Epidemiological data challenges: planning for a more robust future through data standards
- 1Los Alamos National Laboratory (DOE), United States
- 2University of Colorado Boulder, United States
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.
Keywords: Computational epidemiology, Public Health, Data, Informatics, disease modeling, disease surveillance
Received: 17 Jul 2018;
Accepted: 01 Nov 2018.
Edited by:Jimmy T. Efird, University of Newcastle, Australia
Reviewed by:Marco Brandizi, Rothamsted Research (BBSRC), United Kingdom
Reza M. Salek, International Agency For Research On Cancer (IARC), France
Vimal K. Singh, Amity University Gurgaon, India
Copyright: © 2018 Fairchild, Tasseff, Khalsa, Generous, Daughton, Velappan, Priedhorsky and Deshpande. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Geoffrey Fairchild, Los Alamos National Laboratory (DOE), Los Alamos, New Mexico, United States, email@example.com