Mathematical modeling of infectious disease dynamics

被引:265
作者
Siettos, Constantinos I. [1 ]
Russo, Lucia [2 ]
机构
[1] Natl Tech Univ Athens, Sch Appl Math & Phys Sci, Athens, Greece
[2] CNR, Naples, Italy
关键词
mathematical epidemiology; statistical models; dynamical models; agent-based models; machine learning models; INFLUENZA MORTALITY; BAYESIAN DETECTION; SURVEILLANCE DATA; EPIDEMICS; NETWORKS; LIKELIHOOD; PNEUMONIA; OUTBREAKS; MALARIA; RESISTANCE;
D O I
10.4161/viru.24041
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
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.
引用
收藏
页码:295 / 306
页数:12
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