Text mining analysis to understand the impact of online news on public health response : case of syphilis epidemic in Brazil
Pinto, Rafael (Universidade Federal do Rio Grande do Norte. Departamento de Informática e Matemática Aplicada)
Lacerda, Juciano (Universidade Federal do Rio Grande do Norte. Laboratório de Inovação Tecnológica em Saúde)
Silva, Lyrene (Universidade Federal do Rio Grande do Norte. Departamento de Informática e Matemática Aplicada)
Araújo, Ana Claudia (Universidade Federal do Rio Grande do Norte. Laboratório de Inovação Tecnológica em Saúde)
Fontes, Raphael (Universidade Federal do Rio Grande do Norte. Laboratório de Inovação Tecnológica em Saúde)
Santos Lima, Thaisa (Universidade Federal do Rio Grande do Norte. Laboratório de Inovação Tecnológica em Saúde)
Miranda, Angélica Espinosa (Brazil. Ministério da Saúde)
Sanjuán Núñez, Lucía (Universitat Autònoma de Barcelona. Departament d'Antropologia Social i Cultural)
Gonçalo Oliveira, Hugo (Universidade de Coimbra. Departamento de Engenharia Informática)
Atun, Rifat (Harvard University. Health Systems Innovation Lab)
Valentim, Ricardo (Universidade Federal do Rio Grande do Norte. Laboratório de Inovação Tecnológica em Saúde)

Data:	2023
Descripció:	11 pàg.
Resum:	To effectively combat the rising incidence of syphilis, the Brazilian Ministry of Health (MoH) created a National Rapid Response to Syphilis with actions aimed at bolstering epidemiological surveillance of acquired, congenital syphilis, and syphilis during pregnancy complemented with communication activities to raise population awareness and to increase uptake of testing that targeted mass media outlets from November 2018 to March 2019 throughout Brazil, and mainly areas with high rates of syphilis. This study analyzes the volume and quality of online news content on syphilis in Brazil between 2015 and 2019 and examines its effect on testing. The collection and processing of online news were automated by means of a proprietary digital health ecosystem established for the study. We applied text data mining techniques to online news to extract patterns from categories of text. The presence and combination of such categories in collected texts determined the quality of news that were analyzed to classify them as high-, medium-and low-quality news. We examined the correlation between the quality of news and the volume of syphilis testing using Spearman's Rank Correlation Coefficient. 1,049 web pages were collected using a Google Search API, of which 630 were categorized as earned media. We observed a steady increase in the number of news on syphilis in 2015 (n = 18), 2016 (n = 26), and 2017 (n = 42), with a substantial rise in the number of news in 2018 (n = 107) and 2019 (n = 437), although the relative proportion of high-quality news remained consistently high (77. 6 and 70. 5% respectively) and in line with similar years. We found a correlation between news quality and syphilis testing performed in primary health care with an increase of 82. 32, 78. 13, and 73. 20%, respectively, in the three types of treponemal tests used to confirm an infection. Effective communication strategies that lead to dissemination of high quality of information are important to increase uptake of public health policy actions.
Nota:	Altres ajuts: This research was funded by a grant to the Syphilis No! Project from Brazilian Ministry of Health (Project Number: 54/2017)
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Communication ; Mass media ; Data mining ; Text extraction ; Public health ; Notifiable disease ; Syphilis
Publicat a:	Frontiers in Public Health, Vol. 11 (november 2023) , ISSN 2296-2565

DOI: 10.3389/fpubh.2023.1248121
PMID: 38026344

11 p, 972.9 KB

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