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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File: | <div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Fairchild FrontPubHealth2018 6.jpg|240px]]</div> | ||
'''"[[Journal: | '''"[[Journal:Epidemiological data challenges: Planning for a more robust future through data standards|Epidemiological data challenges: Planning for a more robust future through data standards]]"''' | ||
[[ | Accessible [[Epidemiology|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. ('''[[Journal:Epidemiological data challenges: Planning for a more robust future through data standards|Full article...]]''')<br /> | ||
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Revision as of 00:02, 17 June 2021
"Epidemiological data challenges: Planning for a more robust future through data standards"
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. (Full article...)
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