Epidemic Diseases Forestall Module using Data Science and SIR Algorithms

Main Article Content

Nivedita Shimbre
Tanvi Patil
Rutuja Late
Kshitij Jagtap
Amogh Patil

Abstract

This survey paper is intended to prevent epidemic diseases and pandemic diseases. According to the WHO every year in the world over 17 million people die due to this type of disease. Epidemic diseases have lower transmission rate than pandemic diseases and they spread in a bounded area. On the other hand, pandemic diseases have higher transmission rate and it can easily spread in an immense area. We can control this type of disease in its initial stages before it becomes a fatal disease like covid-19. Lack of knowledge in peoples and inefficient systems used by higher authorities in that region are the main reasons to spread diseases in larger areas. But using data science and the epidemic compartment models it’s possible to control infectious diseases in its initial stages. For different diseases there are different compartment algorithms that are able to estimate the number of cases in the future. These models often use ordinary differential equations for predicting things. Using data science, we are able to find what are key factors responsible for the spreading of that particular disease.

Article Details

How to Cite
Shimbre, N. ., Patil, T. ., Late, R. ., Jagtap, K. ., & Patil, A. . (2023). Epidemic Diseases Forestall Module using Data Science and SIR Algorithms. International Journal on Recent and Innovation Trends in Computing and Communication, 11(8), 285–292. https://doi.org/10.17762/ijritcc.v11i8.7956
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Articles

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