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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 9, 2020.
Abstract: On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, general behavior and how it affects, people do not know. Initial few cases reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people. At any given time during a flu epidemic, firstly, should know the number of people who are infected. Second, to know the numbers who have been infected and have recovered, because these people now have immunity to the disease. Well established SIR modeling methodology is used to develop a predictive model in order to understand the key factors that impact the COVID-19 transmission.
DeepaRani Gopagoni and P V Lakshmi, “Susceptible, Infectious and Recovered (SIR Model) Predictive Model to Understand the Key Factors of COVID-19 Transmission” International Journal of Advanced Computer Science and Applications(IJACSA), 11(9), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110934
@article{Gopagoni2020,
title = {Susceptible, Infectious and Recovered (SIR Model) Predictive Model to Understand the Key Factors of COVID-19 Transmission},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110934},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110934},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {9},
author = {DeepaRani Gopagoni and P V Lakshmi}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.