Desenvolvimento de um sistema computacional para monitoramento na vigilância epidemiológica de agravos agudos (dengue, chikingunya e zika)

• Ano de defesa: 2016
• Autor(a) principal: Sousa, Geziel dos Santos de
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Dengue; Febre de Chikungunya; Zika virus; Sistemas de Informação em Saúde
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/69186

The Dengue fever, Chikungunya and Zika are public health issues of greatest importance in the city of Fortaleza. The goal is to develop a software able to produce integrated information relating to spatio-temporal patterns of diseases notifiable, using as a model the application reported cases of Dengue, Chikungunya and Zika at central level for the epidemiological surveillance of Municipal da Saúde (CIEVS/CEVEPI). In methodological terms, the project is located in the field of health information technology, constituting itself as a kind of applied research, focused on the development of a computational system via web (online) named Sistema de Monitoramento de Agravos (SIMA). It is an articulated system to SINAN Online, official notifications entry door of diseases of the Ministry of health. The application will be developed in GRAILS framework, management of technology databases POSTGRESQL and PENTAHO KETTLE ETL tool. The SIMA will have multiple outputs of epidemiological relevance for timely analysis of endemic and epidemic level definition in a particular population, such as the control diagram and dynamic mapping of the reported cases, and will assist in the dissemination of epidemiological information quickly and objectively, seeking the guidance of strategic decisions for the evaluation of control programs , particularly in the detection and containment of epidemics. It is expected that the SIMA contribute in decision making by managers and encourages other similar initiatives for the development of computational systems in health that can help understand local realities and monitor effectively the dynamics of spatial and temporal transmission of diseases.