Impacto e sequelas das manifestações neurológicas da Covid-19

Introdução: A infecção por SARS-CoV-2 foi identificada pela primeira vez em dezembro de 2019, na China, e rapidamente espalhou-se por todo o mundo. Houve um crescente número de casos com envolvimento neurológico da COVID-19, que podem estar associados a sintomas mais severos ou sequelas. Objetivo: investigar as manifestações neurológicas ocorridas ou persistentes após a COVID-19, correlacionando-as com variáveis clínicas dos indivíduos acometidos e seus possíveis impactos biopsicossociais. Metodologia: estudo exploratório, observacional do tipo quantitativo, usando-se formulário eletrônico respondido em 2021 por 800 voluntários que tinham previamente tido covid. Usou-se o teste de chi quadrado de Pearson para correlacionar as variáveis. Resultados: observou-se predominância do sexo feminino (73,6%), idade média de 29,6 ±10 anos, e diagnóstico de COVID-19 feito através de teste laboratorial (77%). Os principais sintomas neurológicos apresentados durante a infecção foram cefaleia (72%), seguida de “dor no corpo” (66,6%) e perda/distorção do olfato ou paladar (66,1%). Oitenta por cento dos participantes referiu ter apresentado sintomas neurológicos pós-infecciosos, sendo que as mais prevalentes foram dificuldade de atenção (42%), seguido de fadiga (35,2%) e dor de cabeça (35,1%). A análise estatística demonstrou que ser do sexo feminino (p=0,0001) e ter apresentado dificuldade respiratória durante a infecção aguda (p=0,0001) foram os maiores fatores de risco preditores para o aparecimento de sintomas neurológicos pós-infecciosos. Observou-se que 64% dos participantes acometidos por sintomas neurológicos pós-Covid relataram algum impacto em sua vida diária, havendo correlação com doença crônica (p=0,001) e doença respiratória durante a infecção (p=0,001). Conclusão: o acometimento neurológico pode ser parte relevante em todas as fases da covid, sendo sua identificação e abordagem terapêutica efetivas essenciais para proporcionar menor impacto na vida dos indivíduos acometidos, inclusive a longo prazo

Casos confirmados de Esquistossomose no Pará no período de 2007 a 2017 / Confirmed cases of Schistosomiasis in Pará in the period 2007 to 2017

Introdução: A esquistossomose é uma doença crônica causada pelos parasitas multicelulares platelmintos do gênero Schistosoma. A esquistossomose possui o homem como hospedeiro definitivo, modificações ambientais e condições inadequadas de saneamento básico são as principais responsáveis pelo aumento do número de transmissores e de seus focos de transmissão. Sendo uma doença relacionada fortemente com as condições socioeconômicas da população.Objetivo: Analisar os casos confirmados de Esquistossomose de 2007 a 2017 no Pará.Método: Trata-se de um estudo descritivo, feito com base em dados recolhidos por meio de fichas de notificação compulsórias do SINAN presentes no DATASUS. Foram recolhidas informações condizentes com o ano da notificação, cidades e escolaridade durante o período de 2007 a 2017.Resultados: Foram encontrados 174 casos notificados, sendo que a maioria ocorreu no ano de 2009 (22,9%), enquanto que minoria ocorreu no ano de 2007 (2,2%). Além disso a cidade mais afetada foi a cidade de Altamira (23,5%), porém acredita-se que possam existir subnotificações em outras cidades do estado. No que diz respeito a escolaridade, os mais afetados foram pacientes com escolaridade da 1ª à 4ª série incompleta do ensino fundamental (20,6%), seguidos pelos analfabetos (17,8%).Conclusão: Foi visto um acréscimo aos casos de notificação compulsória de Esquistossomose no Pará em um comparativo dos anos de 2007 e 2017. No entanto, acredita-se que ainda há muitas subnotificações, principalmente nas cidades mais interioranas.

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

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000-18 : a geospatial modelling study

Background More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.Methods We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km x 5 km resolution in 98 LMICs based on 2.1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.Findings Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205000 (95% uncertainty interval 147000-257000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.Interpretation Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

A ética do silêncio racial no contexto urbano: políticas públicas e desigualdade social no Recife, 1900-1940

Mais de meio século após o preconceito racial ter se tornado o principal alvo dos movimentos urbanos pelos direitos civis nos Estados Unidos e na África do Sul, e décadas depois do surgimento dos movimentos negros contemporâneos no Brasil, o conjunto de ferramentas legislativas criado no Brasil para promover o direito à cidade ainda adere à longa tradição brasileira de silêncio acerca da questão racial. Este artigo propõe iniciar uma exploração das raízes históricas desse fenômeno, remontando ao surgimento do silêncio sobre a questão racial na política urbana do Recife, Brasil, durante a primeira metade do século XX. O Recife foi eé um exemplo paradigmático do processo pelo qual uma cidade amplamente marcada por traços negros e africanos chegou a ser definida política e legalmente como um espaço pobre, subdesenvolvido e racialmente neutro, onde as desigualdades sociais originaram na exclusão capitalista, e não na escravidão e nas ideologias do racismo científico. Neste sentido, Recife lança luzes sobre a política urbana que se gerou sob a sombra do silêncio racial.More than half a century after racial prejudice became central to urban civil rights movements in the United States and South Africa, and decades after the emergence of Brazil’s contemporary Black movements, Brazil's internationally recognized body of rights-to-the-city legislation still adheres to the country's long historical tradition of racial silence. This article explores the historical roots of this phenomenon by focusing on the emergence of racial silence in Recife, Brazil during the first half of the 20th Century. Recife was and remains a paradigmatic example of the process through which a city marked by its Black and African roots came to be legally and politically defined as a poor, underdeveloped and racially neutral space, where social inequalities derived from capitalist exclusion rather than from slavery and scientific racism. As such, Recife'sexperience sheds light on the urban policies that were generated in the shadow of racial silence

Sensitivity of South American tropical forests to an extreme climate anomaly

The tropical forest carbon sink is known to be drought sensitive, but it is unclear which forests are the most vulnerable to extreme events. Forests with hotter and drier baseline conditions may be protected by prior adaptation, or more vulnerable because they operate closer to physiological limits. Here we report that forests in drier South American climates experienced the greatest impacts of the 2015–2016 El Niño, indicating greater vulnerability to extreme temperatures and drought. The long-term, ground-measured tree-by-tree responses of 123 forest plots across tropical South America show that the biomass carbon sink ceased during the event with carbon balance becoming indistinguishable from zero (−0.02 ± 0.37 Mg C ha −1 per year). However, intact tropical South American forests overall were no more sensitive to the extreme 2015–2016 El Niño than to previous less intense events, remaining a key defence against climate change as long as they are protected

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