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A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure
This report describes the development of a data-driven approach for identifying individuals who tested negative to a SARS-CoV-2 infection, despite their residence with individuals who had confirmed infections. Household studies have demonstrated efficiency in evaluating exposure to SARS-CoV-2. Lever...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784910/ https://www.ncbi.nlm.nih.gov/pubmed/36556196 http://dx.doi.org/10.3390/jpm12121975 |
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author | Hen Gabzi, Roni Patalon, Tal Shomron, Noam Gazit, Sivan |
author_facet | Hen Gabzi, Roni Patalon, Tal Shomron, Noam Gazit, Sivan |
author_sort | Hen Gabzi, Roni |
collection | PubMed |
description | This report describes the development of a data-driven approach for identifying individuals who tested negative to a SARS-CoV-2 infection, despite their residence with individuals who had confirmed infections. Household studies have demonstrated efficiency in evaluating exposure to SARS-CoV-2. Leveraging earlier studies based on the household unit, our analysis utilized close contacts in order to trace chains of infection and to subsequently categorize TEFLONs, an acronym for Timely Exposed to Family members Leaving One Not infected. We used over one million anonymized electronic medical records, retrieved from Maccabi Healthcare Services’ centralized computerized database from March 2020 to March 2022. The analysis yielded 252 TEFLONs, who were probably at very high risk of infection and yet, demonstrated clinical resistance. The exposure extent in each household positively correlated with household size, reflecting the in-house rolling transmission event. Our approach can be easily implemented in other clinical fields and should spur further research of clinical resistance to various infections. |
format | Online Article Text |
id | pubmed-9784910 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97849102022-12-24 A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure Hen Gabzi, Roni Patalon, Tal Shomron, Noam Gazit, Sivan J Pers Med Article This report describes the development of a data-driven approach for identifying individuals who tested negative to a SARS-CoV-2 infection, despite their residence with individuals who had confirmed infections. Household studies have demonstrated efficiency in evaluating exposure to SARS-CoV-2. Leveraging earlier studies based on the household unit, our analysis utilized close contacts in order to trace chains of infection and to subsequently categorize TEFLONs, an acronym for Timely Exposed to Family members Leaving One Not infected. We used over one million anonymized electronic medical records, retrieved from Maccabi Healthcare Services’ centralized computerized database from March 2020 to March 2022. The analysis yielded 252 TEFLONs, who were probably at very high risk of infection and yet, demonstrated clinical resistance. The exposure extent in each household positively correlated with household size, reflecting the in-house rolling transmission event. Our approach can be easily implemented in other clinical fields and should spur further research of clinical resistance to various infections. MDPI 2022-11-30 /pmc/articles/PMC9784910/ /pubmed/36556196 http://dx.doi.org/10.3390/jpm12121975 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hen Gabzi, Roni Patalon, Tal Shomron, Noam Gazit, Sivan A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure |
title | A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure |
title_full | A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure |
title_fullStr | A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure |
title_full_unstemmed | A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure |
title_short | A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure |
title_sort | data-driven strategy for identifying individuals resistant to sars-cov-2 virus under in-household exposure |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784910/ https://www.ncbi.nlm.nih.gov/pubmed/36556196 http://dx.doi.org/10.3390/jpm12121975 |
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