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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.
Nuzzo, Andrea; Tan, Can Ozan; Raskar, Ramesh; DeSimone, Daniel C; Kapa, Suraj; Gupta, Rajiv.
  • Nuzzo A; GlaxoSmithKline US, Collegeville, PA. Electronic address: andrea.8.nuzzo@gsk.com.
  • Tan CO; Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA; Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, MA.
  • Raskar R; Media Lab, Massachusetts Institute of Technology, Boston, MA.
  • DeSimone DC; Division of Infectious Disease, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
  • Kapa S; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
  • Gupta R; Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, MA.
Mayo Clin Proc ; 95(9): 1898-1905, 2020 09.
Article in English | MEDLINE | ID: covidwho-735304
ABSTRACT

OBJECTIVE:

To model and compare effect of digital contact tracing versus shelter-in-place on severe acute respiratory syndrome - coronavirus 2 (SARS-CoV-2) spread.

METHODS:

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. Under influence of these variables, the number of individuals infected, exposed, and isolated were estimated.

RESULTS:

Without any intervention, a high rate of infection (>10 million) with early peak is predicted. Shelter-in-place results in rapid decline in infection rate at the expense of impacting a large population segment. The AACT model achieves reduction in infected and exposed individuals similar to shelter-in-place without impacting a large number of individuals. For example, a 50% AACT adoption rate mimics a shelter-in-place order for 40% of the population and results in a greater than 90% decrease in peak number of infections. However, as compared to shelter-in-place, with AACT significantly fewer individuals would be isolated.

CONCLUSION:

Wide adoption of digital contact tracing can mitigate infection spread similar to universal shelter-in-place, but with considerably fewer individuals isolated.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Software / Communicable Disease Control / Contact Tracing / Coronavirus Infections / Pandemics Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Mayo Clin Proc Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Software / Communicable Disease Control / Contact Tracing / Coronavirus Infections / Pandemics Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Mayo Clin Proc Year: 2020 Document Type: Article