0473/2018 - Production spaces of cutaneous leishmaniasis in the State of Rio de janeiro.
Espaços de produção da leishmaniose tegumentar americana no Estado do Rio de Janeiro.
Publicado
Author:
• Valdenir Bandeira Soares - Soares, VB - <valdenir@ensp.fiocruz.br>ORCID: https://orcid.org/0000-0002-4800-2940
Co-author(s):
• Andréa Sobral - Sobral, A. - <andrea.sobral@fiocruz.br>ORCID: https://orcid.org/0000-0003-0552-771X
• Paulo Chasgastelles Sabroza - Sabroza, P.C - <sabroza@ensp.fiocruz.br>
ORCID: https://orcid.org/0000-0001-8235-0562
• Waldemir Paixão Vargas - Vargas, WP - <waldemir.vargas@ensp.fiocruz.br>
ORCID: https://orcid.org/0000-0003-3692-7185
• Reinaldo Souza-Santos - Souza-Santos, R. - <rssantos@ensp.fiocruz.br; santo_rei@outlook.com>
ORCID: https://orcid.org/0000-0003-2387-6999
• Ana Cecília de Oliveira Valdés - Valdés, ACO - <ana_oliveiravaldes@yahoo.com.br>
ORCID: https://orcid.org/0000-0002-1158-5476
Abstract:
The objective was to identify and characterize spatial units of epidemiological relevance in the state of Rio de Janeiro, through the highest concentrations of cases oftegumentary leishmaniasis (TL)1980 to 2012, considering the concepts of geography. We used SUCAM databases, FUNASA and SINAN. It was applied a method of
adjustment of spatially referenced data for demarcation of the regions with the largest concentrations of densities of cases called circuits and poles. These were superimposed on the socioenvironmental indicator maps. Of the total cases registered in the period, 87% occurred in the municipalities located in the resulting circuits and poles. A cyclic behavior of the disease was identified, presented by thematic maps of density of cases. The variations in the occurrence of cases in
the different circuits and poles were not related to the socioenvironmental indicators. The identification of the circuits and poles can subsidize the state program of the
TL for the prioritization of strategies of prevention and control actions and the optimization of the resources of the program. These regions, which are more stable than the localities, allow surveillance and control operations in locations with many cases and in other locations in the identified risk area, because they have the same characteristics as those already affected.
