Modeling adaptive forward-looking behavior in epidemics on networks
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866929691206615040 |
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| author | Fard, Lorenzo Amir Nemati Bisin, Alberto Starnini, Michele Tizzoni, Michele |
| author_facet | Fard, Lorenzo Amir Nemati Bisin, Alberto Starnini, Michele Tizzoni, Michele |
| contents | Incorporating decision-making dynamics during an outbreak poses a challenge for epidemiology, faced by several modeling approaches siloed by different disciplines. We propose an epi-economic model where high-frequency choices of individuals respond to the infection dynamics over heterogeneous networks. Maintaining a rational forward-looking component to individual choices, agents follow a behavioral rule-of-thumb in the face of limited perceived forecasting precision in a highly uncertain epidemic environment. We describe the resulting equilibrium behavior of the epidemic by analytical expressions depending on the epidemic conditions. We study existence and welfare of equilibrium, identifying a fundamental negative externality. We also sign analytically the effects of the behavioral rule-of-thumb at different phases of the epidemic and characterize some comparative statics. Through numerical simulations, we contrast different information structures: global awareness -- where individuals only know the prevalence of the disease in the population -- with local awareness, where individuals know the prevalence in their neighborhood. We show that agents' behavioral response through forward-looking choice can flatten the epidemic curve, but local awareness, by triggering highly heterogeneous behavioral responses, more effectively curbs the disease compared to global awareness. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2301_04947 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Modeling adaptive forward-looking behavior in epidemics on networks Fard, Lorenzo Amir Nemati Bisin, Alberto Starnini, Michele Tizzoni, Michele Physics and Society Theoretical Economics Incorporating decision-making dynamics during an outbreak poses a challenge for epidemiology, faced by several modeling approaches siloed by different disciplines. We propose an epi-economic model where high-frequency choices of individuals respond to the infection dynamics over heterogeneous networks. Maintaining a rational forward-looking component to individual choices, agents follow a behavioral rule-of-thumb in the face of limited perceived forecasting precision in a highly uncertain epidemic environment. We describe the resulting equilibrium behavior of the epidemic by analytical expressions depending on the epidemic conditions. We study existence and welfare of equilibrium, identifying a fundamental negative externality. We also sign analytically the effects of the behavioral rule-of-thumb at different phases of the epidemic and characterize some comparative statics. Through numerical simulations, we contrast different information structures: global awareness -- where individuals only know the prevalence of the disease in the population -- with local awareness, where individuals know the prevalence in their neighborhood. We show that agents' behavioral response through forward-looking choice can flatten the epidemic curve, but local awareness, by triggering highly heterogeneous behavioral responses, more effectively curbs the disease compared to global awareness. |
| title | Modeling adaptive forward-looking behavior in epidemics on networks |
| topic | Physics and Society Theoretical Economics |
| url | https://arxiv.org/abs/2301.04947 |