Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps
The ongoing COVID-19 pandemic is the first epidemic in human history in which digital contact tracing has been deployed at a global scale. Tracking and quarantining all the contacts of individuals who test positive for a virus can help slow down an epidemic, but the impact of contact tracing is seve...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2022-05-01
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| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.4.023092 |
| _version_ | 1797210726759137280 |
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| author | Aleix Bassolas Andrea Santoro Sandro Sousa Silvia Rognone Vincenzo Nicosia |
| author_facet | Aleix Bassolas Andrea Santoro Sandro Sousa Silvia Rognone Vincenzo Nicosia |
| author_sort | Aleix Bassolas |
| collection | DOAJ |
| description | The ongoing COVID-19 pandemic is the first epidemic in human history in which digital contact tracing has been deployed at a global scale. Tracking and quarantining all the contacts of individuals who test positive for a virus can help slow down an epidemic, but the impact of contact tracing is severely limited by the generally low adoption of contact-tracing apps in the population. We derive here an analytical expression for the effectiveness of contact-tracing app installation strategies in a susceptible-infected-recovered (SIR) model on a given contact graph. We propose a decentralized heuristic to improve the effectiveness of contact tracing under fixed adoption rates, which targets a set of individuals to install contact-tracing apps and can be easily implemented. Simulations on a large number of real-world contact networks confirm that this heuristic represents a feasible alternative to the current state of the art. |
| first_indexed | 2024-04-24T10:15:11Z |
| format | Article |
| id | doaj.art-70fb9d2e655e49929174f81cd0a909ae |
| institution | Directory Open Access Journal |
| issn | 2643-1564 |
| language | English |
| last_indexed | 2024-04-24T10:15:11Z |
| publishDate | 2022-05-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Research |
| spelling | doaj.art-70fb9d2e655e49929174f81cd0a909ae2024-04-12T17:20:33ZengAmerican Physical SocietyPhysical Review Research2643-15642022-05-014202309210.1103/PhysRevResearch.4.023092Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing appsAleix BassolasAndrea SantoroSandro SousaSilvia RognoneVincenzo NicosiaThe ongoing COVID-19 pandemic is the first epidemic in human history in which digital contact tracing has been deployed at a global scale. Tracking and quarantining all the contacts of individuals who test positive for a virus can help slow down an epidemic, but the impact of contact tracing is severely limited by the generally low adoption of contact-tracing apps in the population. We derive here an analytical expression for the effectiveness of contact-tracing app installation strategies in a susceptible-infected-recovered (SIR) model on a given contact graph. We propose a decentralized heuristic to improve the effectiveness of contact tracing under fixed adoption rates, which targets a set of individuals to install contact-tracing apps and can be easily implemented. Simulations on a large number of real-world contact networks confirm that this heuristic represents a feasible alternative to the current state of the art.http://doi.org/10.1103/PhysRevResearch.4.023092 |
| spellingShingle | Aleix Bassolas Andrea Santoro Sandro Sousa Silvia Rognone Vincenzo Nicosia Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps Physical Review Research |
| title | Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps |
| title_full | Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps |
| title_fullStr | Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps |
| title_full_unstemmed | Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps |
| title_short | Optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps |
| title_sort | optimizing the mitigation of epidemic spreading through targeted adoption of contact tracing apps |
| url | http://doi.org/10.1103/PhysRevResearch.4.023092 |
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