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

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

Structure for prevention of health care-associated infections in Brazilian hospitals: A countrywide study

Background: Minimal structure is required for effective prevention of health careeassociated infection (HAI). The objective of this study was to evaluate the structure for prevention of HAI in a sample of Brazilian hospitals. Methods: This was a cross-sectional study from hospitals in 5 Brazilian regions (n = 153 total beds: 13,983) classified according to the number of beds 11 university hospitals were used as reference for comparison. Trained nurses carried out the evaluation by using structured forms previously validated. The evaluation of conformity index (CI) included elements of structure of the Health CareeAssociated Prevention and Control Committee (HAIPCC), hand hygiene, sterilization, and laboratory of microbiology. Results: The median CI for the HAIPCC varied from 0.55-0.94 among hospital categories. Hospitals with > 200 beds had the worst ratio of beds to sinks (3.9 P <. 001). Regarding alcoholic product for handrubbing, the worst ratio of beds to dispensers was found in hospitals with < 50 beds (6.4) compared with reference hospitals (3.3 P<.001). The CI for sterilization services showed huge variation ranging from 0.0-1.00. Reference hospitals were more likely to have their own laboratory of microbiology than other hospitals. Conclusion: This study highlights the need for public health strategies aiming to improve the structure for HAI prevention in Brazilian hospitals.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Ministry of Health of Brazil, under the call MCT/CNPq/CT-Saude/MS/SCTIE/DECITUniv Sao Paulo, Sch Nursing, Dept Collect Hlth Nursing, BR-05403000 Sao Paulo, BrazilState Univ Sao Paulo, Botucatu Sch Med, Dept Infect Dis, Botucatu, SP, BrazilUniv Fed Sao Paulo, Special Clin Microbiol Lab, Infect Dis Discipline, Sao Paulo, BrazilUniv Fed Rio Grande do Sul, Clin Hosp Porto Alegre, Ctr Expt Res, Lab Res Bacterial Resistance, Porto Alegre, RS, BrazilFed Univ Para, Dept Infect Dis, BR-66059 Belem, Para, BrazilPequeno Principe Hosp, Epidemiol & Infect Control Dept, Curitiba, Parana, BrazilUniv Fed Ceara, Fac Med, Dept Community Hlth, Fortaleza, Ceara, BrazilUniv Fed Paraiba, Clin Microbiol Discipline, BR-58059900 Joao Pessoa, Paraiba, BrazilHosp Infect Control Comm, Inst Med Integral Prof Fernando Figueira, Recife, PE, BrazilPontifical Catholic Univ, Dept Nursing, Goiania, Go, BrazilUniv Fed Uberlandia, Inst Biomed Sci, Microbiol, BR-38400 Uberlandia, MG, BrazilFundacao Oswaldo Cruz, Nucleo Vigilancia Hosp, Inst Nacl Saude Mulher Crianca & Adolescente Fern, Rio De Janeiro, BrazilUniv Fed Sao Paulo, Div Infect Dis, Sao Paulo, BrazilSpecial Clinical Microbiology Laboratory, Infectious Diseases Discipline, Federal University of São Paulo, São Paulo, BrazilDivision of Infectious Diseases, Federal University of São Paulo, São Paulo, BrazilCNPq: 563225/2010-6MCT/CNPq/CT-Saude/MS/SCTIE/DECIT: 40/2010.Web of Scienc

Ocorrência de tuberculose doença entre contatos de tuberculose sensível e multirresistente Occurrence of active tuberculosis in households inhabited by patients with susceptible and multidrug-resistant tuberculosis

INTRODUÇÃO: Desde os primeiros anos da quimioterapia anti-tuberculose, existe polêmica a respeito da transmissibilidade, infectividade, virulência e patogenicidade de bacilos sensíveis e resistentes à quimioterapia. OBJETIVO: Determinar a ocorrência de casos de tuberculose doença entre contatos intra-domiciliares de tuberculose multirresistente e tuberculose sensível. MÉTODO: Foi realizado um estudo caso-controle, sendo considerado tuberculose multirresistente o caso de portador de bacilo resistente a pelo menos rifampicina e isoniazida, e tuberculose sensível o caso que tivesse feito o primeiro tratamento num período semelhante ao primeiro tratamento do caso de tuberculose multirresistente, estando o paciente curado no momento da entrevista. Contato foi definido como o residente no domicílio do caso índice. Os casos foram selecionados a partir dos resultados dos testes de sensibilidade obtidos pelo método das proporções no Laboratório Central do Estado do Ceará, e os controles constituídos por pacientes bacilíferos registrados no Programa de Controle da Tuberculose, entre 1.990 e 1.999. RESULTADOS: Foram avaliados 126 portadores de tuberculose multirresistente e 176 de tuberculose sensível. O número de contatos foi de 557 no grupo dos casos, 752 no grupo controle e a média de contatos por caso índice foi de 4,42 e 4,27 respectivamente. Entre os casos, 4,49% dos contatos (25/557) fizeram tratamento para tuberculose após os casos índices. Esse percentual foi de 5,45% (41/752) entre os controles (p = 0,4468). Ocorreu micro-epidemia de tuberculose multirresistente confirmada por teste de sensibilidade em oito famílias. CONCLUSÃO: Os resultados deste estudo sugerem que a ocorrência de tratamentos de tuberculose gerados entre contatos intra-domiciliares de tuberculose sensível e tuberculose multirresistente é semelhante.<br>BACKGROUND: Since the first years of antituberculosis chemotherapy, there has been controversy regarding the transmissibility, infectiousness, virulence and pathogenicity of susceptible and drug-resistant strains of Mycobacterium tuberculosis. OBJECTIVE: To determine the incidence of active tuberculosis (TB) among individuals cohabiting with patients infected with susceptible and multidrug-resistant tuberculosis (MDR-TB). METHODS: A case-control study was conducted. Cases of MDR-TB were defined as those infected with M. tuberculosis strains resistant to at least rifampin and isoniazid. Susceptible TB cases (controls) were defined as those first treated at approximately the same time as the first treatment of the MDR-TB cases - and cured by the time of the interview. Study cases were selected on the basis of the results of susceptibility tests, using the proportion method, carried out at the Central Laboratory of Public Health of the State of Ceará. The control group consisted of patients enrolled in the Tuberculosis Control Program between 1990 and 1999. RESULTS: We evaluated 126 patients and 176 controls. The number of individuals sharing the household with patients was 557 in the MDR-TB group and 752 in the controls. The average number of exposed individuals per index case was 4.42 and 4.27 among patients and controls, respectively. Of the 557 MDR-TB-exposed individuals, 4.49% (25) received antituberculosis treatment after the respective index case had begun treatment, compared to 5.45% (41/752) among the controls (p = 0.4468). Microepidemics of MDR-TB were confirmed in eight families. CONCLUSION: Our results suggest that the incidence of active TB is comparable between households inhabited by MDR-TB patients and those inhabited by susceptible-TB patients