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Reseach Article

Spread Patterns of Epidemics: Survey

by Siddharth Satish, Smitha G. R.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 1
Year of Publication: 2017
Authors: Siddharth Satish, Smitha G. R.
10.5120/ijca2017915855

Siddharth Satish, Smitha G. R. . Spread Patterns of Epidemics: Survey. International Journal of Computer Applications. 179, 1 ( Dec 2017), 39-41. DOI=10.5120/ijca2017915855

@article{ 10.5120/ijca2017915855,
author = { Siddharth Satish, Smitha G. R. },
title = { Spread Patterns of Epidemics: Survey },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2017 },
volume = { 179 },
number = { 1 },
month = { Dec },
year = { 2017 },
issn = { 0975-8887 },
pages = { 39-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number1/28702-2017915855/ },
doi = { 10.5120/ijca2017915855 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:54:11.235933+05:30
%A Siddharth Satish
%A Smitha G. R.
%T Spread Patterns of Epidemics: Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 1
%P 39-41
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main purpose of this paper is to bring out a distinct strategy to promote and predict the dispersion behaviors of epidemic diseases before they actually happen. With innumerable cases of epidemic outbreaks being recorded in various parts of the world, techniques such as those discussed in this paper, if widely used, under supervision can help to circumvent such occurrences even before they actually happen with accurate predictions. This would also ensure a better coping mechanism is provided to study the spread of such infections and adequate control mechanisms are put in place to prevent loss of human life. Through the course of the paper, the hope is 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 and also predicting future instances in their infancy.

References
  1. Daphne Lopez, M. Gunasekaran, B. Senthil Murugan, Spatial big data analytics of influenza epidemic in Vellore, India, IEEE International Conference on Big Data,10.1109/BigData.2014.7004422, 2014.
  2. Nadra Guizani, Arif Ghafoor., Modelling and evaluation of disease spread behaviours, Wireless Communications, and Mobile Computing Conference, 10.1109/ IWCMC.2014.6906491, 2014.
  3. Konstantinos P. Exarchos et al, “Prediction of coronary atherosclerosis progression using dynamic Bayesian networks”, 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013.
  4. Courtney D. Corley et al, “Disease Prediction Models and Operational Readiness”, in PMC3960139, 2014.
  5. Nicholas Then, et al, “DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced 
Response”, in plos - /journal.pone.0155417, 2016.
  6. João Andrade, Artur Arsenio, Epidemic Spreading Over Social Networks Using Large-scale Biosensors: A Survey, Volume 
5, Pages 922-931, Procedia Technology, 2012.
  7. Lauren N. Carroll, et al, “Visualization and analytics tools for infectious disease epidemiology: A systematic review”, Volume 
51, Pages 287–298, Journal of Biomedical Informatics, 2014.
  8. Baroba.si Albert-Laszlo, Reka Albert, "Emergence of Scaling in Random Networks", Science, vol. 286, pp. 509-512,Oct.1999.
Index Terms

Computer Science
Information Sciences

Keywords

Epidemics Diseases Forecasting Pathogen Detection Bio-surveillance.