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.
