Loading...
Please wait, while we are loading the content...
Similar Documents
Universidade Federal Do Rio Grande Do Sul Faculdade De Medicina Programa De Pós-graduação Em Epidemiologia Mapeamento Da Mortalidade Infantil No Rio Grande Do Sul: Uma Comparação Entre as Abordagens Empirica Bayesiana E Totalmente Bayesiana
| Content Provider | Semantic Scholar |
|---|---|
| Author | Letícia, Sabrina Silva, Couto Da Fachel, Maria Guimarães Alegre, Porto |
| Copyright Year | 2009 |
| Abstract | The infant mortality rate (IMR) has been used as one of the main indicators of the quality of life of a population. It reflects the levels of health and socioeconomic development in a given area, and is considered one of the most important epidemiological indicators. The analysis of spatial dispersion of the risk of occurrence of an event for aggregate data is usually done by incidence rates maps, where the areas are shaded according to the values calculated for this rate. A major problem associated with the use of rates, however, is their high instability to express the risk of rare events in regions with a small population. Alternately, there are spatial statistical methods to map diseases, called Empirical Bayes estimate, and also Totally Bayesian estimate, which use information from the whole region or surroundings to estimate the risk of occurrence of the event in each area. The present study applies and compares the two methods for IMR estimates in the 496 municipalities of Rio Grande do Sul using data accumulated between 2001 and 2004 (data available in DATASUS); it indicates the advantages of using the Bayesian estimates compared to the gross rate and compares the estimates obtained by gross modeling and the Bayesian methods. When the estimates obtained by Bayesian modeling were compared to those of the gross calculation, a substantial gain could be observed in the interpretation and detection of patterns of variation of infant mortality risk in the municipalities of Rio Grande do Sul. Comparing the Bayesian methods, it is observed that the estimates calculated using the Empirical Bayes method smooth out less in the high risk areas than the Totally Bayesian estimates. The Empirical Bayes method can be used to reduce the variation observed in estimation through the classical method and is implemented in different Geoprocessing and Spatial Epidemiology softwares, which can be easily utilized by health care professionals. Although the Totally Bayesian method has a few important properties from the statistical perspective, it is requires highly complex computations. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.lume.ufrgs.br/bitstream/handle/10183/17765/000721664.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
