Variabilidade espacial e temporal da produtividade do cafeeiro canephora

GIS techniques have been used in many agricultural crops to study and assess the causes of spatial and temporal variability in production. The spatial and temporal variability of the canephora (conilon) coffee productivity was analyzed in the present work in three consecutive agricultural years (harvests) using geoprocessing techniques. A sampling grid with 109 georeferenced points was built with five plants per point. Significant differences in productivity were observed, with the lowest productivity recorded for the harvest 3 in 93.5% of the area. The productivity index (YI) varied from -18.0% in harvest 2 to harvest 1 and from -57.0% in harvest 2 to harvest 3, showing increasing decrease between different harvests.Em várias culturas, tem-se utilizado técnicas de geoprocessamento com intuito de estudar e interpretar as causas da variabilidade espacial e temporal da sua produção. Este trabalho foi desenvolvido objetivando-se analisar a variabilidade espacial e temporal da produtividade do cafeeiro canephora (conilon) em três safras consecutivas, utilizando técnicas de geoprocessamento. Uma malha amostral foi construída com 109 pontos georreferenciados, considerando cinco plantas por ponto. As produtividades apresentaram diferenças significativas, com menor produtividade na safra 3, em 93,5% da área. O índice de produtividade (IP) ficou da safra 2 para a 1 em -18,0% e da safra 3 para a 2 em -57,0%, mostrando redução crescente entre as diferentes safras

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Lógica fuzzy na avaliação da fertilidade do solo e produtividade do café conilon

The objective of this study was to analyze, using the geoestatistic and a system of classification fuzzy, the fertility of an experimental area with base in chemical attributes of the soil and its relationship with the productivity of the conilon coffee. The study was accomplished in the experimental farm of the INCAPER - ES. The soil samples were collected in the depth of 0 - 0.2 m, being analyzed the attributes: matches, potassium, calcium and magnesium, aluminum, sum of bases, cation exchange capacity (pH 7), and saturation percentage. The data were submitted to a descriptive, exploratory, and geostatistical analysis. A system of fuzzy classification was applied using the attributes described to infer about the fertility of the soil and its relationship with the productivity of the culture. The fertility possibility presented positive spatial relationship with the productivity of the culture, with higher values of this where the possibility of fertile soil is superior

Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon.

BackgroundSince its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.Methodology/principal findingsWe report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraima's state, located in the Brazilian Amazon region. We generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraima's population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.Conclusions/significanceThis study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region

Chikungunya virus outbreak in the Amazon region: replacement of the Asian genotype by an ECSA lineage

Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Universidade de São Paulo. Faculdade de Medicina. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Patologia Experimental. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Patologia Experimental. Salvador, BA, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil / Fundação Ezequiel Dias. Instituto Octávio Magalhães. Laboratório Central de Saúde Pública. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Universidade Federal do Rio de Janeiro. Instituto de Biologia. Departamento de Genética Laboratório de Virologia Molecular. Rio de Janeiro, RJ, Brazil.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Harvard Medical School. Department of Pediatrics. Boston, MA, USA / Boston Children’s Hospital. Computational Health Informatics Program. Boston, MA, USA.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom / Boston Children’s Hospital. Computational Epidemiology Lab. Boston, MA, USA.University of Birmingham. Institute of Microbiology and Infection. Birmingham, United Kingdom.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Universidade de São Paulo. Faculdade de Medicina. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Laboratório Central de Saúde Pública. Boa Vista, RR, Brazil.Laboratório Central de Saúde Pública. Boa Vista, RR, Brazil.Laboratório Central de Saúde Pública. Boa Vista, RR, Brazil.Secretaria Municipal de Saúde de Boa Vista. Superintendência de Vigilância em Saúde. Boa Vista, RR, Brazil.Fundação de Medicina Tropical Doutor Heitor Vieira. Departamento de Virologia. Manaus, AM, Brazil.Secretaria Municipal de Saúde de Boa Vista. Superintendência de Vigilância em Saúde. Boa Vista, RR, Brazil.Laboratório Central de Saúde Pública do Amazonas. Manaus, AM, Brazil.Organização Pan - Americana da Saúde/Organização Mundial da Saúde. Brasília, DF, BrazilMinistério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.University of Birmingham. Institute of Microbiology and Infection. Birmingham, United Kingdom.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Universidade de São Paulo. Faculdade de Medicina. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Background Since its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country. Methodology/Principal Findings We report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraima’s state, located in the Brazilian Amazon region. In just 48 hours, we generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraima’s population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima. Conclusions/Significance This study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region

Resumos concluídos - Saúde Coletiva

Resumos concluídos - Saúde Coletiv

Resumos concluídos - Saúde Coletiva

Resumos concluídos - Saúde Coletiv