Data informed epidemiological-behavioural modelling
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913961524330496 |
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| author | Proverbio, Daniele Tessarin, Riccardo Giordano, Giulia |
| author_facet | Proverbio, Daniele Tessarin, Riccardo Giordano, Giulia |
| contents | Augmenting classical epidemiological models with information from the social sciences helps unveil the interplay between contagion dynamics and social responses. However, multidisciplinary integration of social analysis and epidemiological modelling is often challenging, due to scarcity of vast and reliable data sources and because ad hoc modelling assumptions may not reproduce empirically observed patters. Here, we test the hypothesis that awareness and information spreading straightforwardly translates into behavioural responses, analysing empirical data to generate insights about their dynamics and relationships. We employ such results to build a data-informed behavioural-epidemiological model that elucidates the impact of compliant behaviours and the role of centralised regulations in mitigating epidemics. We investigate model properties and its benefits in integrating theoretical modelling and data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_10472 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data informed epidemiological-behavioural modelling Proverbio, Daniele Tessarin, Riccardo Giordano, Giulia Physics and Society Quantitative Methods Augmenting classical epidemiological models with information from the social sciences helps unveil the interplay between contagion dynamics and social responses. However, multidisciplinary integration of social analysis and epidemiological modelling is often challenging, due to scarcity of vast and reliable data sources and because ad hoc modelling assumptions may not reproduce empirically observed patters. Here, we test the hypothesis that awareness and information spreading straightforwardly translates into behavioural responses, analysing empirical data to generate insights about their dynamics and relationships. We employ such results to build a data-informed behavioural-epidemiological model that elucidates the impact of compliant behaviours and the role of centralised regulations in mitigating epidemics. We investigate model properties and its benefits in integrating theoretical modelling and data. |
| title | Data informed epidemiological-behavioural modelling |
| topic | Physics and Society Quantitative Methods |
| url | https://arxiv.org/abs/2410.10472 |