Modelado de temas de investigación en el nuevo coronavirus: aplicación Latente de Asignación de Dirichlet
Resumen
Objetivo: analisar o desenvolvimento global de publicações científicas e construir tópicos abordados em pesquisas sobre o novo coronavírus/COVID-19. Métodos: estudo de revisão de resumos de publicações sobre o novo coronavírus/COVID-19, com busca nas bases de dados Embase e Web of Science, em 03 de novembro de 2020. A análise dos dados se deu pela modelagem dos tópicos de pesquisa pelo método Latent Dirichlet Allocation (LDA). Resultados: analisaram-se 31.769 publicações, com envolvimento de pesquisadores de 182 países. Os estudos foram publicados em 5.336 periódicos diferentes. A análise identificou 20 tópicos principais de pesquisa sobre o novo coronavírus/COVID-19, sendo que mais da metade (54,5%) das publicações foram contempladas nos temas de impactos e desafios decorrentes da pandemia (11,3%), resposta imunológica (9,6%), potenciais terapêuticas (9,0%), epidemiologia (7,8%), saúde mental (6,3%), recomendações para assistência a outras necessidades de saúde (5,3%) e complicações clínicas. O tema da telemedicina e telessaúde foi evidenciado em 4,2% das publicações. Conclusões: as publicações científicas estavam distribuídas dentre 20 principais temas, caracterizando sua importância e relevância no entendimento do agravo em questão para traçar estratégias de controle, prevenção, tratamento e atenção aos agravos/implicações decorrentes da pandemia. Identificaram-se como principal lacuna de conhecimento estudos sobre cuidados primários/atenção primária à saúde.
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