Peak Infection Time for a Networked SIR Epidemic with Opinion Dynamics
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2021
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| _version_ | 1866909653101707264 |
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| author | She, Baike Leung, Humphrey C. H. Sundaram, Shreyas Paré, Philip E. |
| author_facet | She, Baike Leung, Humphrey C. H. Sundaram, Shreyas Paré, Philip E. |
| contents | We propose an SIR epidemic model coupled with opinion dynamics to study an epidemic and opinions spreading in a network of communities. Our model couples networked SIR epidemic dynamics with opinions towards the severity of the epidemic, and vice versa. We develop an epidemic-opinion based threshold condition to capture the moment when a weighted average of the epidemic states starts to decrease exponentially fast over the network, namely the peak infection time. We define an effective reproduction number to characterize the behavior of the model through the peak infection time. We use both analytical and simulation-based results to illustrate that the opinions reflect the recovered levels within the communities after the epidemic dies out. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2109_14135 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Peak Infection Time for a Networked SIR Epidemic with Opinion Dynamics She, Baike Leung, Humphrey C. H. Sundaram, Shreyas Paré, Philip E. Systems and Control We propose an SIR epidemic model coupled with opinion dynamics to study an epidemic and opinions spreading in a network of communities. Our model couples networked SIR epidemic dynamics with opinions towards the severity of the epidemic, and vice versa. We develop an epidemic-opinion based threshold condition to capture the moment when a weighted average of the epidemic states starts to decrease exponentially fast over the network, namely the peak infection time. We define an effective reproduction number to characterize the behavior of the model through the peak infection time. We use both analytical and simulation-based results to illustrate that the opinions reflect the recovered levels within the communities after the epidemic dies out. |
| title | Peak Infection Time for a Networked SIR Epidemic with Opinion Dynamics |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2109.14135 |