Biomedical subjects

O G Cruz

Publications and source records attributed to O G Cruz.

3 recordsLinked to original sources

PubMed2001

[Empirical bayesian model applied to the spatial analysis of leprosy occurrence].

OBJECTIVE: To analyze the spatial distribution of leprosy, identify areas of potential case underreporting or high transmission risk, and to assess the ecological association of leprosy distribution with multibacillary cases. METHODS: This study was carried out in 94 neighborhoods of Recife, Brazil. Data was obtained from the Ministry of Health's Disease Reporting System. An ecological approach with the empirical Bayesian method was applied for local rate flattening, using data from a neighborhood matrix. RESULTS: The mean annual occurrence was 17.3% of new cases in individuals under the age of 15 (28.3% corresponded to multibacillary forms), revealing an intense disease transmission. The spatial distribution of leprosy indicated three areas where there was a concentration of high detection rates and low-income neighborhoods. CONCLUSIONS: The Bayesian method allowed to reassess epidemiological indicators based on data from neighboring spatial units. This enabled to identify areas that should be prioritized in municipal control programs, either because of underreporting of cases or the higher number of occurrences related to multibacillary forms in individuals under 15.

Adolescent↗

PubMedDate not supplied

Spatial partitioning using multivariate cluster analysis and a contiguity algorithm.

Spatial analysis of epidemiological data can be a useful tool for identifying patterns of disease occurrence and can provide substantial support for prevention and control strategies. To obtain the greatest spatial resolution, it is important to use the smallest available areal units with homogeneous population. However, small areas usually have a small population, introducing spurious variability in the chosen indicators of disease occurrence. This paper describes an approach for combining small geographical units to stabilize mortality rates by pooling information across areas according to specified risk profiles. The procedure is based on a principal component analysis, followed by a cluster analysis of social-economic indicators to classify the risk profile of each small area. The classification is used in an algorithm to join neighbouring areas with similar profiles until an estimated population size is achieved. We applied this method to two Administrative Regions of the city of Rio de Janeiro, Brazil, using the census tracts as the basic areal unit. Census tracts were classified according to four socioeconomic categories distributed spatially as a mosaic, where tracts of differing categories neighbour each other. The aggregation algorithm produced a new partition of the region studied, with the created areal units preserving the internal socioeconomic homogeneity.

Adult↗

PubMedDate not supplied

[Use of spatial analysis tools in the epidemiological surveillance of American visceral leishmaniasis, Araçatuba, São Paulo, Brazil, 1998-1999].

The control of American visceral leishmaniasis (AVL) is based on combating the vector and eliminating the domestic reservoir of the focus area - defined as 200 meters around human or canine cases. This paper discusses the use of spatial analysis techniques in the epidemiological surveillance of AVL in Araçatuba, São Paulo State, in order to propose a model for territorial epidemiological surveillance, reformulating current control strategies. The results showed that AVL transmission was not homogeneous; human cases were more frequent in areas with higher canine prevalence rates. Vector dispersion appeared to be restricted to a few houses, although it was not possible to model the vector density. In order to study the vector distribution and correlated covariates, a field study based on house sampling is being conducted. The results will aid the development of new spatial analysis tools and possibly redefine protocols and routines for the control of this endemic disease in urban areas.

Adolescent↗