Autoregressive spatial modeling of possible cases of dengue, chikungunya, and Zika in the capital of Northeastern Brazil

Abstract INTRODUCTION: Dengue, chikungunya, and Zika are a growing global health problem. This study analyzed the spatial distribution of dengue, chikungunya, and Zika cases in São Luís, Maranhão, from 2015 to 2016 and investigated the association between socio-environmental and economic factors and hotspots for mosquito proliferation. METHODS: This was a socio-ecological study using data from the National Information System of Notifiable Diseases. The spatial units of analysis were census tracts. The incidence rates of the combined cases of the three diseases were calculated and smoothed using empirical local Bayes estimates. The spatial autocorrelation of the smoothed incidence rate was measured using Local Moran's I and Global Moran's I. Multiple linear regression and spatial autoregressive models were fitted using the log of the smoothed disease incidence rate as the dependent variable and socio-environmental factors, demographics, and mosquito hotspots as independent variables. RESULTS: The findings showed a significant spatial autocorrelation of the smoothed incidence rate. The model that best fit the data was the spatial lag model, revealing a positive association between disease incidence and the proportion of households with surrounding garbage accumulation. CONCLUSIONS: The distribution of dengue, chikungunya, and Zika cases showed a significant spatial pattern, in which the high-risk areas for the three diseases were explained by the variable "garbage accumulated in the surrounding environment," demonstrating the need for an intersectoral approach for vector control and prevention that goes beyond health actions.

Land Use and Environmental Zoning of Mixed Ombrophilous Forests for Sustainable Use (Irati National Forest, Brazil Southern Region)

ABSTRACT An environmental zoning proposal due to the demand to develop strategies to ensure biodiversity scenarios for the remaining mixed ombrophilous forests was carried out for the Irati National Forest, a legally protected area for sustainable use located in southern Brazil. To identify land use and cover, Ikonos PSM images dated from December 2004, based on the interpretation of visual character and vectorization of orbital data were used. Qualitative and quantitative classifications identified six types of land and cover use: native forest, forestry, capoeira grass, wetland, araucaria plantation, and anthropic. The native forest relative to the mixed ombrophilous forest was the prevailing type of land cover. The environmental zoning proposal defined seven zones of use, some that involved several potentially harmful activities to the biodiversity of the Irati National Forest. The environmental zone proposal, based on ecosystem conservation, outlined specific factors that enhanced ecosystem and community viability, supporting the design and evaluation of the management plan of the Irati National Forest.