Research Article
Using Data Assimilation Technique and Epidemic Model to Predict TB Epidemic
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 128 - Issue 9 |
| Published: October 2015 |
| Authors: Himanshu Gupta, Kamal Kant Verma, Punit Sharma |
10.5120/ijca2015906625
|
Himanshu Gupta, Kamal Kant Verma, Punit Sharma . Using Data Assimilation Technique and Epidemic Model to Predict TB Epidemic. International Journal of Computer Applications. 128, 9 (October 2015), 1-5. DOI=10.5120/ijca2015906625
@article{ 10.5120/ijca2015906625,
author = { Himanshu Gupta,Kamal Kant Verma,Punit Sharma },
title = { Using Data Assimilation Technique and Epidemic Model to Predict TB Epidemic },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 128 },
number = { 9 },
pages = { 1-5 },
doi = { 10.5120/ijca2015906625 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Himanshu Gupta
%A Kamal Kant Verma
%A Punit Sharma
%T Using Data Assimilation Technique and Epidemic Model to Predict TB Epidemic%T
%J International Journal of Computer Applications
%V 128
%N 9
%P 1-5
%R 10.5120/ijca2015906625
%I Foundation of Computer Science (FCS), NY, USA
Abstract
People of India are very susceptible to many infectious diseases like malaria, TB, HIV etc. There are many epidemic models that are used to predict new cases of disease. Some of the popular epidemic models are SI (Susceptible-Infectious), SIR (Susceptible-Infectious-Recovered), SIRS, SIS etc. In this research quarterly data of TB disease in Uttarakhand (India) for 7 years is collected and on the basis of this data new infected population in the next quarter is predicted using SIR epidemic model and data assimilation technique (Ensemble Kalman Filter). Analysis and implementation is done in MATLAB. Results show good agreement to measured values.
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