Web System for Spatial Processing and Analysis: An Application in a Neonatal Screening Program in Southern Brazil

Background: Spatial data analysis refers to the process of finding patterns, detecting anomalies, or testing hypotheses and theories by observing phenomena associated with a specific geographic area or location. The literature in the area presents different studies that seek to understand its phenomena through spatial analysis techniques and methods. However, these studies have several problems, such as the frequent use of only one type of analysis, area or punctual. Furthermore, the studies do not formally describe the process of treatment and organization applied to the data to replicate the spatial analyzes in other research areas. Thus, this work proposes a web system for generating, organizing, and processing data compatible with geographic information systems to construct spatial analysis of area and points. Methods The proposed method was developed with the JavaScript programming language and structured in four sequential steps: data acquisition, processing and organization, data validation, and spatial analysis. Data from three diseases (cystic fibrosis, congenital adrenal hyperplasia and hemoglobinopathies) from a neonatal screening program in southern Brazil were used to validate the proposed method and construct the spatial analyses. The choropleth mapping and kernel density estimation methods were used to build the analyses. Results The results obtained made it possible to georeference the data, validate it to its area of study, associate it with its micro and mesoregions, and cross it with public databases. In addition, the results enabled the construction of scientific maps of area and points to visualize the primary evidence from the spatial distribution of disease cases. Conclusions The developed method showed high replication potential for other study contexts. Also, it proved to be relevant in the context of spatial analysis, enabling speed in processing, data organization and, consequently, in the construction of significant results that can be used in public policies that directly impact people's quality of life and health challenges.