Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic
An infodemic—an outpouring of information, including misleading and also fake news—is accompanying the current pandemic caused by SARS-CoV-2. In the absence of valid therapeutic approaches, behavioral responses may seriously affect the social dynamics of contagion, so the infodemic may cause confusi...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2022-02-01
|
| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.4.013158 |
| _version_ | 1797210825009659904 |
|---|---|
| author | Valeria d'Andrea Oriol Artime Nicola Castaldo Pierluigi Sacco Riccardo Gallotti Manlio De Domenico |
| author_facet | Valeria d'Andrea Oriol Artime Nicola Castaldo Pierluigi Sacco Riccardo Gallotti Manlio De Domenico |
| author_sort | Valeria d'Andrea |
| collection | DOAJ |
| description | An infodemic—an outpouring of information, including misleading and also fake news—is accompanying the current pandemic caused by SARS-CoV-2. In the absence of valid therapeutic approaches, behavioral responses may seriously affect the social dynamics of contagion, so the infodemic may cause confusion and disorientation in the public, leading to possible individually and socially harmful choices. This new phenomenon requires specific modeling efforts to better understand the complex intertwining of the epidemic and infodemic components of a pandemic crisis, with a view to building an integrative public health approach. We propose three models, from epidemiology to game theory, as potential candidates for the onset of the infodemics and statistically assess their accuracy in reproducing real infodemic waves observed in a data set of 390 million tweets collected worldwide. Our results show that evolutionary game-theory models are the most suitable ones to reproduce the observed infodemic modulations around the onset of the local epidemic wave. Furthermore, we find that the number of confirmed COVID-19 reported cases in each country and worldwide are driving the modeling dynamics with opposite effects. |
| first_indexed | 2024-04-24T10:16:44Z |
| format | Article |
| id | doaj.art-e5ef568819334ac7a72d0ea8c901bc67 |
| institution | Directory Open Access Journal |
| issn | 2643-1564 |
| language | English |
| last_indexed | 2024-04-24T10:16:44Z |
| publishDate | 2022-02-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Research |
| spelling | doaj.art-e5ef568819334ac7a72d0ea8c901bc672024-04-12T17:18:31ZengAmerican Physical SocietyPhysical Review Research2643-15642022-02-014101315810.1103/PhysRevResearch.4.013158Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemicValeria d'AndreaOriol ArtimeNicola CastaldoPierluigi SaccoRiccardo GallottiManlio De DomenicoAn infodemic—an outpouring of information, including misleading and also fake news—is accompanying the current pandemic caused by SARS-CoV-2. In the absence of valid therapeutic approaches, behavioral responses may seriously affect the social dynamics of contagion, so the infodemic may cause confusion and disorientation in the public, leading to possible individually and socially harmful choices. This new phenomenon requires specific modeling efforts to better understand the complex intertwining of the epidemic and infodemic components of a pandemic crisis, with a view to building an integrative public health approach. We propose three models, from epidemiology to game theory, as potential candidates for the onset of the infodemics and statistically assess their accuracy in reproducing real infodemic waves observed in a data set of 390 million tweets collected worldwide. Our results show that evolutionary game-theory models are the most suitable ones to reproduce the observed infodemic modulations around the onset of the local epidemic wave. Furthermore, we find that the number of confirmed COVID-19 reported cases in each country and worldwide are driving the modeling dynamics with opposite effects.http://doi.org/10.1103/PhysRevResearch.4.013158 |
| spellingShingle | Valeria d'Andrea Oriol Artime Nicola Castaldo Pierluigi Sacco Riccardo Gallotti Manlio De Domenico Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic Physical Review Research |
| title | Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic |
| title_full | Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic |
| title_fullStr | Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic |
| title_full_unstemmed | Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic |
| title_short | Epidemic proximity and imitation dynamics drive infodemic waves during the COVID-19 pandemic |
| title_sort | epidemic proximity and imitation dynamics drive infodemic waves during the covid 19 pandemic |
| url | http://doi.org/10.1103/PhysRevResearch.4.013158 |
| work_keys_str_mv | AT valeriadandrea epidemicproximityandimitationdynamicsdriveinfodemicwavesduringthecovid19pandemic AT oriolartime epidemicproximityandimitationdynamicsdriveinfodemicwavesduringthecovid19pandemic AT nicolacastaldo epidemicproximityandimitationdynamicsdriveinfodemicwavesduringthecovid19pandemic AT pierluigisacco epidemicproximityandimitationdynamicsdriveinfodemicwavesduringthecovid19pandemic AT riccardogallotti epidemicproximityandimitationdynamicsdriveinfodemicwavesduringthecovid19pandemic AT manliodedomenico epidemicproximityandimitationdynamicsdriveinfodemicwavesduringthecovid19pandemic |