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Mathematical modeling of infectious disease dynamics

机译:传染病动力学的数学模型

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摘要

Over the last years, an intensive worldwide effort is speeding up the developments in the establishment of a global surveillance network for combating pandemics of emergent and re-emergent infectious diseases. Scientists from different fields extending from medicine and molecular biology to computer science and applied mathematics have teamed up for rapid assessment of potentially urgent situations. Toward this aim mathematical modeling plays an important role in efforts that focus on predicting, assessing, and controlling potential outbreaks. To better understand and model the contagious dynamics the impact of numerous variables ranging from the micro host-pathogen level to host-to-host interactions, as well as prevailing ecological, social, economic, and demographic factors across the globe have to be analyzed and thoroughly studied. Here, we present and discuss the main approaches that are used for the surveillance and modeling of infectious disease dynamics. We present the basic concepts underpinning their implementation and practice and for each category we give an annotated list of representative works.
机译:在过去的几年中,全球范围内的不懈努力正在加快建立全球监测网络的发展速度,以应对突发性和复发性传染病的大流行。从医学和分子生物学到计算机科学和应用数学的不同领域的科学家已经联手对潜在紧急情况进行快速评估。为了实现这一目标,数学建模在致力于预测,评估和控制潜在疾病爆发的努力中起着重要作用。为了更好地理解和模拟传染性动力学,必须分析从微观宿主-病原体水平到宿主之间的相互作用等众多变量的影响,以及全球主要的生态,社会,经济和人口统计学因素,并深入研究。在这里,我们介绍并讨论用于监视和模拟传染病动态的主要方法。我们介绍了实现和实践的基本概念,并为每个类别提供了一个带注释的代表性作品列表。

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