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Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment
Alberto Ferrari1, Enrico Santus2, Davide Cirillo3,4
1FROM Research Foundation, Papa Giovanni XXIII Hospital, Bergamo, Italy. aferrari34@yahoo.com.
NPJ Digital Medicine
|January 15, 2021
Summary
Mobile app contact-tracing can help control COVID-19 spread. However, its effectiveness depends on population density, with higher density areas posing greater containment challenges for this digital health intervention.
Area of Science:
- Epidemiology
- Public Health
- Computational Modeling
Background:
- Contact-tracing via mobile apps is proposed for COVID-19 containment and lockdown management.
- Debate exists regarding the efficacy of app-based contact-tracing, particularly considering regional demographic variations.
Purpose of the Study:
- To evaluate the impact of a contact-tracing app on COVID-19 epidemics using an expanded SIR model.
- To assess the influence of region-specific population densities and user fractions on containment efficacy.
Main Methods:
- Developed an expanded SIR model incorporating region-specific population densities.
- Simulated various scenarios using demographic and mobility data from Italy and Spain.
- Varied baseline contact rates, population densities, and the fraction of app users.
Main Results:
- App-mediated contact-tracing can mitigate epidemics even with a small user fraction, supporting symptomatic case isolation.
- Higher user fractions demonstrated the potential to suppress the epidemic.
- Containment proved more challenging in higher population density areas, indicating context-specific limitations.
Conclusions:
- App-mediated contact-tracing is a valuable mitigation measure for COVID-19.
- Region-specific demographic and mobility factors are crucial for maximizing the efficacy of containment policies.
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