Internet of Healthcare Things (IoHTs) Technology to Strengthen Nigeria Health Systems: A predictive technique for Syndromic Surveillance of Suspected cases of Filovirus Diseases in Africa.

Abstract

Infectious disease should be early recognised, treated timely and adequately, otherwise it spreads and leads to many other complications that is capable of causing health hazards, which can relatively become a cause of multiple cases of death. The emergence and re-emerging of Filovirus diseases especially in African continent are alarmingly threatening the healthcare workers and poses greater fatality rate. Ebola Virus Disease (EVD) and Marburg Virus Disease (MVD) are in the family of Filovirus infectious disease, that is predicted to continue emerging especially in regions where the reservoir host species are known. The upsurge of Internet of Things (IoTs) in Healthcare has provision very many technological advancement and positive solutions to healthcare challenges across the globe especially in many developed countries of the world. Internet of Healthcare Things (IoHTS) is a pool of innovative technological medical related devices that are connected together to provide seemingly control management, monitoring and surveillance, predictive detection and information sharing, etc that is capable of improving quality of healthcare delivery. Thus, early recognition, and timely detection and response to highly contagious and deadly virus is critically important in this modern era. This research study employs the Case-Study methodology to present an investigative framework of the use of Internet of Healthcare Things (IoHTs) technique to detect, predict and real-time report of -re-emerging Filovirus diseases in order to provide early recognition, quick response and intervention management with improved contact tracing tool of Geographical Information System (GIS) for active surveillance for informed decision-making on emergency healthcare delivery while minimizing the spread of the viruses. The study proposes to apply the emerging IoTs innovations to symptomatically detect and predict particular Filovirus (MVD or EVD) based on the defined physiological condition systematically presented. The objectives of the study are not limited to properly review the existing frameworks suitable for the research study, and design the propose architectural framework for the performance improvement of the system. The outcome is to provide a scientific way of detecting and predicting re-emerging Filovirus Diseases, and reporting such data in real-time for improve rapid response to emergency health intervention. The system structure is logically abreast with the technique to provide Suspected individuals with opportunity to early, easily and speedily detect and predict (know) their health condition during any Filovirus (EVD and MVD) outbreaks, and significantly minimize the spread of the diseases.

Keywords:          Ebola Virus Disease, Marburg Virus Disease, Internet of Healthcare Things, Smart Health Care, Filovirus, Predictive Detection, Syndromic Surveillance and Real-Time Reporting.

DOI: 10.7176/CEIS/13-2-05

Publication date:April 30^th 2022