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Abstract

The introduction and spread of emerging infectious diseases is increasing in both prevalence and scale. Whether naturally, accidentally or maliciously introduced, the substantial uncertainty surrounding the emergence of novel viruses, specifically where they may come from and how they will spread, demands robust and quantifiably validated outbreak control policies that can be implemented in real time. This work presents a novel mathematical modeling framework that integrates both outbreak dynamics and outbreak control into a decision support tool for mitigating infectious disease pandemics that spread through passenger air travel. An ensemble of border control strategies that exploit properties of the air traffic network structure and expected outbreak behavior are proposed. A stochastic metapopulation epidemic model is developed to evaluate and rank the control strategies based on their effectiveness in reducing the spread of outbreaks. Sensitivity analyses are conducted to illustrate the robustness of the proposed control strategies across a range of outbreak scenarios, and a case study is presented for the 2009 H1N1 influenza pandemic. This study highlights the importance of strategically allocating outbreak control resources, and the results can be used to identify the most robust border control policy that can be implemented in the early stages of an outbreak.

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Original document

The different versions of the original document can be found in:

https://doaj.org/toc/2045-2322
http://www.nature.com/articles/s41598-019-38665-w,
http://dx.doi.org/10.1038/s41598-019-38665-w under the license https://creativecommons.org/licenses/by/4.0
http://dx.doi.org/10.1101/414185
https://biorxiv.org/content/biorxiv/early/2018/09/12/414185.full-text.pdf,
https://academic.microsoft.com/#/detail/2892086906
http://www.nature.com/articles/s41598-019-38665-w,
https://www.ncbi.nlm.nih.gov/pubmed/30778107,
https://europepmc.org/abstract/MED/30778107,
https://academic.microsoft.com/#/detail/2952343975


DOIS: 10.1038/s41598-019-38665-w 10.1101/414185

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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.1038/s41598-019-38665-w
Licence: Other

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