1,589 research outputs found
CoronaviridaeâOld friends, new enemy!
Coronaviridae is a family of singleâstranded positive enveloped RNA viruses. This article aimed to review the history of these viruses in the last 60 years since their discovery to understand what lessons can be learned from the past. A review of the PubMed database was carried out, describing taxonomy, classification, virology, genetic recombination, host adaptation, and main symptoms related to each type of virus. SARSâCoVâ2 is responsible for the ongoing global pandemic, and SARSâCoV and MERSâCoV were responsible for causing severe respiratory illness and regional epidemics in the past while the four other strains of CoVs (229âE OC43, NL63, and HKU1) circulate worldwide and normally only cause mild upper respiratory tract infections. Given the enormous diversity of coronavirus viruses in wildlife and their continuous evolution and adaptation to humans, future outbreaks would undoubtedly occur. Restricting or banning all trade in wild animals in wet markets would be a necessary measure to reduce future zoonotic infections
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 postâthe 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, MaranhĂŁo, PiauĂ, Rio Grande do Norte, AmapĂĄ, RondĂŽnia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for EspĂrito Santo, Minas Gerais, ParanĂĄ, 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
National equipment of intraoperatory gamma detection in the identification of sentinel lymph node in animal model
Efeitos da densidade de plantas no rendimento comercial de espigas verdes de cultivares de milho
Cultivares de batata para sistemas orgùnicos de produção.
InformaçÔes a respeito de cultivares adaptadas ao sistema de cultivo orgĂąnico sĂŁo escassas. O objetivo deste estudo foi avaliar, sob sistema de cultivo orgĂąnico, genĂłtipos nacionais e estrangeiros desenvolvidos para o cultivo convencional, quanto ao potencial produtivo, em condiçÔes de campo. O experimento foi conduzido em 2008, no PĂłlo APTA Leste Paulista, em Monte Alegre do Sul-SP. O delineamento experimental foi em blocos ao acaso, com 18 tratamentos e quatro repetiçÔes. Cada parcela foi constituĂda por 80 batatas-semente, dispostas em quatro linhas de 5 m de comprimento, espaçadas de 80 cm, com 25 cm entre tubĂ©rculos. Os genĂłtipos avaliados foram Agata, Asterix, Caesar, Cupido, Ăden, Melody, Novella e Vivaldi, de origem estrangeira; e ApuĂŁ, Aracy, Catucha, IAC Aracy Ruiva, ItararĂ©, Monte Alegre 172, IAC 6090, APTA 16.5, APTA 15.20 e APTA 21.54, nacionais. Foram avaliadas as caracterĂsticas de produtividade total e comercial de tubĂ©rculos, massa mĂ©dia total e comercial de tubĂ©rculos, teor de matĂ©ria seca e severidade da pinta-preta (Alternaria solani). Os clones APTA 16.5, APTA 21.54 e IAC 6090, e as cultivares Cupido, ApuĂŁ, ItararĂ© e Monte Alegre 172 foram os mais produtivos. âAPTA 21.54â superou os demais em relação a produtividade comercial (18,07 t ha-1), sendo que âAPTA 16.5â, âCupidoâ, âIAC 6090â e âItararĂ©â formaram o segundo grupo. As maiores massas mĂ©dias de tubĂ©rculos foram apresentadas pelas cultivares ItararĂ© e Cupido. O clone IAC 6090 e as cultivares Aracy e Aracy Ruiva foram as que apresentaram maiores teores de matĂ©ria seca, com valor mĂ©dio de 22,91%. âAPTA 16.5â, âApuĂŁâ, âAracyâ, âAracy Ruivaâ, âĂdenâ, âIbituaçĂșâ e âMonte Alegre 172â apresentaram alto nĂvel de resistĂȘncia Ă pinta-preta. As cultivares ItararĂ©, ApuĂŁ e Cupido sĂŁo adaptadas ao cultivo orgĂąnico, e os clones avançados APTA 16.5, APTA 21.54 e IAC 6090 apresentam potencial de cultivo no sistema orgĂąnico
Evaluation of a 25-Year-Program for the Control of Schistosomiasis Mansoni in an Endemic Area in Brazil
A clinical-epidemiological reevaluation on schistosomiasis mansoni was performed in 2005, in the urban area of a little town, Comercinho, MG, specifically focusing on the inhabitants of the same area in 1981, when a first survey and treatment with oxamniquine were carried out. The surveys included: identification of the intermediary host, census, mapping of the city, socioeconomic survey, stool examination, clinical examination, research dealing with contact with natural waters, and treatment of the positive cases. From a population of 1,474 people studied in 1981, 358 were submitted to stool examination, and 231 were clinically examined. From 1981 to 1992 five specific treatments were performed with oxamniquine and the last one with praziquantel. The results obtained were compared and demonstrated that the prevalence in Comercinho decreased significantly (70.4% to 1.7%), as well as the hepatosplenic form (7% to 1.3%) in 1981 and 2005, respectively. Significant improvement in the life quality (improvement in the housing, professional qualification and basic sanitation) were observed and must be considered important for the schistosomiasis control
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