TY - JOUR
T1 - A HYBRID MATHEMATICAL MODEL FOR AN OPTIMAL BORDER CLOSURE POLICY DURING A PANDEMIC
AU - Lazebnik, Teddy
AU - Shami, Labib
AU - Bunimovich-Mendrazitsky, Svetlana
N1 - Publisher Copyright:
© 2023 T. Lazebnik et al.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - 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.
AB - 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.
KW - health care
KW - international bio-tourism policy
KW - multi-agent reinforcement learning
KW - spatio-temporal SIR model
UR - http://www.scopus.com/inward/record.url?scp=85180553792&partnerID=8YFLogxK
U2 - 10.34768/amcs-2023-0042
DO - 10.34768/amcs-2023-0042
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AN - SCOPUS:85180553792
SN - 1641-876X
VL - 33
SP - 583
EP - 601
JO - International Journal of Applied Mathematics and Computer Science
JF - International Journal of Applied Mathematics and Computer Science
IS - 4
ER -