Title: Corona Virus Disease (COVID 19): Analysis and Design of an Alert and Real-time Tracking System
Author(s): Chinecherem Umezuruike, Wilson Nwankwo, Prisca Tibenderana, John Patrick Assimwe, Muhirwa Ronald
Year 2020
Publisher: International Journal of Emerging Trends in Engineering Research Volume 8. No. 5
File: PDF
Keywords: COVID-19 Corona Virus Epidemic Pandemic Infectious disease Informatics

Microscopic agents such as viruses, protozoa, bacteria, fungi, etc. are common aetiologic agents in most infections affecting man. Whereas some infectious diseases are localized owing to the unique geospatial and biochemical characteristics of the aetiologic agents, others are not bound by such restrictions hence their manifest tendencies towards evolving an epidemic or even a pandemic. CoVID-19 sprang up in Wuhan China in November 2019 and was declared a pandemic by the in January 2020 World Health Organization (WHO). Like the Spanish flu of 1918 that claimed millions of lives, the COVID-19 has caused the demise of thousands with China, Italy, Spain and the USA having the highest statistics on infection and mortality rates. Regardless of existing sophisticated technologies and medical science, the spread has continued to surge high. Tracking of suspected carriers (cases) has been difficult, thereby increasing the risk of spread. As a novel infection, real-time information management beyond national geographical borders is vital to the success of any disease management campaign. Currently, information on the Covid-19 and applicable management procedures in most countries is limited thus

creating a knowledge and management gap among the populace and even health management personnel especially in areas susceptible to the pandemic. In response to the aforementioned, this paper proposes an Alert and Tracking System (CVATS) that enhances information dissemination, disease management, tracking of cases, and management of confirmed cases. The system follows an object-oriented approach in articulating the various actors and evolves a model that could be implemented on both web and mobile platforms. On mobile platform, it employs google maps and could be used to track persons as well as geographical areas with prevalence of infections.


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