d_1.metadata,ch.swisstopo.swissbuildings3d_2.metadata&amp;E=2717616.28&amp;N=1096597.25&amp;catalogNodes=687,696&amp;layers_timestamp=,,2016,2016,,&amp;layers_visibility=true,false,false,false,false,false&amp;layers_opacity=1,1,1,1,1,0.75</p> <p>For further enquiries on this data, contact the Swiss federal Office of Statistics at the details listed here: https://www.bfs.admin.ch/bfs/en/home/services/contact.html</p> <p>The shapefiles of the Comuni can be accessed here: https://www4.ti.ch/dfe/de/ucr/documentazione/download-file/?noMobile=1</p> <p>Data from the people living in the Municipalities in Ticino can be downloaded here: https://www3.ti.ch/DFE/DR/USTAT/index.php?fuseaction=dati.home&amp;tema=33&amp;id2=61&amp;id3=65&amp;c1=01&amp;c2=02&amp;c3=02</p> <p>## Future work</p> <p>In the future, these functions from the paper may be generalised and put into their own package. If that happens, this repository will be updated with a link to updated functions.</p>

opencc-by-4.0Jun 2019View details →
zenodo36/100

Fig. 2 in Spatial distribution of Culicidae (Diptera) larvae, and its implications for Public Health, in five areas of the Atlantic Forest biome, State of São Paulo, Brazil

Fig. 2. Spatial distribution of the species found in the Cruzeiro do Sul rural district.

opencc-by-4.0Jan 2017View details →
zenodo36/100

Fig. 1 in Spatial distribution of Culicidae (Diptera) larvae, and its implications for Public Health, in five areas of the Atlantic Forest biome, State of São Paulo, Brazil

Fig. 1. Localization of the study areas in the Atlantic Forest biome, São Paulo state – Brazil.

opencc-by-4.0Jan 2017View details →
zenodo36/100

Fig. 6 in Spatial distribution of Culicidae (Diptera) larvae, and its implications for Public Health, in five areas of the Atlantic Forest biome, State of São Paulo, Brazil

Fig. 6. Adjusted Semi-variograms of the Simpson diversity index.

opencc-by-4.0Jan 2017View details →
zenodo36/100

Fig. 3 in Spatial distribution of Culicidae (Diptera) larvae, and its implications for Public Health, in five areas of the Atlantic Forest biome, State of São Paulo, Brazil

Fig. 3. Spatial distribution of the species found in the Vale das Cigarras rural districts.

opencc-by-4.0Jan 2017View details →
zenodo36/100

Fig. 1 in Sentinels in the shadows: Exploring Toxoplasma gondii and other Sarcocystidae parasites in synanthropic rodents and their public health implications

Fig. 1. Geographical distribution of PCR positive rodents.

opencc-by-4.0Aug 2024View details →
zenodo36/100

Public Health Image Library: public-health-image-library (79) DwCA

Created by a Working Group at the Centers for Disease Control and Prevention (CDC), the PHIL offers an organized, universal electronic gateway to CDC__s pictures. <p></p>http://phil.cdc.gov/<p></p>

opennotspecifiedAug 2024View details →
zenodo36/100

Metal and Metalloid Bioaccumulation in Nodipecten nodosus (Linnaeus, 1758) Scallops (Mollusca: Pectinidae) Cultivated in Southeastern Brazil and Associated Public Health Issues

<p>Supplementary Table S1. Instrumental ICP-MS conditions for metal and metalloid detection in lion&rsquo;s paw scallops in Southeastern Brazil. <strong>Table S2.</strong> Metal accumulation levels for Cd, Cu, Zn and Ni between scallop species and different locations worldwide. All data are expressed as &mu;g. g<sup>-1</sup>w.w. FAAS - Flame Atomic Absorption Spectrometry, ICP-MS - Inductively Coupled Plasma Mass Spectrometry, ICP-OES - Inductively Coupled Optical Emission Spectrometry, ATFS &ndash; Atomic Fluorescence Spectrometry.&nbsp; <strong>Table S3</strong>. Metal accumulation levels for Pb, Cr, Fe and Mn between scallop species and different locations worldwide. All data are expressed as &mu;g. g<sup>-1</sup>w.w. FAAS - Flame Atomic Absorption Spectrometry, ICP-MS - Inductively Coupled Plasma Mass Spectrometry, ICP-OES - Inductively Coupled Optical Emission Spectrometry, ATFS &ndash; Atomic Fluorescence Spetrometry</p>

opencc-by-4.0Dec 2022View details →
dryad36/100

#Coronavirus on TikTok: User engagement with misinformation as a potential threat to public health behavior

<p><strong>Background:</strong> COVID-related misinformation is prevalent online, including on social media. The purpose of this study was to explore factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok.</p> <p><strong>Methods:</strong> A sample of TikTok videos associated with the hashtag #coronavirus were downloaded on September 20, 2020. Misinformation was evaluated on a scale (low, medium, high) using a codebook developed by experts in infectious diseases. Multivariable modeling was used to evaluate factors associated with number of views and presence of user comments indicating intention to change behavior.</p> <p><strong>Results:</strong> 166 TikTok videos were identified. Moderate misinformation was present in 36 (22%) videos, and high-level misinformation was present in 11 (7%). After controlling for characteristics and content, videos containing moderate misinformation were less likely to generate a user response indicating intended behavior change. By contrast, videos containing high-level misinformation were less likely to be viewed but demonstrated a non-significant trend towards higher engagement among viewers.</p> <p><strong>Conclusions:</strong> COVID-related misinformation is less frequently viewed on TikTok but more likely to engage viewers. Public health authorities can combat misinformation on social media by posting content of their own. </p>

opencc-zeroJan 2023View details →
zenodo36/100

A crowd clustering prediction and captioning technique for public health emergencies

<p>Data set used to implement the project&nbsp;<strong>A crowd clustering prediction and captioning technique for public health emergencies&nbsp;crowd clustering prediction and captioning technique for public health emergencies</strong></p>

opencc-by-4.0Feb 2023View details →
dryad36/100

Public health emergency operations centres in Africa: A cross-sectional study assessing the implementation status of core components and areas for improvement, December 2021

<div> <p><span><strong>Objective:</strong> </span><span>To assess implementation status of Public Health Emergency Operations Centres (PHEOCs) in all countries in Africa.</span></p> <p><span><strong>Design:</strong> </span><span>Cross-sectional.</span></p> <p><span><strong>Setting:</strong> </span><span>Fifty-four national PHEOC focal points in Africa responded to an online survey between May and November 2021. Included variables aimed to assess capacities for each of the four PHEOC core components. To assess the PHEOCs' functionality, criteria were defined from among the collected variables by expert consensus based on PHEOC operations' prioritisation. We report results of the descriptive analysis, including frequencies of proportions.</span></p> <p><span><strong>Results:</strong> </span><span>A total of 51 (93%) African countries responded to the survey. Among these, 41 (80%) have established a PHEOC. Twelve (29%) of these met 80% or more of the minimum requirements and were classified as fully functional. Twelve (29%) and 17 (41%) PHEOCs that met 60%–79% and below 60% of the minimum requirements were classified as functional and partially functional, respectively. </span></p> <p><span><strong>Conclusions:</strong> </span><span>Countries in Africa made considerable progress in setting up and improving functioning of PHEOCs. One-third of the responding countries with a PHEOC have one fulfilling at least 80% of the minimum requirements to operate the critical emergency functions. There are still several African countries that either do not have a PHEOC or whose PHEOCs only partially meet these minimal requirements. This calls for significant collaboration across all stakeholders to establish functional PHEOCs in Africa.</span></p> </div>

opencc-zeroMar 2023View details →
zenodo36/100

Table 2. Studies on psychiatric side effects of fluoroquinolones. The risk of bias and study quality assessed with the Effective Public Health Practice Project's Quality Assessment Tool for Quantitative Studies (QATQS) was presented as the global rating for each publication (3 – weak).

<p>Studies on psychiatric side effects of fluoroquinolones. The risk of bias and study quality assessed with the Effective Public Health Practice Project&rsquo;s Quality Assessment Tool for Quantitative Studies (QATQS) was presented as the global rating for each publication (3 &ndash; weak).</p>

opencc-by-4.0Jun 2023View details →
zenodo36/100

Figure 1 in Species composition of hard ticks (Acari: Ixodidae) on domestic animals and their public health importance in Tamil Nadu, South India

Figure 1. Localities where the field work was carried out in Madurai district.

opencc-by-4.0Jan 2021View details →
zenodo36/100

Imptox Public Workshop Micro- Nanoplastics & Human Health: Insights from Science and Research (pt2)

<p>Experts gather at the Imptox workshop to discuss the emerging understanding of micro- and nanoplastics&#39; impact on human health. On Friday, March 24th, 2023, the successful Imptox public workshop attracted a large audience discussing the potential health impacts of micro- and nanoplastics with experts from all over Europe. The Imptox project has received funding from the EU&rsquo;s H2020 framework program for research and innovation under grant agreement n. 965173</p>

opencc-by-4.0Mar 2023View details →
zenodo36/100

Imptox Public Workshop Micro- Nanoplastics & Human Health: Insights from Science and Research (pt3)

<p>Experts gather at the Imptox workshop to discuss the emerging understanding of micro- and nanoplastics' impact on human health. On Friday, March 24th, 2023, the successful Imptox public workshop attracted a large audience discussing the potential health impacts of micro- and nanoplastics with experts from all over Europe. The Imptox project has received funding from the EU's H2020 framework program for research and innovation under grant agreement n. 965173.&nbsp;</p>

opencc-by-4.0Mar 2023View details →
ClinicalTrials.gov36/100

Evaluating Public Health Interventions to Improve COVID-19 Testing Among Underserved Populations

ClinicalTrials.gov study NCT05270694. IPD Sharing: Not stated. Countries: 1. Publications: 7.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Inter-organizational Health Planning for Older Adults: Public Dental Care and Municipal Care

ClinicalTrials.gov study NCT06310798. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

Improving Cancer Prevention and Control Through Academic-local Public Health Department Partnerships

ClinicalTrials.gov study NCT06605196. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

Disseminating Public Health Evidence to Support Prevention and Control of Diabetes Among Local Health Departments

ClinicalTrials.gov study NCT03211832. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →

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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