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Reseach Article

Simple Techniques to Predict the Onset of Pandemics

by Sunitha Suresh, Rajan Chattamvelli
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 28
Year of Publication: 2022
Authors: Sunitha Suresh, Rajan Chattamvelli
10.5120/ijca2022922352

Sunitha Suresh, Rajan Chattamvelli . Simple Techniques to Predict the Onset of Pandemics. International Journal of Computer Applications. 184, 28 ( Sep 2022), 22-25. DOI=10.5120/ijca2022922352

@article{ 10.5120/ijca2022922352,
author = { Sunitha Suresh, Rajan Chattamvelli },
title = { Simple Techniques to Predict the Onset of Pandemics },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2022 },
volume = { 184 },
number = { 28 },
month = { Sep },
year = { 2022 },
issn = { 0975-8887 },
pages = { 22-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number28/32494-2022922352/ },
doi = { 10.5120/ijca2022922352 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:22:40.495112+05:30
%A Sunitha Suresh
%A Rajan Chattamvelli
%T Simple Techniques to Predict the Onset of Pandemics
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 28
%P 22-25
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Accurate identification and prediction of underlying factors of pandemics (like COVID-19) are research priorities, but require elaborate data analysis on a global scale. Due to the large number of mutations of coronavirus that have already ensued during a short span of 2+ years, it is absurd to assume that further mutations will cease to exist. The place and time of future mutations are unpredictable. However, simple visualization techniques can sometimes reveal data peculiarities and provide quick answers to the onset of new mutations, thereby avoiding an expensive analytics run. This paper is aimed at exploring how visualization plots play an essential role to expose hidden relationships among a multitude of variables involved, and how it can be effectively utilized to predict new waves in selected geographic regions.

References
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Index Terms

Computer Science
Information Sciences

Keywords

COVID-19