A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure

Roni Hen Gabzi*, Tal Patalon, Noam Shomron, Sivan Gazit

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number1975
JournalJournal of Personalized Medicine
Volume12
Issue number12
DOIs
StatePublished - Dec 2022

Funding

FundersFunder number
CBRN
Edmond J. Safra Center for Bioinformatics at Tel-Aviv University
Koret-UC Berkeley-Tel Aviv University
Office of Assistant Minister of Defense for Chemical, Biological, Radiological and Nuclear
Research and Innovation Framework Programme
UCSF-Tel Aviv University
Foundation Fighting Blindness
Yonsei University
Tel Aviv University
Queensland Brain Institute
Ministry of Science and Technology, Israel
Horizon 2020
Ministry of Defense

    Keywords

    • COVID
    • SARS-CoV-2
    • electronic medical records
    • household
    • infectious diseases
    • resistance

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