一种基于网络的内布拉斯加州百日咳传播分区模型。
A Network-Based Compartmental Model For The Spread Of Whooping Cough In Nebraska.
作者信息
Ameri Kimia, Cooper Kathryn D
机构信息
College of Information Science and Technology, University of Nebraska at Omaha, Omaha, Nebraska, United States.
出版信息
AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:388-397. eCollection 2019.
Outbreaks of pertussis have increased over the past few years, drawing the attention of health care providers. Un- derstanding the transmission mechanisms of contagious disease is critically important, but depends on many intricate factors including pathogen and host environment, exposed population, and their activities. In this work, we try to improve upon the prediction model for the exposed population. The number of whooping cough reported cases in Nebraska between 2000-2017 was gathered. The standard Susceptible-Exposed-Infected-Recovered (SEIR) model is used to predict the infected numbers. The results show that the SEIR model prediction for the number of infected indi- viduals is much higher than the actual number. To overcome this problem, the Network Based-SEIR model is proposed, and is able to estimate the number of infected more accurately than the classic SEIR model.
在过去几年中，百日咳疫情有所增加，引起了医疗保健提供者的关注。了解传染病的传播机制至关重要，但这取决于许多复杂因素，包括病原体和宿主环境、暴露人群及其活动。在这项工作中，我们试图改进针对暴露人群的预测模型。收集了2000年至2017年内布拉斯加州百日咳报告病例数。使用标准的易感-暴露-感染-康复（SEIR）模型来预测感染人数。结果表明，SEIR模型对感染个体数量的预测远高于实际数量。为克服这一问题，提出了基于网络的SEIR模型，该模型能够比经典SEIR模型更准确地估计感染人数。
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