Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic
This study estimates the consequences of risk propagation, such as that of COVID-19, using network-agent dynamics. Given several scenarios, the network-agent model provides critical insights into infection risk using a model-driven approach to interconnected interventions. The simulation results sug...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/7382033 |
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| _version_ | 1832551220126941184 |
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| author | Chulwook Park |
| author_facet | Chulwook Park |
| author_sort | Chulwook Park |
| collection | DOAJ |
| description | This study estimates the consequences of risk propagation, such as that of COVID-19, using network-agent dynamics. Given several scenarios, the network-agent model provides critical insights into infection risk using a model-driven approach to interconnected interventions. The simulation results suggest that employing a nonevolutionary governing structure with evolutionary individual interaction parameters guided by testing can help suppress outbreaks to levels below the standard critical-care capacity. Furthermore, setting the protection level as the macroscale and the shrinking of individual interactions as the microscale, the effects of social distancing on transmission rates are reflected in the disease model. In addition, the parameters that reflect the best feasible scenarios can be determined. These findings are relevant to COVID-19 pandemic policies wherein interconnected interventions reduce the socioeconomic costs of risk propagation. |
| format | Article |
| id | doaj-art-dd6b1c44d12541f0a6c2d5ae410e39e5 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-dd6b1c44d12541f0a6c2d5ae410e39e52025-02-03T06:04:40ZengWileyComplexity1099-05262022-01-01202210.1155/2022/7382033Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent DynamicChulwook Park0International Institute for Applied Systems Analysis (IIASA)This study estimates the consequences of risk propagation, such as that of COVID-19, using network-agent dynamics. Given several scenarios, the network-agent model provides critical insights into infection risk using a model-driven approach to interconnected interventions. The simulation results suggest that employing a nonevolutionary governing structure with evolutionary individual interaction parameters guided by testing can help suppress outbreaks to levels below the standard critical-care capacity. Furthermore, setting the protection level as the macroscale and the shrinking of individual interactions as the microscale, the effects of social distancing on transmission rates are reflected in the disease model. In addition, the parameters that reflect the best feasible scenarios can be determined. These findings are relevant to COVID-19 pandemic policies wherein interconnected interventions reduce the socioeconomic costs of risk propagation.http://dx.doi.org/10.1155/2022/7382033 |
| spellingShingle | Chulwook Park Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic Complexity |
| title | Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic |
| title_full | Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic |
| title_fullStr | Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic |
| title_full_unstemmed | Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic |
| title_short | Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic |
| title_sort | potential consequence of interconnected intervention against systemic risk covid 19 via a model driven network agent dynamic |
| url | http://dx.doi.org/10.1155/2022/7382033 |
| work_keys_str_mv | AT chulwookpark potentialconsequenceofinterconnectedinterventionagainstsystemicriskcovid19viaamodeldrivennetworkagentdynamic |