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Enhancing Decision Making during a Public Health Emergency: Use of Natural Language Processing to Process Unstructured Data

Using Natural Language Processing on social media data to enhance decision makers’ response to public health emergencies

Executive Summary

Post Ebola in 2016, CDC pilot-tested the use of Political, Economic, Social, Technological, Legal and Environmental (PESTLE) analysis. PESTLE is a promising framework that can give decision makers a bird’s eye view of the nature of these changing variables as well as the risks and opportunities derived from them. The analysis helped CDC response leaders identify areas for improvement and think about risks and opportunities that can be anticipated. We propose to design a tool that uses natural language processing (NLP) to categorize the large amount of unstructured texts to inform effective incident management leadership decision making and advise CDC leadership on risks and opportunities.

Team Members

Bobby Rasulina (team lead), CDC
Shawn Chiang. CDC

Milestones

October 2018: Project selected into the HHS Ignite Accelerator
March 2019: Time in Accelerator Began
June 2019: Time in Accelerator Ended