Paula A Opromolla1, Ivete Dalben, Márcio Cardim. 1. Coordenadoria de Controle de Doenças, Secretaria de Estado da Saúde de São Paulo, Avenida Dr. Arnaldo, São Paulo, SP, Brazil. opromolla@saude.sp.gov.br
Abstract
OBJECTIVE: To analyze the spatial pattern of leprosy case occurrences in order to identify areas with a probability of disease transmission risks. METHODS: This was an ecological study in which the analysis units were municipalities in the State of São Paulo that were georeferenced at their centroids. The data source was the electronic database of notified leprosy cases at the Epidemiological Surveillance Center of the State of São Paulo, from 1991 to 2001. Geostatistical techniques were used for detecting areas with a probability of leprosy risk, and for quantifying the spatial dependency of cases. RESULTS: The spatial dependence detected extended outwards to 0.55 degrees from the georeferenced coordinates, which corresponded to approximately 60 km. The main areas identified as presenting a probability of risk were the northeastern, northern and northwestern regions of the State. CONCLUSIONS: Verification of areas with the probability of leprosy risk using spatial dependence analysis may be a useful tool for assessing health conditions and planning budget allocations.
OBJECTIVE: To analyze the spatial pattern of leprosy case occurrences in order to identify areas with a probability of disease transmission risks. METHODS: This was an ecological study in which the analysis units were municipalities in the State of São Paulo that were georeferenced at their centroids. The data source was the electronic database of notified leprosy cases at the Epidemiological Surveillance Center of the State of São Paulo, from 1991 to 2001. Geostatistical techniques were used for detecting areas with a probability of leprosy risk, and for quantifying the spatial dependency of cases. RESULTS: The spatial dependence detected extended outwards to 0.55 degrees from the georeferenced coordinates, which corresponded to approximately 60 km. The main areas identified as presenting a probability of risk were the northeastern, northern and northwestern regions of the State. CONCLUSIONS: Verification of areas with the probability of leprosy risk using spatial dependence analysis may be a useful tool for assessing health conditions and planning budget allocations.
Authors: Antônio Carlos Vieira Ramos; Mellina Yamamura; Luiz Henrique Arroyo; Marcela Paschoal Popolin; Francisco Chiaravalloti Neto; Pedro Fredemir Palha; Severina Alice da Costa Uchoa; Flávia Meneguetti Pieri; Ione Carvalho Pinto; Regina Célia Fiorati; Ana Angélica Rêgo de Queiroz; Aylana de Souza Belchior; Danielle Talita Dos Santos; Maria Concebida da Cunha Garcia; Juliane de Almeida Crispim; Luana Seles Alves; Thaís Zamboni Berra; Ricardo Alexandre Arcêncio Journal: PLoS Negl Trop Dis Date: 2017-02-27
Authors: Lorena Dias Monteiro; Francisco Rogerlândio Martins-Melo; Aline Lima Brito; Carlos Henrique Alencar; Jorg Heukelbach Journal: Rev Saude Publica Date: 2015-11-24 Impact factor: 2.106