Forecasting epidemics using social media

In order to better manage resources and democratize health services, DATASUS has a database with relevant information for quantifying and evaluating health information. However, one difficulty encountered is that the data obtained by official means is not always made available in a timely manner and is often only made available when an epidemic is already out of control, leaving no time for preventative measures by public bodies. In this context, there is a need to investigate other methods that make it possible to obtain and analyze data in order to disseminate the information needed for preventive health actions. Therefore, the main objective of this research is to propose a methodology for analyzing epidemics using the social network Twitter. To this end, a case study was carried out in which we sought to identify suspected cases of Chikungunya fever in Brazil based on the symptoms reported by users on the social network.

Autorentext

Hélder Nunes de Almeida hat einen Master-Abschluss in Gesundheitswissenschaften und -technologie von der Staatlichen Universität von Paraíba - UEPB (2016). Er hat einen Abschluss in Informatik (UEPB, 2013). Er hat umfangreiche Erfahrung in der Java-Entwicklung und im Text Mining. Vladimir Costa de Alencar ist Professor/PhD-Forscher an der UEPB, Brasilien, und ist Datenwissenschaftler.