Your browser doesn't support javascript.
Modeling of network based digital contact tracing and testing strategies, including the pre-exposure notification system, for the COVID-19 pandemic.
Xu, Daniel.
  • Xu D; MIT PRIMES-USA, Massachusetts Institute of Technology, Cambridge, MA, United States of America. Electronic address: danielxu@mit.edu.
Math Biosci ; 338: 108645, 2021 08.
Article in English | MEDLINE | ID: covidwho-1492387
ABSTRACT
With more than 1.7 million COVID-19 deaths, identifying effective measures to prevent COVID-19 is a top priority. We developed a mathematical model to simulate the COVID-19 pandemic with digital contact tracing and testing strategies. The model uses a real-world social network generated from a high-resolution contact data set of 180 students. This model incorporates infectivity variations, test sensitivities, incubation period, and asymptomatic cases. We present a method to extend the weighted temporal social network and present simulations on a network of 5000 students. The purpose of this work is to investigate optimal quarantine rules and testing strategies with digital contact tracing. The results show that the traditional strategy of quarantining direct contacts reduces infections by less than 20% without sufficient testing. Periodic testing every 2 weeks without contact tracing reduces infections by less than 3%. A variety of strategies are discussed including testing second and third degree contacts and the pre-exposure notification system, which acts as a social radar warning users how far they are from COVID-19. The most effective strategy discussed in this work was combining the pre-exposure notification system with testing second and third degree contacts. This strategy reduces infections by 18.3% when 30% of the population uses the app, 45.2% when 50% of the population uses the app, 72.1% when 70% of the population uses the app, and 86.8% when 95% of the population uses the app. When simulating the model on an extended network of 5000 students, the results are similar with the contact tracing app reducing infections by up to 79%.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Document Type: Article Main subject: Contact Tracing / Disease Notification / Social Network Analysis / COVID-19 / Models, Theoretical Subject: Contact Tracing / Disease Notification / Social Network Analysis / COVID-19 / Models, Theoretical Type of study: Prognostic study / Screening study Language: English Journal: Math Biosci Year: 2021

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Document Type: Article Main subject: Contact Tracing / Disease Notification / Social Network Analysis / COVID-19 / Models, Theoretical Subject: Contact Tracing / Disease Notification / Social Network Analysis / COVID-19 / Models, Theoretical Type of study: Prognostic study / Screening study Language: English Journal: Math Biosci Year: 2021
...