<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>95(9)</volume><submitter>Nuzzo A</submitter><pubmed_abstract>&lt;h4>Objective&lt;/h4>To model and compare effect of digital contact tracing versus shelter-in-place on severe acute respiratory syndrome - coronavirus 2 (SARS-CoV-2) spread.&lt;h4>Methods&lt;/h4>Using a classical epidemiologic framework and parameters estimated from literature published between February 1, 2020, and May 25, 2020, we modeled two non-pharmacologic interventions - shelter-in-place and digital contact tracing - to curb spread of SARS-CoV-2. For contact tracing, we assumed an advanced automated contact tracing (AACT) application that sends alerts to individuals advising self-isolation based on individual exposure profile. Model parameters included percentage population ordered to shelter-in-place, adoption rate of AACT, and percentage individuals who appropriately follow recommendations</pubmed_abstract><journal>Mayo Clinic proceedings</journal><pagination>1898-1905</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7306713</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Universal Shelter-in-Place Versus Advanced Automated Contact Tracing and Targeted Isolation: A Case for 21st-Century Technologies for SARS-CoV-2 and Future Pandemics.</pubmed_title><pmcid>PMC7306713</pmcid><pubmed_authors>Gupta R</pubmed_authors><pubmed_authors>Raskar R</pubmed_authors><pubmed_authors>Nuzzo A</pubmed_authors><pubmed_authors>Tan CO</pubmed_authors><pubmed_authors>Kapa S</pubmed_authors><pubmed_authors>DeSimone DC</pubmed_authors></additional><is_claimable>false</is_claimable><name>Universal Shelter-in-Place Versus Advanced Automated Contact Tracing and Targeted Isolation: A Case for 21st-Century Technologies for SARS-CoV-2 and Future Pandemics.</name><description>&lt;h4>Objective&lt;/h4>To model and compare effect of digital contact tracing versus shelter-in-place on severe acute respiratory syndrome - coronavirus 2 (SARS-CoV-2) spread.&lt;h4>Methods&lt;/h4>Using a classical epidemiologic framework and parameters estimated from literature published between February 1, 2020, and May 25, 2020, we modeled two non-pharmacologic interventions - shelter-in-place and digital contact tracing - to curb spread of SARS-CoV-2. For contact tracing, we assumed an advanced automated contact tracing (AACT) application that sends alerts to individuals advising self-isolation based on individual exposure profile. Model parameters included percentage population ordered to shelter-in-place, adoption rate of AACT, and percentage individuals who appropriately follow recommendations</description><dates><release>2020-01-01T00:00:00Z</release><publication>2020 Sep</publication><modification>2025-04-05T15:19:02.819Z</modification><creation>2020-08-30T07:18:51Z</creation></dates><accession>S-EPMC7306713</accession><cross_references><pubmed>32861334</pubmed><doi>10.1016/j.mayocp.2020.06.027</doi></cross_references></HashMap>