Analytic Hierarchy Process Model for the Diagnosis of Typhoid Fever

Typhoid fever is a global health problem, which seems neglected. Still, it is responsible for significant levels of morbidity in many regions of the world, with about 12 million cases annually, and about 600,000 fatalities. Diagnosis of typhoid poses a lot of challenges because its clinical presentation is confused with those of many other febrile infections such as malaria, yellow fever, etc. In addition, most developing countries do not have adequate bacteriology laboratories for further investigations. Decision support systems (DSSs) have been known to increase the efficiency and effectiveness of the diagnosis process, in addition to improving access; however, most existing decision support models for the diagnosis of diseases have largely focused on ‘non-tropical’ conditions. An effective decision support model for the diagnosis of tropical diseases can only be developed through the engineering of experiential knowledge of physicians who are experts in the management of such conditions. In this study, we mined the experiential knowledge of twenty-five tropical disease specialist physicians to develop a decision support system based on the Analytic Hierarchy Process (AHP). The resulting model was tested based on 2044 patient data. Our model successfully determined the occurrence (or otherwise) of typhoid fever in 78.91% of the cases, demonstrating the utility of AHP in the diagnosis of typhoid fever.