14 research outputs found
Human migration, railways and the geographic distribution of leprosy in Rio Grande do Norte State – Brazil
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Previous issue date: 2015Hospital Giselda Trigueiro. Natal, RN, Brasil / Universidade Federal do Rio Grande do Norte. Instituto de Medicina Tropical do Rio Grande do Norte. Natal, RN, Brasil /Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Pós-Graduação em Medicina Tropical. Rio de |Janeiro, RJ, Brasil.Universidade Federal do Rio Grande do Norte. Instituto de Medicina Tropical do Rio Grande do Norte. Natal, RN, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Pós-Graduação em Medicina Tropical. Rio de |Janeiro, RJ, Brasil./ Weill Cornell Medical College. Division of Infectious Diseases and Center for Global Health. New York, NY, USA.Universidade Federal do Rio Grande do Norte. Departamento de Arquitetura. Natal, RN, Brasil.Instituto Nacional de Seguridade Social. Mossoró, RN, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ. Brasil.Universidade Federal do Rio Grande do Norte. Instituto de Medicina Tropical do Rio Grande do Norte. Natal, RN, Brasil / Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais (INCT/DT). Salvador, BA, Brasil.Introduction—Leprosy is a public health problem in Brazil where 31,044 new cases were detected in 2013. Rio Grande do Norte is a small Brazilian state with a rate of leprosy lower than other areas in the same region, for unknown reasons.
Objectives—We present here a review based on the analysis of a database of registered leprosy cases in Rio Grande do Norte state, comparing leprosy's geographic distribution among municipalities with local socio-economic and public health indicators and with historical documents about human migration in this Brazilian region.
Results—The current distribution of leprosy in Rio Grande do Norte did not show correlation with socio-economic or public health indicators at the municipal level, but it appears related to economically emerging municipalities 100 years ago, with spread facilitated by railroads and train stations. Drought-related migratory movements which occurred from this state to leprosy endemic areas within the same period may be involved in the introduction of leprosy and with its present distribution within Rio Grande do Norte
Multibacillary leprosy by population groups in Brazil: Lessons from an observational study
<div><p>Background</p><p>Leprosy remains an important public health problem in Brazil where 28,761 new cases were diagnosed in 2015, the second highest number of new cases detected globally. The disease is caused by <i>Mycobacterium leprae</i>, a pathogen spread by patients with multibacillary (MB) leprosy. This study was designed to identify population groups most at risk for MB disease in Brazil, contributing to new ideas for early diagnosis and leprosy control.</p><p>Methods</p><p>A national databank of cases reported in Brazil (2001–2013) was used to evaluate epidemiological characteristics of MB leprosy. Additionally, the databank of a leprosy reference center was used to determine factors associated with higher bacillary loads.</p><p>Results</p><p>A total of 541,090 cases were analyzed. New case detection rates (NCDRs) increased with age, especially for men with MB leprosy, reaching 44.8 new cases/100,000 population in 65–69 year olds. Males and subjects older than 59 years had twice the odds of MB leprosy than females and younger cases (OR = 2.36, CI95% = 2.33–2.38; OR = 1.99, CI95% = 1.96–2.02, respectively). Bacillary load was higher in male and in patients aged 20–39 and 40–59 years compared to females and other age groups. From 2003 to 2013, there was a progressive reduction in annual NCDRs and an increase in the percentage of MB cases and of elderly patients in Brazil. These data suggest reduction of leprosy transmission in the country.</p><p>Conclusion</p><p>Public health policies for leprosy control in endemic areas in Brazil should include activities especially addressed to men and to the elderly in order to further reduce <i>M</i>. <i>leprae</i> transmission.</p></div
Mean new case detection rates (NCDR) of leprosy in Brazil (2001–2013).
<p>3a) NCDR by sex according to age group. 3b) NCDR by sex and operational classification according to age group. MB: multibacillary, PB: paucibacillary.</p
Annual indicators for leprosy in Brazil (2001–2013)
<p>Annual indicators for leprosy in Brazil (2001–2013)</p
Mean new case detection rates (NCDR) of leprosy by time period, according to age group–Brazil (2001 to 2013).
<p>Mean new case detection rates (NCDR) of leprosy by time period, according to age group–Brazil (2001 to 2013).</p
Bacillary index of leprosy cases at diagnosis by sex according to age groups–Ambulatório Souza Araújo, Fiocruz/RJ, Brazil (1990–2014).
<p>5a = All cases; 5b = MB cases. * = extremes, dots = outliers, horizontal bar = median, box = 25–75 percentiles.</p
Mean new case detection rates (NCDR) of leprosy by Brazilian state (2001 to 2013).
<p>Mean new case detection rates (NCDR) of leprosy by Brazilian state (2001 to 2013).</p
Sex ratio of leprosy cases detected without disabilities, by operational classification according to age group–Brazil.
<p>MB: multibacillary, PB: paucibacillary.</p
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Long‐term mortality after tuberculosis treatment among persons living with HIV in Haiti
IntroductionLong-term mortality among TB survivors appears to be higher than control populations without TB in many settings. However, data are limited among persons with HIV (PWH). We assessed the association between cured TB and long-term mortality among persons with PWH in Haiti.MethodsA prospective cohort of PWH from the CIPRA HT-001 trial was followed from study enrolment (August 2005 to July 2008) to study closure (December 2018) to compare mortality between participants with and without TB. The index date for the survival analysis was defined as 240 days after TB diagnosis or randomization date. Time to death was described using Kaplan-Meier curves, and log-rank tests were used to compare time to death between the TB and no-TB cohorts. The association between TB and long-term mortality was estimated with multivariable Cox models.ResultsOf the 816 participants in the CIPRA HT-001 trial, 77 were excluded for a history of TB prior to study enrolment and 31 were excluded due to death or attrition prior to the index date, leaving 574 in the no-TB and 134 in the TB cohort. Twenty-four (17.9%) participants in the TB and 48 (8.4%) in the no-TB cohort died during follow-up. Five and 10-year mortality rates were 14.2% and 17.9% respectively, in the TB cohort, and 6.1% and 8.4% in the no-TB cohort. In Kaplan-Meier analysis, participants in the TB cohort had a significantly shorter time to death (log-rank p < 0.001). In multivariable analysis, TB treatment was the only predictor of mortality (HR: 2.78; 95% CI: 1.61, 4.79). Sensitivity analyses, which included only baseline TB cases, an index date of two years after TB diagnosis, and study enrolment and case-control matching yielded results that were consistent with primary analyses.ConclusionsPWH who are successfully treated for TB have higher long-term mortality than those who are never diagnosed with TB, even after accounting for acute TB-related mortality. A better understanding of the underlying mechanisms associated with TB sequelae is critically needed to guide specific interventions. Until then, more aggressive measures for health promotion and disease prevention are essential to improve long-term survival for PWH after TB treatment