Sistema de apoio à decisão espacial multicritério: uma nova arquitetura aplicada a problemas epidemiológicos

• Ano de defesa: 2020
• Autor(a) principal: Lima, Luciana Moura Mendes de
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Ciências Exatas e da Saúde; Programa de Pós-Graduação em Modelos de Decisão e Saúde; UFPB
• Palavras-chave em Português: Tomada de decisão; Epidemiologia; Análise espacial; Tomada de Decisão Multicritério; Anormalidades Congênitas.; Decision making; Epidemiology; Spatial analysis; Multicriteria Decision Making; Congenital Abnormalities.; CNPQ::CIENCIAS DA SAUDE::SAUDE COLETIVA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/20681

Decisions in the health area, in general, cover several complex and conflicting data, factors and options. Additionally, in Epidemiology, social, spatial, technological aspects, among others, must be considered to provide decisions on the definition of intervention priority levels, for example. A Spatial Decision Support System can use that information and help define these levels based on some criteria. The aim of this work is to develop a new architecture for the Multicriteria Spatial Decision Support System that can be applied to epidemiological problems. The new architecture presents an innovative approach with an interdisciplinary vision, involving statistical, spatial and spatial-temporal analysis, multicriteria decision making and Epidemiology in the identification of priority areas for intervention. The architecture was applied to a quantitative, ecological and retrospective study that used data referring to cases of congenital anomalies of the nervous system in live births, as it is an important public health problem and has a high quantity in relation to the others. The data source was the Live Birth Information System, from 2013 to 2017, state of Parahyba, Brazil. For the creation and testing of the new architecture, the cases of the mentioned anomalies were used. The new architecture uses and replicates the architecture of a previously developed spatial decision support system, using them as criteria and subcriteria. In turn, each subcriteria is processed particularly, generating a georeferenced decision map as a result. Then, these maps are analyzed and combined by a multicriteria decision-making method, using the weights assigned by the experts, producing a final decision map that points out four levels of priority for intervention as alternatives: “non-priority”, “tendency to non-priority”, “tendency to priority” and “priority” used for the problem in question. It was found that most municipalities were considered “non-priority” and six as “tendency to priority” for cases of congenital anomalies of the nervous system. The new architecture allows results that are easy to interpret, especially for health managers who are not in the habit of dealing with this type of methodology in their daily lives. In addition, it can be used in other diseases and geographic regions, allowing to change or not its modules, so it adapts to the problem in every circumstance. The architecture was planned as a decision support tool for health managers.