This paper is published in Volume-3, Issue-2, 2017
Area
Big Data
Author
Siddharth Satish, Smitha G. R
Org/Univ
R. V College Of Engineering, Bangalore, Karnataka, India
Keywords
Epidemic Diseases, Disease Forecast, Pathogen Detection, Bio Surveillance, Epidemic Breakout Detection.
Citations
IEEE
Siddharth Satish, Smitha G. R. Epidemic Disease Detection and Forecasting: A Survey, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Siddharth Satish, Smitha G. R (2017). Epidemic Disease Detection and Forecasting: A Survey. International Journal of Advance Research, Ideas and Innovations in Technology, 3(2) www.IJARIIT.com.
MLA
Siddharth Satish, Smitha G. R. "Epidemic Disease Detection and Forecasting: A Survey." International Journal of Advance Research, Ideas and Innovations in Technology 3.2 (2017). www.IJARIIT.com.
Siddharth Satish, Smitha G. R. Epidemic Disease Detection and Forecasting: A Survey, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Siddharth Satish, Smitha G. R (2017). Epidemic Disease Detection and Forecasting: A Survey. International Journal of Advance Research, Ideas and Innovations in Technology, 3(2) www.IJARIIT.com.
MLA
Siddharth Satish, Smitha G. R. "Epidemic Disease Detection and Forecasting: A Survey." International Journal of Advance Research, Ideas and Innovations in Technology 3.2 (2017). www.IJARIIT.com.
Abstract
The objective of this paper is to present a precise methodology to project and forecast the spread behaviors of epidemic diseases well before they occur. With numerous cases of widespread outbreaks of epidemics being reported in densely populated areas, these methodologies can help restrict the outbreak only to a small confined area. This would ensure that a better coping mechanism is provided to study the spread of infectious diseases and adequate control mechanisms are provided to reduce casualties in the form of human death. Through the course of this paper, we hope to develop a well-defined prediction methodology that can predict the likeliness of an individual being affected by a particular epidemic through assessing of early symptoms.