Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. / Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. / Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. / Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America

Concentration-dependent diffusivity and anomalous diffusion: A magnetic resonance imaging study of water ingress in porous zeolite

Magnetic resonance imaging is employed to study water ingress in fine zeolite powders compacted by high pressure. The experimental conditions are chosen such that the applicability of Boltzmann's transformation of the one-dimensional diffusion equation is approximately satisfied. The measured moisture profiles indicate subdiffusive behavior with a spatiotemporal scaling variable eta=x/t(gamma/2) (0 <gamma < 1). A time-fractional diffusion equation model of anomalous diffusion is adopted to analyze the data, and an expression that yields the moisture dependence of the generalized diffusivity is derived and applied to our measured profiles. In spite of the differences between systems exhibiting different values of gamma a striking similarity in the moisture dependence of the diffusivity is apparent. This suggests that the model addresses the underlying physical processes involved in water transport.731

A cultura da interpretação das doenças infecto - contagiosas

As autoras referem comportamentos, atitudes e conhecimentos expressos pelas mães em relação a doenças como: sarampo, varíola, varicela, parotidite, tuberculose e difteria. Trata-se de um relato das informações de mães de baixo nível sócio-econômico que frequentam os Centros de Saúde da cidade do Salvador - Bahia

Lipid-based nanostructures as a strategy to enhance curcumin bioaccessibility: behavior under digestion and cytotoxicity assessment

The aim of this study was to evaluate the behavior of different lipid-based nanostructures during in vitro digestion, in particular on curcumins bioaccessibility, and to access their potential toxicity. Solid lipid nanoparticles (SLN), nanostructured lipid carriers (NLC) and nanoemulsions (NE) were submitted to harmonized static in vitro digestion and their cytotoxicity and cellular transport were evaluated using Caco-2 cell line. NE presented the highest curcumins bioaccessibility followed by NLC and SLN, 71.1%, 63.7% and 53.3%, respectively. Free fatty acids percentage increased in the following order: NLC ? NE < SLN. Non-digested nanostructures and excipients presented no cytotoxicity; however, digested NE and NLC presented cytotoxicity due to MCT oil, which presented cytotoxicity after digestion. The apparent permeability coefficient of NLC was higher than SLN and NE. These results showed that lipid-based nanostructures physical state and composition have a high influence on particles' behavior during digestion, and on their cytotoxicity/intestinal permeability, and highlights the importance of conducting cytotoxicity assessments after in vitro digestion. This work contributes to a better understanding of the behavior of lipid-based nanostructures under digestion/adsorption, and this knowledge will be useful in design of nanostructures that afford both safety and an increased bioactive compounds bioavailability.Acknowledgments Raquel F. S. Goncalves acknowledge the Foundation for Science and Technology (FCT) for her fellowship (SFRH/BD/140182/2018) . This study was supported by Foundation for Science and Technology (FCT) under the scope of Project PTDC/AGRTEC/5215/2014, the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. Funding from INTERFACE Programme through the Innovation, Technology and Circular Economy Fund (FITEC) and iNova4Health, a program also financially supported by Fundacao para a Ciencia eTecnologia, is also gratefully acknowledged.info:eu-repo/semantics/publishedVersio

Urinary incontinence related to perineal muscle strength in the first trimester of pregnancy: cross-sectional study

Objective To analyze pelvic floor muscle strength (PFMS), urinary continence and quality of life related to urinary incontinence (UI) of women in the first trimester of pregnancy. Method Cross-sectional study with a sample of 500 women who started prenatal care in a complementary healthcare facility in Guarulhos, state of São Paulo, from 2012 and 2013. Pelvic floor muscle strength was evaluated through perineometry. The pregnant women who presented UI answered the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF). Results It was found that maternal age (OR=1.06; CI95% 1.02-1.11) and prior UI (OR=15.12; 95%CI 8.19-27.92) are the variables that, in tandem, best explain the occurrence of UI at the beginning of pregnancy. The mean score on the ICIQ-SF was 8.2 (SD=3.9), considered a moderate impact on quality of life. Conclusion Older pregnant women with prior UI are more likely to have UI in the first trimester of pregnancy.
</jats:p

Photosynthetic quantum efficiency in south‐eastern Amazonian trees may be already affected by climate change

Tropical forests are experiencing unprecedented high‐temperature conditions due to climate change that could limit their photosynthetic functions. We studied the high‐temperature sensitivity of photosynthesis in a rainforest site in southern Amazonia, where some of the highest temperatures and most rapid warming in the Tropics have been recorded. The quantum yield (F v /F m ) of photosystem II was measured in seven dominant tree species using leaf discs exposed to varying levels of heat stress. T 50 was calculated as the temperature at which F v /F m was half the maximum value. T 5 is defined as the breakpoint temperature, at which F v /F m decline was initiated. Leaf thermotolerance in the rapidly warming southern Amazonia was the highest recorded for forest tree species globally. T 50 and T 5 varied between species, with one mid‐storey species, Amaioua guianensis , exhibiting particularly high T 50 and T 5 values. While the T 50 values of the species sampled were several degrees above the maximum air temperatures experienced in southern Amazonia, the T 5 values of several species are now exceeded under present‐day maximum air temperatures