TY - JOUR
T1 - Universal Shelter-in-Place Versus Advanced Automated Contact Tracing and Targeted Isolation
T2 - A Case for 21st-Century Technologies for SARS-CoV-2 and Future Pandemics
AU - Nuzzo, Andrea
AU - Tan, Can Ozan
AU - Raskar, Ramesh
AU - DeSimone, Daniel C.
AU - Kapa, Suraj
AU - Gupta, Rajiv
N1 - Publisher Copyright:
© 2020 Mayo Foundation for Medical Education and Research
PY - 2020/9
Y1 - 2020/9
N2 - 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.
AB - 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.
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U2 - 10.1016/j.mayocp.2020.06.027
DO - 10.1016/j.mayocp.2020.06.027
M3 - Article
C2 - 32861334
AN - SCOPUS:85089799814
SN - 0025-6196
VL - 95
SP - 1898
EP - 1905
JO - Mayo Clinic Proceedings
JF - Mayo Clinic Proceedings
IS - 9
ER -