Design and Implementation of Intelligent System for Detection and Analysis of Ebola Disease

Abstract

Ebola virus disease is a hemorrhagic fever that has a near 100%
fatality rate if not detected on time and properly managed. Between
December 2013 and September 6, 2015, Africa and few other
countries such as Italy and Spain witnessed the worst outbreak of the
disease with 28,183 confirmed cases out of which 11,306 died. In an
untiring effort to eradicate this pandemic, scientists have sought
different measures for treating and caring for infected persons while
also preventing further transmission of the disease. Hitherto, there
still exist cases of transmission among humans especially patient-tohealth care provider transmission. This project addresses the
problem using visual programming language for diagnosing the
disease. Requirement gathering exercise and specification was done
through interviews with health care providers, site visit to Ebola
treatment center and review of literature and Ebola registries. Expert
system concepts with Visual Basic programming language were
adopted in the development of the system. Reliable inferences were
made regardless of the Ebola case scenario that was used in the
testing of the expert system. The system showed that reduction in
person-to-person transmission of Ebola virus disease can be
achieved if probable suspects are identified and diagnosed on time
using computer applications that eliminates physical contact with
suspects or infected materials and fluids. For confirmed suspects, the
system recommends laboratory test as a final proof of the infection.
Using an interactive diagnosis expert system for detecting Ebola
cases is a fast and safer avenue through which Ebola transmissions;
especially human-to-human transmissions could be reduced.