The spatio-temporal analysis of infectious diseases

传染病时空分析

• 批准号: 340888-2007
• 负责人: Deardon, Robert
• 金额: $ 0.87万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2009
• 资助国家: 加拿大
• 起止时间: 2009-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=429495
• 关键词: spatio; temporal; analysis; infectious; diseases

Infectious diseases are of great importance across society. Epidemic outbreaks of diseases such as measles, SARS, influenza or foot-and-mouth disease, can pose direct threats to public health and/or have serious economic effects. In order to control such diseases, it is vital to understand how the disease spreads geographically over time, and what factors lead to some individuals becoming infected, and some not. To this end, a new class of mathematical models, individual-level models (ILMs) for infectious diseases, has been developed. These models are intuitive, flexible, and have been shown to accurately describe the patterns of previously observed epidemics over space and time. However, ILMs are relatively new and so there are many infectious disease problems for which specific models do not yet exist.

传染病在整个社会都非常重要。麻疹、非典、流感或口蹄疫等疾病的流行可能对公众健康构成直接威胁和/或产生严重的经济影响。为了控制这些疾病，至关重要的是要了解疾病是如何随着时间的推移在地理上传播的，以及是什么因素导致一些人被感染，另一些人不被感染。为此，发展了一类新的数学模型--传染病的个体水平模型(ILM)。这些模型直观、灵活，并已被证明准确地描述了以前观察到的流行病在空间和时间上的模式。然而，ILM相对较新，因此存在许多传染病问题，目前还不存在针对这些问题的具体模型。