Leishmaniose Visceral no Nordeste brasileiro: aspectos espaço-temporal e variabilidade climática

Abstract

Brazil is the country in Latin America which has the highest record of notifications of confirmed cases of Visceral Leishmaniasis (VL), with the majority number of cases recorded in the Northeast region. Thus, by considering that the main goal of the present work is to identify patterns of spatial and temporal distribution of VL in Northeastern Brazil (NEB) and analyze potential relationship with climate factors associated to the expansion of the distribution of cases in the NEB. The climate variables such as temperature (minimum, average, and maximum), relative humidity and accumulated precipitation were used. Those data were obtained from the Climate Prediction Center/National Oceanic and Atmospheric Administration (CPC/NOAA) as well as from the Instituto Nacional de Meteorologia (INMET), for a period from 2001 to 2015. LV incidence rates were computed on the basis of LV notifications, by place of residence, from the Brazilian Information System for Notifiable Diseases (SINAN) made available by the SUS Information Department (DATASUS) and the census data from the Brazilian Institute of Geography and Statistics (IBGE), collected in the 2000 and 2010 Demographic Census. The Moran Index, the Mann-Kendall test and the Friedman test, and cross-correlation were used and, finally, the estimation of the odds ratios of the intensities of VL transmission based on the Ministry of Health classification according to the Cumulative Mixed Effects Modeling (GLMM). It was considered as a random effect the 1,792 municipalities measured at five moments in time, formed by the three-year periods under investigation. The main results showed an increasing trend in VL for the state of Ceará (𝑝 = 0.046) and a decreasing trend for the state of Alagoas (𝑝 = 0.006). Spatial autocorrelation of the data was observed in the five studied triennia: 2001-2003 (𝑝 = 0.001); 2004-2006 (𝑝 = 0.001); 2007-2009 (𝑝 = 0.001); 2010-2012 (𝑝 = 0.003) e 2013 − 2015 (𝑝 = 0.001), showing the spread of the disease in the NEB. GLMM via cumulative logitos showed a positive association between VL and population size (p<0.001), VL and average temperature (p=0.002), as well as between VL and relative humidity (p<0.001). The larger the population of the municipality, the greater the chance of transmitting VL by 3.48 times, and the higher the average temperature this chance is 1.29 times greater. Regarding humidity, it was found that the higher it is, the chance of transmission decreases by 13%. The results obtained contribute to the understanding of the relationship between VL and climate, pointing out areas of greater risk and the spatial spread of the disease. The modeling used allowed for considering the variability between and within municipalities, proving to be effective in estimating the parameters associated with VL.