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.
BT - Revista de saude publica C1 - http://www.ncbi.nlm.nih.gov/pubmed/11723520?dopt=Abstract DA - 2001 Oct DO - 10.1590/s0034-89102001000500011 IS - 5 J2 - Rev Saude Publica LA - por N2 -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.
PY - 2001 SP - 474 EP - 80 T2 - Revista de saude publica TI - [Empirical bayesian model applied to the spatial analysis of leprosy occurrence]. TT - Aplicação de modelo bayesiano empírico na análise espacial da ocorrência de hanseníase UR - http://www.scielosp.org/pdf/rsp/v35n5/6587.pdf VL - 35 SN - 0034-8910 ER -