Mathematical epidemiology in a data-rich world

被引：5
|
作者：
Arino, Julien [1 ]
机构：
[1] Univ Manitoba, Dept Math & Data Sci NEXUS, Winnipeg, MB, Canada
来源：
INFECTIOUS DISEASE MODELLING | 2020年 / 5卷
基金：
加拿大自然科学与工程研究理事会;
关键词：
Mathematical epidemiology; Data acquisition; Open data;
D O I：
10.1016/j.idm.2019.12.008
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
I discuss the acquisition and use of "background" data in mathematical epidemiology models, advocating a proactive approach to the incorporation of said data. I illustrate various mechanisms for acquiring data, mainly from open data sources. I also discuss incorporating this data into models. (c) 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页码：161 / 188
页数：28
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