{"title":"Current Trends in Social-Media based Disease Outbreak Prediction & Surveillance Systems","authors":"Soofi Shafiya, S. Jabin","doi":"10.1109/REEDCON57544.2023.10151369","DOIUrl":null,"url":null,"abstract":"The purpose of disease surveillance is to monitor and predict public health emergencies or to predict outbreak of any disease. It can be achieved by analyzing disease related data being collected by various government agencies/hospitals. Public health officials keep track of information, predict possible outbreaks, and keep an eye on emergency situations using this data. In the recent past, social media has grown enough to have deep impact on people’s life specially during time of pandemic. Analysis of social media data offers meaningful insights towards disease surveillance. It helps in figuring out how much people know about diseases and how they feel about official/government health related communications and responses. In this study, we present review of most recent works which used social media as a data source for the prevention & prediction of outbreaks. Additionally, we discuss methods that are being implemented on social media data towards designing robust disease outbreak prediction models. This study emphasizes how social media has helped during various outbreaks in the past. A bibliometric analysis has also been done over the most recent & relevant literature collected from source SCOPUS.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REEDCON57544.2023.10151369","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The purpose of disease surveillance is to monitor and predict public health emergencies or to predict outbreak of any disease. It can be achieved by analyzing disease related data being collected by various government agencies/hospitals. Public health officials keep track of information, predict possible outbreaks, and keep an eye on emergency situations using this data. In the recent past, social media has grown enough to have deep impact on people’s life specially during time of pandemic. Analysis of social media data offers meaningful insights towards disease surveillance. It helps in figuring out how much people know about diseases and how they feel about official/government health related communications and responses. In this study, we present review of most recent works which used social media as a data source for the prevention & prediction of outbreaks. Additionally, we discuss methods that are being implemented on social media data towards designing robust disease outbreak prediction models. This study emphasizes how social media has helped during various outbreaks in the past. A bibliometric analysis has also been done over the most recent & relevant literature collected from source SCOPUS.