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OBJECTIVES: This study aimed to investigate patterns of mortality by road transport injury (RTI) in Brazilian municipalities, focused on deaths of motorcyclists, between 2000 and 2018, and their relation with population size and economic status. STUDY DESIGN: This was an ecological epidemiological study with a descriptive and analytical nature. METHODS: The age-standardized RTI mortality rates were calculated for the Brazilian municipalities, referring to the 3-year periods of 2000/2002 (T1), 2009/2011 (T2), and 2016/2018 (T3). The rates were stratified according to macroregion and population size and were compared in terms of percentage variation from one 3-year period to another. The Moran Global and Local indices were used in the spatial point-pattern analysis of the rates. To verify the association with the gross domestic product (GDP) per capita, the Spearman correlation coefficient was applied. RESULTS: A decline in RTI mortality rates was found between 2000 and 2018, with the most significant declines observed in municipalities from the South and Southeast regions of Brazil. However, increases were observed among motorcyclists. Clusters of municipalities were detected, which presented high mortality rates among the motorcyclists in the Northeast region and in some states of the North and Midwest regions. The mortality rates showed a negative correlation with the GDP per capita of the Brazilian municipalities. CONCLUSIONS: Although there were decreases in RTI mortality rates between 1990 and 2018, there was a significant increase in deaths among motorcyclists, especially in the Northeast, North, and Midwest regions of the country. Such differences can be explained by unequal growth in the size of the motorcycle fleet in those regions, by less law enforcement capability, and by the implementation of educational actions.

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This article focused on risk factors for neonatal and post-neonatal mortality by linking live births and infant death records. The study was conducted in the municipality of Goiânia, in the Central-West region of Brazil. A total of 20,981 live births and 342 infant deaths constitute the retrospective cohort. Neonatal and post-neonatal mortality risks were estimated in this cohort study of live births by logistic regression. In the neonatal period, the highest ORs were for delivery in public hospitals (OR = 2.28; 95% CI 1.57-3.32), pre-term neonates (OR = 8.94; 95% CI 5.85-13.67), and low birth weight (OR = 8.92; 95% CI 5.77-13.79). Cesarean delivery appeared as a protective factor (OR = 0.58; 95% CI 0.43-0.78). For post-neonatal mortality, the highest ORs were for illiterate mothers (OR = 6.25; 95% CI 1.25-31.27), low birth weight (OR = 3.12; 95% CI 1.67-5.84), and delivery in public hospitals (OR = 2.65; 95% CI 1. 13-6.23). The linkage identified socioeconomic variables that were more important risk factors for post-neonatal than neonatal mortality.

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In this article we discuss the methodological issues associated with the creation of a surveillance system for endemic diseases in urban areas based on analysis of populations at risk and on spatially referenced epidemiological indicators. We comment on the system's basic requirements, selection criteria for socioeconomic variables, and methodological steps to combine these variables so as to construct a census-based deprivation index. We also present the ways we solved some operational problems related to generation of digitized census tracts maps and linkage of morbidity data from different sources. This approach, spatial organization into account in surveillance of endemic diseases, exemplified here by tuberculosis and leprosy, allows for the interaction of several official data sets from census and health services in order to geographically discriminate inner-city risk strata. Criteria for constructing these risk strata were considered a useful tool for health planning and management activities for the control of endemic diseases in cities.

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The anti-phenolic glycolipid-I (PGL-I) assay as currently applied for leprosy is conceived as an early marker of asymptomatic infection, early disease diagnosis and cure monitoring. Its use as a prognostic marker of reaction is still a matter of controversy. We conducted a case-control study to investigate whether IgM and IgG anti-PGL-I antibodies could discriminate patients at increased risk of developing reactions. Eligible cases were untreated leprosy patients at the onset of type 1 and type 2 reactions recruited from among 600 concurrent, newly detected, untreated leprosy patients attending an outpatient clinic in central Brazil. For the patients with reaction, approximately the same number of leprosy cases without reaction matched as to bacterial index (BI), age and gender were randomly selected. Individuals without clinical leprosy were evaluated as healthy controls. Sera from type 1 reaction (N = 43) and type 2 reaction (N = 26) patients were tested by an ELISA using PGL-I synthetic disaccharide-BSA antigen and 1:300 sera dilution (cut-off point > or = 0.2 OD). Antibody profiles were evaluated by exploratory data analysis and reverse cumulative distribution curves. The IgG anti-PGL-I response did not have a defined pattern, being detected only at low levels. Our results indicate that leprosy patients, independently of their reactional status, produce high levels of IgM anti-PGL-I, demonstrating a strong correlation between the magnitude of antibody response and the BI. Patients with a higher BI were at least 3.4 times more prone to produce an antibody response compared to healthy controls.

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