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

机译：流行病学数据挑战：通过数据标准规划更健壮的未来

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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.
机译：可获取的流行病学数据对于应急准备和响应，了解整个人群的疾病进展以及建立能够进行预测的统计和机制疾病模型具有重要价值。然而，现状使得在实践中难以获取和使用这种数据。在许多情况下，获取流行病学数据的主要方法是通过互联网，但是在机构之间，将数据呈现给公众的方法通常大不相同。结果，强烈需要更好的数据共享实践。本文通过示例详细地确定了尝试获取和使用流行病学数据时遇到的三个主要挑战：（1）接口，（2）数据格式和（3）报告。这些挑战用于为将来随着这些系统的发展提供改进的建议和指导。如果坚持这些建议的数据和界面建议，则将大大简化流行病学和公共卫生分析，建模和信息学工作，从而可以提高公共卫生决策能力。

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