Analysis of COVID-19 Vaccinations and Symptom Mapping Diagnostic Technique for Viral Diseases: Using Data Analytics, Machine Learning, and Artificial Intelligence

Abstract

To analyze, understand, and measure the COVID-19 vaccination outlook in a developing country as Nigeria; and the non-clinical analysis, diagnosis, treatment and management of COVID-19, and other Viral Diseases, using Data/Machine Learning (ML)/Artificial Intelligence (AI), Analytical Tools, and Methodologies. Using current and historical data from validated open source data stores, analysis was carried out on COVID-19 vaccination and related economic, demographic, and geo-climatic data for a developing country, Nigeria and selected countries from all continents of the world. The methodical and data-driven analyses were carried out using the following Data/Artificial Intelligence (AI) methodologies and algorithms: Excel Data Analytics, Multivariate Linear Regression Analysis method in Machine Learning (ML) Engineering, Symptom Mapping Analysis, Gray System Analysis. The COVID-19 vaccinations expectedly does reduce the number of active COVID cases and the amount or number of vaccinations for a developing country as Nigeria is affected by a good number of economic, demographic, and geo-climatic factors; and so COVID-19 vaccinations strategies must be unique to a country and categories of countries and take into account influencing factors not only limited to number of active COVID cases. The strategies (including vaccinations roll-out) to eliminate COVID-19 can be better understood and managed for increased productivity and faster success rate in the fight against COVID-19. Medical practitioners can provide even more efficient diagnosis and treatment of viral diseases; and also patients can carry out personalized cost effective diagnosis and treatment/management of viral diseases, with also the advises of medical practitioners.