5 research outputs found
Tuberculose em área endêmica na Bahia, Brasil: análise de tendência de uma década
Objetivo: Descrever os casos de tuberculose, com base no perfil clĂnico-epidemiolĂłgico e na distribuição geográfica, no perĂodo de 2010 a 2020, em uma área endĂŞmica da Bahia, Brasil. MĂ©todo: Estudo realizado a partir de dados secundários obtidos mediante consulta Ă s fichas de notificação de tuberculose de um centro de referĂŞncia no municĂpio de Paulo Afonso, Bahia, Brasil. Os casos notificados de tuberculose entre 2010 e 2020 foram incluĂdos e submetidos Ă análise estatĂstica e distribuição espacial. Resultados: Dos 391 casos, 90,8% foram diagnosticados como tuberculose pulmonar, com mĂ©dia de 25,9 casos por 100.000 habitantes na sĂ©rie histĂłrica. Do total de casos, 69,8% eram do sexo masculino, 49,6% tinham idade entre 31 e 59 anos, mĂ©dia de idade 43,4 ± 17.7 anos, 62,1% eram bacilĂferos e a maioria dos pacientes foram categorizados como casos novos (81,6%). Ao final do tratamento da TB, 75,7% apresentaram um resultado bem-sucedido (curado) e 48,8% dos casos receberam terapia diretamente observada. Na distribuição espacial, observou-se aglomerados nas macrozonas insular e sul no municĂpio de Paulo Afonso. ConclusĂŁo: A tuberculose persiste como significativo problema de saĂşde pĂşblica no municĂpio e medidas para melhorar o diagnĂłstico precoce e o tratamento sĂŁo essenciais, principalmente apĂłs a pandemia da COVID-19, considerando o perfil epidemiolĂłgico e a distribuição espacial da doença.Objective: To describe the tuberculosis cases, based on clinical-epidemiological profile and geographic distribution, from 2010 to 2020 in an endemic area in Bahia, Brazil. Method: It was a study based on secondary data obtained of individual tuberculosis reporting forms from a reference center in Paulo Afonso municipality, Bahia, Brazil. Reported tuberculosis cases between 2010 and 2020 were included and submitted to statistical analysis and spatial distribution. Results: Among the 391 cases, 90.8% had a pulmonary form with a mean of 25.9 cases per 100,000 inhabitants in the historical series. Of all cases, 69.8% were male, 49.6% were aged between 31 and 59 years, mean age 43.4 ± 17.7 years, 62.1% were smear-positive and most of the cases were new (81.6%). At the end of TB treatment, 75.7% had a successful outcome (cured) and 48.8% patients received directly observed therapy. In the spatial distribution, we observed agglomerates in the insular and south macrozones in Paulo Afonso municipality. Conclusion: Tuberculosis remains a significant public health problem in the municipality, and measures to improve early diagnosis and treatment are crucial, especially following the onset of the COVID-19 pandemic, considering the epidemiological profile and spatial distribution of the disease
Análise da cobertura vacinal por BCG nos 20 municĂpios mais populosos da Bahia: uma sĂ©rie histĂłrica de 2011 a 2021
Introdução: Tuberculose (TB), doença crĂ´nica infectocontagiosa causada por Mycobacterium tuberculosis, Ă© considerada um grave problema de saĂşde pĂşblica. Em 2021, estima-se que a TB foi responsável por, aproximadamente, 1,6 milhões de Ăłbitos no mundo. Diante desse cenário, percebe-se a importância das medidas de prevenção e controle da doença, como a vacinação com o bacilo de Calmette-GuĂ©rin (BCG). Objetivo: avaliar a cobertura vacinal (CV) do BCG e analisar as taxas de incidĂŞncia e mortalidade decorrentes da TB em menores de 1 ano de idade. Metodologia: o estudo possui caráter descritivo ecolĂłgico-espacial, em que foram analisadas as taxas de CV nos 20 municĂpios mais populosos da Bahia, no perĂodo de 2011 a 2021. Resultados: observou-se uma CV mĂ©dia de 103% ± 18,5%. No entanto, nove (45%) municĂpios apresentaram tendĂŞncia decrescente na CV, especialmente em Feira de Santana (P<0,0001). A partir de 2015, observa-se uma queda considerável das CV e da homogeneidade entre os municĂpios, acentuando-se apĂłs 2019. Em relação Ă incidĂŞncia, o municĂpio com maior nĂşmero de casos de TB foi Candeias, com 85 casos por 100.000 habitantesem menores de um ano de idade. Por fim, apenas trĂŞs municĂpios relataram a presença de Ăłbitos por TB extrapulmonar, sendo a maior taxa registrada em IlhĂ©us com 2,7%. ConclusĂŁo: o estudo evidencia uma importante redução e heterogeneidade nas CV dos municĂpios analisados, e fomenta a importância de ações mais efetivas de vacinação e controle da TB baseadas nas necessidades locais de cada municĂpio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost