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Article: How to avoid a local epidemic becoming a global pandemic

TitleHow to avoid a local epidemic becoming a global pandemic
Authors
Keywordscoupled simulation model
data science
digital twin model
Disease X
epidemiology
Issue Date27-Feb-2023
PublisherNational Academy of Sciences
Citation
Proceedings of the National Academy of Sciences, 2023, v. 120, n. 10 How to Cite?
Abstract

Here, we combine international air travel passenger data with a standard epidemiological model of the initial 3 mo of the COVID-19 pandemic (January through March 2020; toward the end of which the entire world locked down). Using the information available during this initial phase of the pandemic, our model accurately describes the main features of the actual global development of the pandemic demonstrated by the high degree of coherence between the model and global data. The validated model allows for an exploration of alternative policy efficacies (reducing air travel and/or introducing different degrees of compulsory immigration quarantine upon arrival to a country) in delaying the global spread of SARS-CoV-2 and thus is suggestive of similar efficacy in anticipating the spread of future global disease outbreaks. We show that a lesson from the recent pandemic is that reducing air travel globally is more effective in reducing the global spread than adopting immigration quarantine. Reducing air travel out of a source country has the most important effect regarding the spreading of the disease to the rest of the world. Based upon our results, we propose a digital twin as a further developed tool to inform future pandemic decision-making to inform measures intended to control the spread of disease agents of potential future pandemics. We discuss the design criteria for such a digital twin model as well as the feasibility of obtaining access to the necessary online data on international air travel.


Persistent Identifierhttp://hdl.handle.net/10722/333900
ISSN
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 3.737
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorStenseth, Nils-
dc.contributor.authorSchlatte, Rudolf-
dc.contributor.authorLiu, Xiaoli-
dc.contributor.authorPielke, Roger-
dc.contributor.authorLi, Ruiyun-
dc.contributor.authorChen, Bin-
dc.contributor.authorBjørnstad, Ottar-
dc.contributor.authorKusnezov, Dimitri-
dc.contributor.authorGao, George-
dc.contributor.authorFraser, Christophe-
dc.contributor.authorWhittington, Jason-
dc.contributor.authorBai, Yuqi-
dc.contributor.authorDeng, Ke-
dc.contributor.authorGong, Peng-
dc.contributor.authorGuan, Dabo-
dc.contributor.authorXiao, Yixiong-
dc.contributor.authorXu, Bing-
dc.contributor.authorJohnsen, Einar Broch-
dc.date.accessioned2023-10-06T08:40:03Z-
dc.date.available2023-10-06T08:40:03Z-
dc.date.issued2023-02-27-
dc.identifier.citationProceedings of the National Academy of Sciences, 2023, v. 120, n. 10-
dc.identifier.issn0027-8424-
dc.identifier.urihttp://hdl.handle.net/10722/333900-
dc.description.abstract<p>Here, we combine international air travel passenger data with a standard epidemiological model of the initial 3 mo of the COVID-19 pandemic (January through March 2020; toward the end of which the entire world locked down). Using the information available during this initial phase of the pandemic, our model accurately describes the main features of the actual global development of the pandemic demonstrated by the high degree of coherence between the model and global data. The validated model allows for an exploration of alternative policy efficacies (reducing air travel and/or introducing different degrees of compulsory immigration quarantine upon arrival to a country) in delaying the global spread of SARS-CoV-2 and thus is suggestive of similar efficacy in anticipating the spread of future global disease outbreaks. We show that a lesson from the recent pandemic is that reducing air travel globally is more effective in reducing the global spread than adopting immigration quarantine. Reducing air travel out of a source country has the most important effect regarding the spreading of the disease to the rest of the world. Based upon our results, we propose a digital twin as a further developed tool to inform future pandemic decision-making to inform measures intended to control the spread of disease agents of potential future pandemics. We discuss the design criteria for such a digital twin model as well as the feasibility of obtaining access to the necessary online data on international air travel.</p>-
dc.languageeng-
dc.publisherNational Academy of Sciences-
dc.relation.ispartofProceedings of the National Academy of Sciences-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectcoupled simulation model-
dc.subjectdata science-
dc.subjectdigital twin model-
dc.subjectDisease X-
dc.subjectepidemiology-
dc.titleHow to avoid a local epidemic becoming a global pandemic-
dc.typeArticle-
dc.identifier.doi10.1073/pnas.2220080120-
dc.identifier.scopuseid_2-s2.0-85148972954-
dc.identifier.volume120-
dc.identifier.issue10-
dc.identifier.eissn1091-6490-
dc.identifier.isiWOS:001076303900003-
dc.identifier.issnl0027-8424-

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