| Literature DB >> 29845585 |
Abstract
In the last two decades, urbanization has intensified, and in Brazil, about 90% of the population now lives in urban centers. Atmospheric patterns have changed owing to the high growth rate of cities, with negative consequences for public health. This research aims to elucidate the spatial patterns of air pollution and respiratory diseases. A data-based model to aid local urban management to improve public health policies concerning air pollution is described. An example of data preparation and multivariate analysis with inventories from different cities in the Metropolitan Region of Curitiba was studied. A predictive model with outstanding accuracy in prediction of outbreaks was developed. Preliminary results describe relevant relations among morbidity scales, air pollution levels, and atmospheric seasonal patterns. The knowledge gathered here contributes to the debate on social issues and public policies. Moreover, the results of this smaller scale study can be extended to megacities.Entities:
Keywords: Air pollution; Curitiba; Data mining; Respiratory diseases; Urban management
Year: 2019 PMID: 29845585 PMCID: PMC6677834 DOI: 10.1007/s11524-018-0271-5
Source DB: PubMed Journal: J Urban Health ISSN: 1099-3460 Impact factor: 3.671