@article{Poleto2023,
abstract = {The interface between Decision Support Systems (DSS) and Geographical Information Sys-tems (GIS) generates Spatial Decision Support Systems (SDSS) which aid in the deci-sion-making process, particularly in situations where spatial attributes play a pivotal role in achieving accurate conclusions. By integrating conventional decision criteria with spatial crite-ria and visualization through the adoption of SDSS and geographic information systems tech-nologies, a comprehensive analysis is ensured. The primary aim of this research is to exemplify an application of SDSS to support analyses and decisions on a specific issue in Public Health. The focus lies on assessing cities within the state of Pernambuco (Brazil) that exhibit the high-est rates of maternal mortality. This approach promises to offer valuable insights and aid in making informed decisions to address critical maternal health issues in the region.},
author = {Poleto, Thiago and {De Carvalho}, Victor Diogho Heuer and {De Oliveira}, Rodrigo Cleiton Paiva},
doi = {10.51359/2965-4661.2023.259360},
file = {:G\:/Meu Drive/Drive (UFPE)/Administrativo/Editorial/Socioeconomic Analytics/Issue 1 (2023)/5. Poleto et al/Poleto et al. (2023).pdf:pdf},
issn = {2965-4661},
journal = {Socioeconomic Analytics},
keywords = {Brazil,Pernambuco,Spatial Decision Support Systems,decision-making,ma- ternal mortality,public health},
month = {aug},
number = {1},
pages = {92--102},
title = {{Applying spatial decision support for maternal mortality analysis in a Brazilian state}},
url = {https://periodicos.ufpe.br/revistas/index.php/SECAN/article/view/259360},
volume = {1},
year = {2023}
}