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

Abstract

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.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
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  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); Defense Threat Reduction Agency (DTRA) (United States)
OSTI Identifier:
1489945
Report Number(s):
LA-UR-17-21702
Journal ID: ISSN 2296-2565
Grant/Contract Number:  
89233218CNA000001; CB3656; CB10007
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Public Health
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2296-2565
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 97 MATHEMATICS AND COMPUTING; epidemiology, data, standardization

Citation Formats

Fairchild, Geoffrey, Tasseff, Byron, Khalsa, Hari, Generous, Nicholas, Daughton, Ashlynn R., Velappan, Nileena, Priedhorsky, Reid, and Deshpande, Alina. Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards. United States: N. p., 2018. Web. doi:10.3389/fpubh.2018.00336.
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Fairchild, Geoffrey, Tasseff, Byron, Khalsa, Hari, Generous, Nicholas, Daughton, Ashlynn R., Velappan, Nileena, Priedhorsky, Reid, & Deshpande, Alina. Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards. United States. https://doi.org/10.3389/fpubh.2018.00336
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Fairchild, Geoffrey, Tasseff, Byron, Khalsa, Hari, Generous, Nicholas, Daughton, Ashlynn R., Velappan, Nileena, Priedhorsky, Reid, and Deshpande, Alina. Fri . "Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards". United States. https://doi.org/10.3389/fpubh.2018.00336. https://www.osti.gov/servlets/purl/1489945.
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@article{osti_1489945,
title = {Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards},
author = {Fairchild, Geoffrey and Tasseff, Byron and Khalsa, Hari and Generous, Nicholas and Daughton, Ashlynn R. and Velappan, Nileena and Priedhorsky, Reid and Deshpande, Alina},
abstractNote = {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.},
doi = {10.3389/fpubh.2018.00336},
journal = {Frontiers in Public Health},
number = ,
volume = 6,
place = {United States},
year = {Fri Nov 23 00:00:00 EST 2018},
month = {Fri Nov 23 00:00:00 EST 2018}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.3389/fpubh.2018.00336
Copyright Statement
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Citation Metrics:
Cited by: 16 works
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Figures / Tables:

Figure 1 Figure 1: Screenshot showing part of the mosquito-borne illness epidemiological bulletin list. This is the most current and complete list, with data available through the 38th week of 2016.
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    Works referencing / citing this record:

    Google Health Trends performance reflecting dengue incidence for the Brazilian states
    journal, March 2020

    Google Health Trends performance reflecting dengue incidence for the Brazilian states
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