Epidemo A Machine Learning Regression-Based
Abstract
In recent years, the world has witnessed the devastating consequences of disease outbreaks, highlighting the urgent need for effective epidemic management. An epidemic signifies the rapid transmission of illness to a substantial portion of a population within a short timeframe. The proposed system offers a proactive approach to this challenge by leveraging advanced Machine Learning (ML) regression tools. By analyzing diverse data sources such as historical disease trends, environmental conditions, and human behaviors, the system predicts the onset and spread of diseases, providing crucial early warnings for public health authorities and communities. Through timely implementation of preventive measures informed by these forecasts, authorities can mitigate the impact of epidemics, safeguard public health, and alleviate strain on healthcare systems. This proactive strategy underscores the importance of early intervention and data-driven approaches in combating and controlling disease outbreaks.
Keywords:
Epidemic ManagementPublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Dr.Sinciya P.O, Aaron Varughese Bino, Anamin Fathima Anish, Aathira Krishna, Dona Maria Joseph, Unveiling Stress through Facial Expressions: A Literature Review on Detection Methods , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Heizel Ann Joseph, Drishya K V, Deni Deni Tom Jacob, Ibin Sunny Mathew, Bini M Issac, GERIATRI C PLUS Your One Stop Solution for Old Aged Care , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Parvathy V A, Irfana Parveen C A, Alisha K A, Reshma P R, Manu Krishna C P, Detection of Diabetic Retinopathy and Glaucoma using Deep Learning , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Angelina Kanjooparambil Joseph, Angel Rose Sanoj, Bewin P. G., Fabeela Ali Rawther, A Review on Prompt Engineering in Agriculture , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Juby Mathew, Maria Jojo, Neha Ann Samson, Noell Biju Michael, Ron T Alumkal, PulseSync: IoT-Enabled Monitoring and Predictive Analytics for Healthcare , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Joel Judish, Samrudh Salas, Farhaan Zuhair, Muhammed Zakkariya M, Juby Mathew, SkinGuard: An EfficientNet Model for Skin Cancer and M-pox Detection , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Aaron Samuel Mathew , Adhil P, Alan Siby, Alwyn Jospeh , Real Time Scheduling And Navigation Portal , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Blesson Thomas Abraham, Hariprasad K P, Fiyona Ann Sojan, Diya Mathew, Anishamol Abraham, SmartCook -Your Personalized Cooking Assistant , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Rohan Malka, Jerin Joseph Abraham, Jobcy Johnson, Sobin Saju, Febin Sam Philip, Aju Mathew George, S.N.Kumar , Green Waste Utilization for Sustainable Energy Engineering Application: A Path towards Green Circular Economy , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Ansamol Varghese, Milu Mary Jacob, Shilpa Mariam James, Reeba Rebecca Varghese, Vimal sajan George, A Review on Integrating IoT and Robotics for Improved Care , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
You may also start an advanced similarity search for this article.
