Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards

Frontiers in Public Health

Geoffrey Fairchild¹ 

关键词: data;    computational epidemiology;    public health;    disease modeling;    informatics;    disease surveillance;   

DOI  :  10.3389/fpubh.2018.00336

学科分类：卫生学

来源: Frontiers

【 摘 要 】

Accessible epidemiological data are of great value for emergency preparedness and response, understanding disease progression through a population, and building statistical and mechanistic disease models that enable forecasting. The status quo, however, renders acquiring and using such data difficult in practice. In many cases, a primary way of obtaining epidemiological data is through the internet, but the methods by which the data are presented to the public often differ drastically among institutions. As a result, there is a strong need for better data sharing practices. This paper identifies, in detail and with examples, the three key challenges one encounters when attempting to acquire and use epidemiological data: (1) interfaces, (2) data formatting, and (3) reporting. These challenges are used to provide suggestions and guidance for improvement as these systems evolve in the future. If these suggested data and interface recommendations were adhered to, epidemiological and public health analysis, modeling, and informatics work would be significantly streamlined, which can in turn yield better public health decision-making capabilities.

【 授权许可】

CC BY