Epidemiological Monitoring Of Rumors Through Social Networks During Mass Gatherings
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Abstract
Background: With the global advancement of new technologies, the public health sector is incorporating new tools so that information becomes more dynamic and accessible to the population. With the growth of the internet, a new model of information processing was developed using crowdsourcing and volunteers for solving problems and incorporating technologies in different environments within a society. This population participatory system has been used to provide information for the understanding of disease transmission. Through the use of additional tools in connection with the digital social networks, such as Twitter, detection of possible health threats including the precursory rumors about them has been made possible. This has promoted an improved sensitivity of surveillance in health services and mitigation of potential outbreaks, based on the shared experiences of the target population.
Objectives: To describe the experience of the Strategic Information Center of Health Surveillance in Pernambuco by monitoring Twitter during the Carnival event, Galo da Madrugada, 2013.
Methods: This was a cross-sectional epidemiological study, conducted on February 9, 2013, during the occurrence of the Carnival Galo da Madrugada 2013, in the city of Recife, Pernambuco, Brazil. This one-day, 10-hour event event attracts tourists from all over Brazil and the world, with an attendance of one and a half million people.
We defined a list of strategic terms based on Brazilian law describing the disease that require as immediate response and terms related to syndromic surveillance at mass gatherings. The platform used for this capture was the freeware Tweetdeck. One hundred one terms were defined as search filters, using the word of interest plus the regional component (Pernambuco, Recife e “Galoâ€) to better specify the place of occurrence. Every hour the results that were received were analyzed to assure that they were epidemiologically relevant.
Results: We identified 24 terms of interest related to symptoms and diseases during Galo da Madrugada, 2013, being: Flu (33.3%), violence (16.7%), confusion (12.5%); Accident (8 3%); Surveillance (8.3%), meningitis (4.2%); Dengue (4.2%), headache (4.2%); stomachache (4.2%); Fever (4.2%). None of them demanded an intervention or risk mitigation, despite the readiness of the response team awaiting in a situation room.
Conclusion: Given the above, it can be concluded that the retrieval of epidemiologic rumors through social networks during mass gatherings is of great importance. Tools such as the one presented are favored due to the generosity and possibility of building multiple filters with storage up to 06 days after the term is mentioned. However the sensivity of the activity may have been reduced by not including tweets of people that were participating in the event due to the lack of the use at the regional terms mentioned above these tweets were not considered. Regardless, epidemiological surveillance information is rapidly becoming a vital part of routine health surveillance services, as it is an unprecedented source of information for early identification of the risk of spreading diseases.
Objectives: To describe the experience of the Strategic Information Center of Health Surveillance in Pernambuco by monitoring Twitter during the Carnival event, Galo da Madrugada, 2013.
Methods: This was a cross-sectional epidemiological study, conducted on February 9, 2013, during the occurrence of the Carnival Galo da Madrugada 2013, in the city of Recife, Pernambuco, Brazil. This one-day, 10-hour event event attracts tourists from all over Brazil and the world, with an attendance of one and a half million people.
We defined a list of strategic terms based on Brazilian law describing the disease that require as immediate response and terms related to syndromic surveillance at mass gatherings. The platform used for this capture was the freeware Tweetdeck. One hundred one terms were defined as search filters, using the word of interest plus the regional component (Pernambuco, Recife e “Galoâ€) to better specify the place of occurrence. Every hour the results that were received were analyzed to assure that they were epidemiologically relevant.
Results: We identified 24 terms of interest related to symptoms and diseases during Galo da Madrugada, 2013, being: Flu (33.3%), violence (16.7%), confusion (12.5%); Accident (8 3%); Surveillance (8.3%), meningitis (4.2%); Dengue (4.2%), headache (4.2%); stomachache (4.2%); Fever (4.2%). None of them demanded an intervention or risk mitigation, despite the readiness of the response team awaiting in a situation room.
Conclusion: Given the above, it can be concluded that the retrieval of epidemiologic rumors through social networks during mass gatherings is of great importance. Tools such as the one presented are favored due to the generosity and possibility of building multiple filters with storage up to 06 days after the term is mentioned. However the sensivity of the activity may have been reduced by not including tweets of people that were participating in the event due to the lack of the use at the regional terms mentioned above these tweets were not considered. Regardless, epidemiological surveillance information is rapidly becoming a vital part of routine health surveillance services, as it is an unprecedented source of information for early identification of the risk of spreading diseases.
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