Analysis of the socio-environmental vulnerability of black and Caucasian pregnant women in Salvador, Bahia, Brazil to the occurrence of microcephaly associated with the congenital syndrome of zika virus.

To understand the occurrence of the Congenital Zika Syndrome (CZS), the living conditions of pregnant individuals must be considered in order to identify factors and areas of risk. An intersectional approach provides an understanding of the vulnerabilities to which Black women are subjected. To that end, we present an overview of the spatio-temporal distribution of confirmed cases of microcephaly associated with CZS during the 2015-2016 period in Salvador, Bahia, Brazil based on a survey of Black and Caucasian, pregnant women seen through the intersectional lens of race and class. To consider the confirmed cases of microcephaly and other neurological anomalies associated with CZS, a Living Condition Index (LCI) was utilized to rate the socio-environmental vulnerability of pregnant women. There was less information in the notification records with regard to Black, pregnant women resulting in fewer examinations. Twelve, highrisk areas for Black, pregnant women were identified but only two for Caucasian women. CZS cases referred to Black, pregnant women were found to be concentrated in census sectors with a low (31.6%) and very low (34.5%) LCI, while those referred to Caucasian, pregnant women were concentrated in areas with a high (35.6%) and intermediate (29.4%) LCI. The study concludes that inequities in health expose different population groups to different forms of illnesses, and institutional racism solidifies scenarios of exclusion. In this sense, Black women experiences manifest directly in their health. Confrontation with arboviruses requires the implementation of inter-institutional policies aimed at overcoming discriminatory practices of exposure.

Ecological niche models for sand fly species and predicted distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in Bahia state, Brazil.

Visceral leishmaniasis is a public health problem in Brazil. This disease is endemic in most of Bahia state, with increasing reports of cases in new areas. Ecological niche models (ENM) can be used as a tool for predicting potential distribution for disease, vectors, and to identify risk factors associated with their distribution. In this study, ecological niche models (ENMs) were developed for visceral leishmaniasis (VL) cases and 12 sand fly species captured in Bahia state. Sand fly data was collected monthly by CDC light traps from July 2009 to December 2012. MODIS satellite imagery was used to calculate NDVI, NDMI, and NDWI vegetation indices, MODIS day and night land surface temperature (LST), enhanced vegetation index (EVI), and 19 Bioclim variables were used to develop the ENM using the maximum entropy approach (Maxent). Mean diurnal range was the variable that most contributed to all the models for sand flies, followed by precipitation in wettest month. For Lutzomyia longipalpis (L. longipalpis), annual precipitation, precipitation in wettest quarter, precipitation in wettest month, and NDVI were the most contributing variables. For the VL model, the variables that contributed most were precipitation in wettest month, annual precipitation, LST day, and temperature seasonality. L. longipalpis was the species with the widest potential distribution in the state. The identification of risk areas and factors associated with this distribution is fundamental to prioritize resource allocation and to improve the efficacy of the state's program for surveillance and control of VL.