{"title":"Techniques and Approaches for Disease Outbreak Prediction: A Survey","authors":"A. Bharambe, D. Kalbande","doi":"10.1145/2909067.2909085","DOIUrl":null,"url":null,"abstract":"As on today, due to rise in pollution and dense population in India, there has been an increase in health related issues with respect to spreading disease. The recent outbreak of diseases like HINI, dengue, malaria etc. have made people to focus on ways to minimize the effect of infectious disease. This can be achieved if early prediction and detection of such diseases are possible. Research is being carried out in building various prediction models to forecast the outbreak of such epidemics. While the traditional techniques were useful in giving the results, inputs from social media enabled us to detect the presence, prevalence and spread of these disease in a much early manner. Social networking Medias and their blogs have also been used for prediction. To handle such variety and size of data, it is required to design a system using big data approach for forecasting. Big Data is one of the need of the hour area of research that is become increasingly popular in prediction. This paper focuses on the survey carried out on available techniques and presents a unified approach to prepare a conceptual forecasting model.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Women In Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2909067.2909085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
As on today, due to rise in pollution and dense population in India, there has been an increase in health related issues with respect to spreading disease. The recent outbreak of diseases like HINI, dengue, malaria etc. have made people to focus on ways to minimize the effect of infectious disease. This can be achieved if early prediction and detection of such diseases are possible. Research is being carried out in building various prediction models to forecast the outbreak of such epidemics. While the traditional techniques were useful in giving the results, inputs from social media enabled us to detect the presence, prevalence and spread of these disease in a much early manner. Social networking Medias and their blogs have also been used for prediction. To handle such variety and size of data, it is required to design a system using big data approach for forecasting. Big Data is one of the need of the hour area of research that is become increasingly popular in prediction. This paper focuses on the survey carried out on available techniques and presents a unified approach to prepare a conceptual forecasting model.