A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic
During a global health crisis, a country’s borders are a weak point through which carriers from countries with high morbidity rates can enter, endangering the health of the local community and undermining the authorities’ efforts to prevent the spread of the pathogen. Therefore, most countries have...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-12-01
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| Series: | International Journal of Applied Mathematics and Computer Science |
| Subjects: | |
| Online Access: | https://doi.org/10.34768/amcs-2023-0042 |
| _version_ | 1797375875829727232 |
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| author | Lazebnik Teddy Shami Labib Bunimovich-Mendrazitsky Svetlana |
| author_facet | Lazebnik Teddy Shami Labib Bunimovich-Mendrazitsky Svetlana |
| author_sort | Lazebnik Teddy |
| collection | DOAJ |
| description | During a global health crisis, a country’s borders are a weak point through which carriers from countries with high morbidity rates can enter, endangering the health of the local community and undermining the authorities’ efforts to prevent the spread of the pathogen. Therefore, most countries have adopted some level of border closure policies as one of the first steps in handling pandemics. However, this step involves a significant economic loss, especially for countries that rely on tourism as a source of income. We developed a pioneering model to help decision-makers determine the optimal border closure policies during a health crisis that minimize the magnitude of the outbreak and maximize the revenue of the tourism industry. This approach is based on a hybrid mathematical model that consists of an epidemiological sub-model with tourism and a pandemic-focused economic sub-model, which relies on elements from the field of artificial intelligence to provide policymakers with a data-driven model for a border closure strategy for tourism during a global pandemic. |
| first_indexed | 2024-03-08T19:30:34Z |
| format | Article |
| id | doaj.art-8fa9545123c24061b7c87a5fd60c49ae |
| institution | Directory Open Access Journal |
| issn | 2083-8492 |
| language | English |
| last_indexed | 2024-03-08T19:30:34Z |
| publishDate | 2023-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | International Journal of Applied Mathematics and Computer Science |
| spelling | doaj.art-8fa9545123c24061b7c87a5fd60c49ae2023-12-26T07:43:37ZengSciendoInternational Journal of Applied Mathematics and Computer Science2083-84922023-12-0133458360110.34768/amcs-2023-0042A Hybrid Mathematical Model for an Optimal Border Closure Policy During a PandemicLazebnik Teddy0Shami Labib1Bunimovich-Mendrazitsky Svetlana2aDepartment of Mathematics, Ariel University, 3 Kiryat Hamada St., 40700Ariel, IsraelbDepartment of Economics, Western Galilee College, Hamichlala Rd., 2412101Acre, IsraelaDepartment of Mathematics, Ariel University, 3 Kiryat Hamada St., 40700Ariel, IsraelDuring a global health crisis, a country’s borders are a weak point through which carriers from countries with high morbidity rates can enter, endangering the health of the local community and undermining the authorities’ efforts to prevent the spread of the pathogen. Therefore, most countries have adopted some level of border closure policies as one of the first steps in handling pandemics. However, this step involves a significant economic loss, especially for countries that rely on tourism as a source of income. We developed a pioneering model to help decision-makers determine the optimal border closure policies during a health crisis that minimize the magnitude of the outbreak and maximize the revenue of the tourism industry. This approach is based on a hybrid mathematical model that consists of an epidemiological sub-model with tourism and a pandemic-focused economic sub-model, which relies on elements from the field of artificial intelligence to provide policymakers with a data-driven model for a border closure strategy for tourism during a global pandemic.https://doi.org/10.34768/amcs-2023-0042health carespatio-temporal sir modelinternational bio-tourism policymulti-agent reinforcement learning |
| spellingShingle | Lazebnik Teddy Shami Labib Bunimovich-Mendrazitsky Svetlana A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic International Journal of Applied Mathematics and Computer Science health care spatio-temporal sir model international bio-tourism policy multi-agent reinforcement learning |
| title | A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic |
| title_full | A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic |
| title_fullStr | A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic |
| title_full_unstemmed | A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic |
| title_short | A Hybrid Mathematical Model for an Optimal Border Closure Policy During a Pandemic |
| title_sort | hybrid mathematical model for an optimal border closure policy during a pandemic |
| topic | health care spatio-temporal sir model international bio-tourism policy multi-agent reinforcement learning |
| url | https://doi.org/10.34768/amcs-2023-0042 |
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