Epidemic outbreak detection and prediction using machine learning

Abstract

Epidemic diseases are the contagious diseases that are possible to be spread into the entire nation if the contagion measurement had reached the outbreak level and manage to wipe out the entire population. Epidemic Disease can have possible chances to spread into entire city if the contagion measurement reached to outbreak level.Epidemic disease outbreak had caused nowadays community to raise their great concern over the infectious disease controlling, preventing and handling methods to diminish the disease dissemination percentage and infected area. The aim of the proposed system is to predict the spread of an epidemic by analyzing the conditions in the areas where people are affected.This project is focused on Various diseases,such as Influenza,Zika Virus,Malaria,Dengue which is an infectious disease, caused by exposure to the virus. The prediction will be done by analyzing the spread based on the movement of the disease through the population. It will be implemented using Machine Learning techniques to predict the spread in particular geographical regions.An approach model to predict the Disease area by using Text Analysis.Epidemic model use the power of Social Media data and this data help to provide the probability score of a Outbreak of Epidemic.The Data is extract on daily bases which make the output of the model more accurate.we use SVM Algorithm and various Machine Learning Technique. Keywords: Epidemic Diseases,Disease Forecast,Prediction algorithm, Epidemic spread,sentiment analysis,Machine Learning ,social media, Epidemic Breakout Detection, public health,NLTK.