The Epidemiology and Epistemology of Flu Outbreak in North America

America is a major hotspot for flu outbreak. The disease burden from flu infection is undermined because of its symptoms’ complexity and high level of similarity with SARS, MERS and COVID-19 infections. The epidemiology of influenza using contemporary data to develop stochastic computer algorithms capable of backcasting and forecasting seasonal trends, pattern recognition, and disease quantification, was the aim of this research.Three (3) models were developed, programmed and optimized for influenza epidemiology using contemporary data. They are ETA-REX-EMM-Flu-Vac (VS-01), ETA-REX-EMM-Flu-Epidemics (VS-02), and ETA-REX-EMM-Flu-Deaths (VS-03).The models had very high rating for disease prediction accuracy, model efficiency, and output quality (R2 = 97.70-100%, Adj.R2 = 97.60-99.90%, and Pred.R2 = 97.20-99.35%). The difference between contemporary data and simulated results were insignificant at P<0.001 [T-test = “ns”, (0%)0≠r<1.0(100%)]. It was estimated that 22.8% of US population will suffer from influenza in 2022, and a deficit of -7.1% (i.e., 15.7%) should be expected by 2050. The probability of dying from flu will reduce from 0.098% (2012) to 0.017% (2050).