INTRODUCTION: In 2010, there were 305 (37.8%) municipalities with malaria epidemics in the Brazilian Amazon. The epidemics spread can be explained by the spatial distribution pattern. OBJECTIVE: To analyze the spatial dependence, autocorrelation, of the malaria epidemics in the municipalities of this region. METHODS: An automated algorithm was used for the detection of epidemic municipalities in 2003, 2007 and 2010. Spatial dependence was analyzed by applying the global and local Moran index on the epidemic months proportion variable. The epidemic municipalities clusters were identified using the TerraView software. RESULTS: The global Moran index values were 0.4 in 2003; 0.6 in 2007; and 0.5 in 2010 (p = 0.01), confirming the spatial dependence among the epidemic municipalities. Box Map and Moran Map identified inter-municipal, interstate and borders clusters with spatial autocorrelation (p < 0.05). There were 10 epidemic municipalities clusters in 2003; 9 in 2007 and 8 in 2010. DISCUSSION: The epidemic municipalities clusters may be linked to the health facilities difficulties on acting together. The structural limitations of the health services can be overcome by territorial integration to support planning and control activities, strengthening the interventions. CONCLUSION: The routine analysis of the epidemic municipalities clusters with spatial and temporal persistence may provide a new indicator of planning and integrated control prioritization, contributing to malaria epidemics reducing in inter-municipal, interstate and borders areas.
INTRODUCTION: In 2010, there were 305 (37.8%) municipalities with malaria epidemics in the Brazilian Amazon. The epidemics spread can be explained by the spatial distribution pattern. OBJECTIVE: To analyze the spatial dependence, autocorrelation, of the malaria epidemics in the municipalities of this region. METHODS: An automated algorithm was used for the detection of epidemic municipalities in 2003, 2007 and 2010. Spatial dependence was analyzed by applying the global and local Moran index on the epidemic months proportion variable. The epidemic municipalities clusters were identified using the TerraView software. RESULTS: The global Moran index values were 0.4 in 2003; 0.6 in 2007; and 0.5 in 2010 (p = 0.01), confirming the spatial dependence among the epidemic municipalities. Box Map and Moran Map identified inter-municipal, interstate and borders clusters with spatial autocorrelation (p < 0.05). There were 10 epidemic municipalities clusters in 2003; 9 in 2007 and 8 in 2010. DISCUSSION: The epidemic municipalities clusters may be linked to the health facilities difficulties on acting together. The structural limitations of the health services can be overcome by territorial integration to support planning and control activities, strengthening the interventions. CONCLUSION: The routine analysis of the epidemic municipalities clusters with spatial and temporal persistence may provide a new indicator of planning and integrated control prioritization, contributing to malaria epidemics reducing in inter-municipal, interstate and borders areas.
Authors: Geraldo Bezerra da Silva; José Reginaldo Pinto; Elvino José Guardão Barros; Geysa Maria Nogueira Farias; Elizabeth De Francesco Daher Journal: Rev Inst Med Trop Sao Paulo Date: 2017-08-03 Impact factor: 1.846