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Abstract
This paper explores the effectiveness of a COVID-19 contact tracing smartphone app using an agent-based model. The model simulates the spread of COVID-19 in a population, considering factors like app adoption rate, testing capacity, and behavioral responses. Results show that the app significantly reduces infection rates with sufficient testing capacity or when prioritizing symptomatic cases. High app usage with inadequate testing can be counterproductive due to increased demand overwhelming the system. Efficient testing policies and increased capacity are crucial for the app's success.
Publisher
Scientific Reports
Published On
Dec 17, 2020
Authors
Jonatan Almagor, Stefano Picascia
Tags
COVID-19
contact tracing
smartphone app
agent-based model
infection rates
testing capacity
behavioral responses

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