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Dataset results
18 results for “contact tracing”
Open-Access Data for "Received SignalStrength Measurements with BLE Signals for Contact Tracing and Proximity Detection"
<p>This archive contains three folders which are supplementary material for the paper accepted for publishing in IEEE Sensors Journal.</p> <p><strong>Contents:</strong></p> <ul> <li> The folder `open-access-data/upb/` contains the measurements acquired at UPB. The subfolders are named as `upb_ble_*`, where an asterisk masks the directory number. Whenever UPB is specified, use the data sets from the corresponding directory.</li> <li>The folder `open-access-data/tau/` contains the measurements acquired at TAU. The subfolders are named as `tau_ble_*`, where an asterisk masks the directory number. Whenever TAU is specified, use the data sets from the corresponding directory.</li> <li>The folder `open-access-data/wifi-on-off/` contains a sample code to read the files and plot the data from Fig. 14 in `open-access-data/wifi-on-off/wifi_on_off_read_plot.py` and Fig. 15 in `open-access-data/wifi-on-off/wifi_on_off_read_plot.ipynb`.</li> </ul> <p><strong>Results based on the data have been presented in the paper:</strong><br> Flueratoru, L., Shubina, V., Niculescu, D., Lohan, E.S. (2021). On the High Fluctuations of Received Signal Strength Measurements with BLE Signals for Contact Tracing and Proximity Detection, IEEE Sensors, Special Issue on Advanced Sensors and Sensing Technologies for Indoor Positioning and Navigation</p> <p><strong>To cite these data sets please use the following:</strong><br> Laura Flueratoru, Viktoriia Shubina, Dragoș Niculescu, & Elena Simona Lohan. (2021). Open Access Data for "Received SignalStrength Measurements with BLE Signals for Contact Tracing and Proximity Detection" [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4643668</p>
Contact tracing of binary stars: Pathways to stellar mergers (online data)
<p><strong># Data for Henneco et al. (2024)</strong></p> <p>This repository contains the input files required to reproduce the MESAbinary models from Henneco et al. (2024). It also contains the full machine-readable version of Table G.1. For an overview of the quantities in each column, we refer to the notes underneath Table G.1 in the paper.</p> <p>MESA r12778<br>MESA SDK 20.3.2</p> <p><strong>## MESA_inlists</strong></p> <p>- <strong>inlist1</strong>: inlist for the initially more massive primary star</p> <p>- <strong>inlist2</strong>: inlist for the initially less massive secondary star</p> <p>-<strong> inlist_project</strong>: inlist for the binary system</p> <p> </p> <p><strong>## run_extras</strong></p> <p>- <strong>run_star_extras.f</strong>: subroutines and functions for the individual stars</p> <p>- <strong>run_binary_extras.f</strong>: subroutines and functions for the binary system</p> <p> </p> <p><strong>## MESA_ZAMS_models</strong></p> <p>Precomputed ZAMS models read in through <strong>inlist1</strong> and <strong>inlist2</strong>.</p> <p> </p> <p><strong>## table_G1_full.txt</strong></p> <p>Full machine-readable version of Table G.1.<br> </p> <p><strong>## MESA_models_output</strong></p> <p>Detailed output of the MESAbinary calculations. <em>Will be added in due time.</em></p>
Contact tracing solutions for COVID-19: applications, data privacy and security :: Suplementary Material
<p>Supplementary Material for the paper "Contact tracing solutions for COVID-19: applications, data privacy and security"</p>
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study
<p>Data and code for publication on <em>Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study</em></p>
Package of Resources for Assisted Contact Tracing: Implementation, Costs, and Effectiveness
ClinicalTrials.gov study NCT05343390. IPD Sharing: YES. Countries: 1. Publications: 3.
Digital Contact Tracing: Overview of technological solutions for the fight against pandemics
<p>In late 2019, Covid-19 emerged and was soon declared a pandemic causing until now a massive health disruption and a huge impact on the global economy. Several governments around the world are still forced to take containment measures to curb the spread of the virus including partial or full lockdowns. At the same time, they rely heavily on human resources to perform manual Contact Tracing (CT) for alerting known contacts of the confirmed cases and breaking the infection chains early enough. However, CT does not scale well when the cases increase exponentially, due to the limited capacity of national public health authorities, and cannot identify possible <em>hidden</em> infections due to random encounters with strangers in crowded spaces such as restaurants, bars, theaters, public transportation, etc. To this end, Digital Contact Tracing (DCT) is becoming increasingly popular to enhance and empower CT, enabling automatic and faster identification and notification of exposed users. This presentation will first overview the different generations of DCT solutions from the privacy-invasive use of subscriber location data provided by cellular operators, to location monitoring mobile apps on GPS-equipped smartphones, to privacy-preserving mobile apps based on <em>proximity</em> sensing through Bluetooth. It will discuss the findings of recent studies with regards to the effectiveness of DCT and debate whether it has been – or has the potential to become – a game changer. Finally, it will outline the latest developments and trends in this active research field that are of interest to the IPIN community including <em>presence</em> tracing that aims to notify anonymously those users that have been in the same place (especially indoors) with an infected user, without necessarily satisfying the proximity constraint.</p>
Kharituwe TB Contact Tracing Study
ClinicalTrials.gov study NCT04520113. IPD Sharing: NO. Countries: 1. Publications: 3.
Empirical data for project: Mining user reviews of COVID contact-tracing apps
<p>Empirical data for project: Mining user reviews of COVID contact-tracing apps</p>
A Framework for Improving Social Inclusion using Network Analysis and IoT-based Contact Tracing, Dataset and Source Code
Open the record for dataset details and reuse information.
QuantiFERON®-TB Gold In-Tube for the Diagnosis of Tuberculosis Infection in Contact Tracing Study.
ClinicalTrials.gov study NCT01223534. IPD Sharing: NO. Countries: 1. Publications: 1.
Costing data for implementing mHealth facilitated tuberculosis contact tracing in Uganda
<p><strong>Introduction</strong></p> <p>Mobile health (mHealth) applications may improve timely access to health services and improve patient-provider communication, but the upfront costs of implementation may be prohibitive, especially in resource-limited settings.</p> <p><strong>Methods</strong></p> <p>We measured the costs of developing and implementing an mHealth-facilitated, home-based strategy for tuberculosis (TB) contact investigation (CI) in Kampala, Uganda, between February 2014 and July 2017. We compared routine implementation involving community health workers (CHWs) screening and referring household contacts to clinics for TB evaluation to home-based HIV testing and sputum collection and transport with test results delivered by automated short messaging services (SMS) We carried out key informant interviews with CHWs and asked them to complete time-and-motion surveys. We estimated program costs from the Ugandan health system perspective, using top-down and bottom-up (components-based) approaches. We estimated total costs per contact investigated and per TB-positive contact identified in 2018 US dollars, one and five years after program implementation.</p> <p><strong>Results</strong> </p> <p>The total top-down cost was $472,327, including $358,504 (76%) for program development and $108,584 (24%) for program implementation. This corresponded to $320-$348 per household contact investigated and $8873-$9652 per contact diagnosed with active TB over a 5-year period. CHW time was spent primarily evaluating household contacts who returned to the clinic for evaluation (median 30 minutes per contact investigated, interquartile range [IQR]: 30-70), collecting sputum samples (median 29 minutes, IQR: 25-30) and offering HIV testing services (median 28 minutes, IQR: 17- 43). Cost estimates were sensitive to infrastructural capacity needs, program reach, and the epidemiologic yield of contact investigation. </p> <p><strong>Conclusion</strong></p> <p>Over 75% of all costs of the mHealth-facilitated TB contact investigation strategy were dedicated to establishing mHealth infrastructure and capacity. Implementing the mHealth strategy at scale and maintaining it over a longer time horizon could help decrease development costs as a proportion of total costs.</p>
Costing data for implementing mHealth facilitated tuberculosis contact tracing in Uganda
Open the record for dataset details and reuse information.
Contact Tracing is Associated with Lower COVID-19 Case Fatality Rates: Evidence from 40 countries
<p> </p> <p>Datasets represent data used in regression analysis.</p>
Intensifying Multi-Drug Resistant Tuberculosis Contact Tracing by Social Network Analysis
ClinicalTrials.gov study NCT02175849. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Use of a Gamma-IFN Assay in Contact Tracing for Tuberculosis in a Low-Incidence, High Immigration Area
ClinicalTrials.gov study NCT00557765. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Participant Agreement for Contact Tracing (PACT) Study: Enhancing Partner Notification Services.
ClinicalTrials.gov study NCT00207493. IPD Sharing: Not stated. Countries: 1. Publications: 0.
MDR-TB Close Contacts Tracing in China (TCCT Study)
ClinicalTrials.gov study NCT04484129. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Male Partner-assisted Contact Tracing for HIV and Tuberculosis in Malawi
ClinicalTrials.gov study NCT04285905. IPD Sharing: YES. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.