Probabilistic analysis of contracting Ebola virus using contextual intelligence

Authors: 
A. Gopalakrishnan and K.M. Kavi.
Keywords: 
Ebola, iDid app, Contextual intelligence, Susceptibility, Risk factor, Bayes theorem
Abstract: 

The West African countries witnessed an "extraordinary" outbreak of the Ebola virus in August 2014. It was declared to be a Public Health Emergency of International Concern (PHEIC) by the World Health Organization (WHO). Due to the complex nature of the outbreak, Centers for Disease Control and Prevention (CDC) has created interim guidance for monitoring people potentially exposed to Ebola and for evaluating their intended travel and restricting the movements of carriers when needed. Tools to evaluate the risk of individuals and groups of individuals contracting the disease could mitigate the fear and anxiety. Our goal is to understand and analyze the nature of risk an individual would posses when he/she comes in contact with a carrier. This paper presents a tool that makes use of contextual data intelligence to predict the risk factor of individuals who come in contact with the carrier.

Publish Date: 
Monday, July 25, 2016
Venue: 
2nd International conference on health informatics and medical systems (HiMS'16), Las Vegas, NV
Paper URL: 
csrl.unt.edu/kavi/Research/Ebola-2016.pdf