List of high-risk people advised to self-isolate during Covid pandemic.

The EU-U.S. and Swiss-U.S. Privacy Shield Frameworks are mechanisms that companies can use to comply with data protection requirements when transferring personal data from the European Union and Switzerland to the United States. ITA\'s Privacy Shield Team maintains two lists that are made available to the public: 1) the Privacy Shield Active List, and 2) the Privacy Shield Inactive List. The Active List is an authoritative list of U.S. organizations that have self-certified to the Department of Commerce and declared their commitment to adhere to the Privacy Shield Principles. The Inactive List is an authoritative list of U.S. organizations that are no longer self-certified under Privacy Shield and are therefore no longer assured of the benefits of using Privacy Shield to receive personal data from the European Union and/or Switzerland. Upon request, the Privacy Shield Team may provide a copy of the list in the form of an Excel spreadsheet.

Shielding is one of the government interventions aimed at reducing mortality from COVID-19. Those considered at highest clinical risk of mortality and severe morbidity from COVID-19 (defined as Clinically Extremely Vulnerable) were identified to be on the Shielded Patient List (SPL). These individuals were asked to stay at home and avoid face-to-face contact for a period of at least 12 weeks during the peak of the pandemic in the UK. This publication considers data relating to emergency admissions, mortality and positive COVID-19 tests for a subset of patients on the English SPL compared with an age-matched sample of the general population. The open data file includes the underlying counts and rates to allow for analysis, modelling and planning to take place to aid the response to the coronavirus pandemic.

Unequal impact of COVID-19: BAME disproportionality The shielded population are those that have been defined by Government on medical grounds as medically vulnerable due to a clinical condition that puts them at High risk of developing complications from COVID-19 infection. Those recommended to shield include: • Organ transplant recipients • Pregnant women with congenital heart conditions • Those with rare diseases such as homozygous sickle cell, SCID and others • Those on immunosuppression therapies • People with specific cancers or those with cancer undergoing chemo/radiotherapy. Camden has so far received the contact details of almost 8,000 residents identified by central Government, with more records likely in future. The details received do not contain the personal characteristics of those on the list, although we have received an overview from North Central London NHS. (note: above is broken down into shielder’s location and BAME ward profile, shielding population by ethnicity, shielded food need and dietary requirements).

Experimental data and Jupyter notebooks supporting the article "A biomimetic approach to shielding from ionizing radiation: the case of melanized fungi".

The repository folder:

experiments contains the recordings from the shielding experiments. The directory name is the date the data was recorded. The files are ASCII text at the native output of WinSPEC for Inspectors format (see supplier website for more information).

geant_apps contains the Geant4 applications and output files from the simulations. Any application can be compiled and installed using cmake, similar to the Geant4 examples.

python contains the Jupyter notebooks to produce the figures and the tables on the aforementioned article.

To compile the Geant4 applications, an installation of Geant4 is needed. The results in the repository were obtain using Geant4 10.5.

This dataset includes all the experimental and FE results presented in the IEEE ICECS 2019 paper "Development of Fully Shielded Soft Inductive Tactile Sensors" (DOI: 10.1109/ICECS46596.2019.8964922). URL of IEEE Xplore: https://ieeexplore.ieee.org/abstract/document/8964922

List of data in this dataset: Fig-2-FE modeling-FS-SITS.xlsx Fig-4-Exp_characterization-FS-SITS.xlsx Fig-5-Exp_Demo-FS-SITS.xlsx

All the data included in this dataset were collected by Dr. Hongbo Wang.

Contact person: Dr. Hongbo Wang, ustcwhb@gmail.com