Hybrid Modeling of Ebola Propagation.

Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering Pub Date : 2019-10-01 Epub Date: 2019-12-26 DOI:10.1109/bibe.2019.00044

Cyrus Tanade, Nathanael Pate, Elianna Paljug, Ryan A Hoffman, May D Wang

引用次数: 5

Abstract

The Ebola virus disease (EVD) epidemic that occurred in West Africa between 2014-16 resulted in over 28,000 cases and 11,000 deaths - one of the deadliest to date. A generalized model of the spatiotemporal progression of EVD for Liberia, Guinea, and Sierra Leone in 2014-16 remains elusive. There is also a disconnect in the literature on which interventions are most effective in curbing disease progression. To solve these two key issues, we designed a hybrid agent-based and compartmental model that switches from one paradigm to the other on a stochastic threshold. We modeled disease progression with promising accuracy using WHO datasets.

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埃博拉病毒传播的混合模型。

2014年至2016年期间在西非发生的埃博拉病毒病(EVD)疫情导致2.8万多例病例和1.1万人死亡，是迄今为止最致命的疫情之一。2014- 2016年利比里亚、几内亚和塞拉利昂埃博拉病毒病时空发展的广义模型仍然难以确定。关于哪些干预措施在抑制疾病进展方面最有效，文献中也存在脱节。为了解决这两个关键问题，我们设计了一个基于智能体和隔间的混合模型，该模型在随机阈值上从一种范式切换到另一种范式。我们使用世卫组织数据集对疾病进展进行了建模，准确度很高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering

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