A new combination rule for Spatial Decision Support Systems for epidemiology

International Journal of Health Geographics

Jordana de Almeida Nogueira¹  Rodrigo Pinheiro de Toledo Vianna²  Ana Flávia Uzeda dos Santos Macambira³  Ronei Marcos de Moraes³  Luciana Moura Mendes de Lima⁴  Laísa Ribeiro de Sá⁴ 

[1] Department of Nursing, Federal University of Paraíba;Department of Nutrition, Federal University of Paraíba;Department of Statistics, Federal University of Paraíba;Graduate Program in Decision Models and Health, Department of Statistics, Federal University of Paraíba;

关键词: Epidemiology;    Spatial analysis;    Space–time analysis;    Multiple Criteria Decision Making;    Spatial Decision Support Systems;    Brazil;   

DOI  :  10.1186/s12942-019-0187-7

来源: DOAJ

【 摘 要 】

Abstract Background Decision making in the health area usually involves several factors, options and data. In addition, it should take into account technological, social and spatial aspects, among others. Decision making methodologies need to address this set of information , and there is a small group of them with focus on epidemiological purposes, in particular Spatial Decision Support Systems (SDSS). Methods Makes uses a Multiple Criteria Decision Making (MCDM) method as a combining rule of results from a set of SDSS, where each one of them analyzes specific aspects of a complex problem. Specifically, each geo-object of the geographic region is processed, according to its own spatial information, by an SDSS using spatial and non-spatial data, inferential statistics and spatial and spatio-temporal analysis, which are then grouped together by a fuzzy rule-based system that will produce a georeferenced map. This means that, each SDSS provides an initial evaluation for each variable of the problem. The results are combined by the weighted linear combination (WLC) as a criterion in a MCDM problem, producing a final decision map about the priority levels for fight against a disease. In fact, the WLC works as a combining rule for those initial evaluations in a weighted manner, more than a MCDM, i.e., it combines those initial evaluations in order to build the final decision map. Results An example of using this new approach with real epidemiological data of tuberculosis in a Brazilian municipality is provided. As a result, the new approach provides a final map with four priority levels: “non-priority”, “non-priority tendency”, “priority tendency” and “priority”, for the fight against diseases. Conclusion The new approach may help public managers in the planning and direction of health actions, in the reorganization of public services, especially with regard to their levels of priorities.

【 授权许可】

Unknown