ABSTRACT
The SARS-CoV-2 pandemic has demonstrated the need for genomic epidemiology surveillance. To date, various methodologies have been applied, including metagenomic approaches and amplicon-based sequencing associated with high-throughput sequencing platforms. We adapted some details in amplicon-based sequencing using a SARS-CoV-2 community panel (Illumina AmpliSeq), with additional modifications for balanced and high-quality sequencing using the MiSeq platform. The modified protocol was used to detect circulating SARS-CoV-2 variants in Goiás state, Brazil. Initially, RNA samples were obtained from swab samples from 15 patients from the state of Goiás, Brazil, in November/2020 and February/2021 to validate protocol steps. The libraries were prepared following AmpliSeq for Illumina workflow with modifications;subsequently, we analyzed 305 positive samples collected from the state of Goiás from December 2020 to July 2021. For protocol improvement, we removed the need to treat samples with DNAse and demonstrated the importance of quantification by qPCR before and after library dilution. No fragmentation pattern was observed in the samples analyzed with Bioanalyzer. The libraries returned sequencing results that were used for genome assembly and variant detection. We were able to assemble SARS-CoV-2 genomes from 318 samples, which were used to identify 13 variants of coronavirus circulating in Goiás throughout those months. Variants of concern, such as Alpha (B.1.1.7), Gamma (P.1) and Delta (B.1.617.2) were detected;the latter was detected at first in Goiás in April 2021. The modifications in the workflow we developed were successfully applied to detect SARS-CoV-2 variants, resulting in high coverage genome assembly, and they can be used to increase the number of genome sequences and aid in epidemiological surveillance in Brazil.
ABSTRACT
With the suspension of presential classes due to Covid-19, Remote Learning was adopted, imposing obstacles to the teachers. Therefore, the objective of this research was to investigate how the work of teachers has developed during the pandemic of Covid-19. To fulfill this, a questionnaire to be answered by teachers in the area of Nature Science and Mathematics in basic education was prepared and shared through social networks, obtaining 43 responses. From these, it was concluded that the teachers are not sufficiently trained to act in processes mediated by digital resources, in addition to not believing that they receive the proper support from the institutions in which they work. They also question the effectiveness of their students' learning and assess their engagement. in remote activities as just regular. The results thus pointed to the precariousness of the profession and the need for investments in teachers.
ABSTRACT
The COVID-19 pandemic has affected people's lives as well as the economies of several countries, the health, education, and transportation sectors, among others. To try to contain the spread of the virus, several countries have implemented health barriers at airports, bus stations, stations, company entrance halls, and other shared spaces to detect patients with any symptom of the viral infection. Since fever is one of the most recurrent symptoms of the disease, a rush to the markets for devices to measure body temperature has begun. Thermal imaging cameras, also known as thermal imagers, are other devices used to measure temperature, employing technology known as infrared thermography, a non-invasive, fast and objective tool. In this study, we applied machine learning transfer on YOLO to detect the hottest regions of the human face in thermographic images, allowing the identification of feverish state in humans. To do this, the artificial intelligence algorithms detect the regions of interest in thermographic images, which are: the eyes, forehead and ears, and then the temperatures in these regions are analyzed. The developed software showed excellent performance in detecting the established regions of interest, which adequately indicates the maximum temperature within the regions of interest, and that the choice of the maximum temperature method was adequate.
ABSTRACT
Due to the Covid-19 pandemic, many places with high traffic of people set up sanitary barriers to screening febrile people. Thermal imagers and pyrometers are the equipment commonly used to measure temperature in these barriers. In this paper, Temperature measurements performed by these instruments were compared considering the regions usually monitored in these barriers: forehead, ear, and wrist. The temperatures of volunteers were recorded after initial acclimatization, a short period of physical exercise, and a rest period after exercise, evaluating the instruments and regions of measurement and the influence of the condition of rest and physical exercise of the person. The compatibility of the performed measurements in each of these three moments was then compared using statistical and metrological tools. The outcomes showed that the pyrometer has low repeatability since its results vary widely among different measurements due to the temperature variation existing within the analyzed region and the difficulty of guaranteeing the same measurement point. As a result, a thermal imager is more recommended for taking body temperature measurements on the forehead and, preferably, on the ear. It was also determined that the wrist, in particular, has a significantly lower temperature than the central body temperature, and thus this is not a recommended region to measure body temperature when screening febrile people.
ABSTRACT
Background: Use of patient-reported outcomes (PRO) to evaluate symptoms improves clinical outcomes. Best practices for implementing PROs into routine care may vary according to clinical scenario, site-specific resources and programmatic goals. Patients with metastatic breast cancer (MBC) often experience a variety of symptoms. Methods: As a quality improvement project, we are pilot testing incorporation of a battery of PRO measures into routine care for patients with MBC at Johns Hopkins in order to gain experience that will guide future broader implementation of PROs across our program. Participants complete the PROs on paper at baseline (BL), 3, and 6 months (mo). Measures include NCCN Distress Thermometer (BL only), Patient Health Questionnaire-8 (PHQ-8), Generalized Anxiety Disorder-7 (GAD-7), PRO-CTCAE Insomnia questions and a modified version of the revised Edmonton Symptom Assessment System (rESAS) questionnaire with 3 extra symptom domains. Project team members alert clinicians by email of scores that exceed severity thresholds as follows-Distress: ≥4, PHQ-8: ≥8, GAD-7: ≥10, any item on r-ESAS: ≥4 and PROCTCAE Insomnia: Severe/very severe or quite a bit/very much. Results: From May 29, 2020 and April 5, 2021, 67 patients were approached for participation, and 40 (59.7%) completed the BL PROs. Median age was 64 (range 36-85). Most participants were White (70%), non-Hispanic (90%) and had hormone receptor-positive (93%) MBC. At BL, 22 (55%) had visceral disease and most were receiving endocrine-based regimens [21 (53%)] or chemotherapy [16 (40%)]. 27 (68%) participants had ≥1 BL alert. The most common BL alerts were for symptoms on the r-ESAS [23 participants (58%)]. The most frequent items on the r-ESAS for which participants had BL alerts were pain, tiredness, well-being, tingling/numbness and rash. Other BL alerts were: Distress [9 participants (23%)], PROCTCAE Insomnia [5 participants (13%)], PHQ-8 [4 participants (10%)] and GAD-7 [2 participants (5%)]. To date, 24 of 35 (69%) and 15 of 28 (54%) participants who have reached the 3 and 6 mo time points have completed the respective follow-up (FU) PROs. Most common FU alerts to date are on the r-ESAS [3 mo: 14 participants (58%), 6 mo: 9 participants (60%)]. The project team has successfully notified providers of all alerts to date. Clinical actions (phone calls, provider visits and/or referrals) have been taken within 30 days of notification for > 75% of alerts. Conclusions: Implementation of a PRO battery for patients receiving routine care for MBC led to detection of a range of symptoms, the majority of which were clinically actionable. Restrictions on in-person interactions during the COVID-19 pandemic may have contributed to low rates of PRO completion in this pilot project. Prior to broader implementation, we will consider strategies such as an electronic platform and a shorter battery to enhance patient engagement.
ABSTRACT
This article presents a model that aims to identify with Machine Learning (ML) technics the main symptoms and risk factors affected in patients with Coronavirus Covid-19, registered in the database of epidemiological surveillance of state and municipal information in Brazil. The concept behind ML is the ability to learn and reason. Its application can optimize and make the treatment and care process more accurate for the cases diagnosed with the Covid-19, also known as SARS-CoV-2, adjusting the medical data recorded concerning the disease and reducing the number of symptoms and risk factors, denoting an efficient form of attribute engineering, providing those involved with the clinical observation of a minor sign. We propose an approach structured in the composition of Machine Learning algorithms, aiming to discover knowledge and concepts followed by the refinement of the results. In this article, the proposed model is presented, and a shorter trail of symptomatic observations from Covid-19 are provided. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The COVID-19 pandemic is currently advancing in the world and has killed more people than other recent coronavirus outbreaks like SARS and MERS together. Coronaviruses known to infect humans were all associated to mammal sources, with different species acting as both natural and/or intermediate hosts of these viruses. Although the zoonotic origin of human coronaviruses is well accepted, a great number of mammal species were not yet investigated as their potential to carry these viruses. This work aimed to provide an overview of the current state of scientific knowledge about what are the mammal groups well known to be associated to coronaviruses and other viruses and what are the most neglected groups in these studies. Here we analyze the production of scientific publications about these and other viruses in association with the 29 taxonomic orders of the Mammalia class. Our results highlighted that most of these taxonomic orders have been little studied or completely unexplored in researches with this focus, with only six orders accumulating more than 99% of the articles on coronaviruses in mammals. Ten mammal groups were not found in any scientific publication in association with coronaviruses, with four of them not found even in works mentioning any type of viruses. These results reinforce the importance of identify all the natural and intermediate hosts for viruses to improve monitoring of potential zoonosis and reduce the chances of new disease outbreaks.
ABSTRACT
The aim of this work is to make known the Olympic Education Program (PEO) that has been implemented in Portugal, since 2015, by the Olympic Committee of Portugal (COP). Based on an analysis of the experiences and implementation of similar programs in other countries, in particular the Olympic Values Educational Programme (OVEP), developed by the International Olympic Committee (IOC), an Olympic Education Program was created following international orientations and good practices experiences. In addition to these contributions, it was considered to implement and develop new content aiming at facilitating daily activities carried on by teachers and educators in Portuguese teaching institutions;themes such as the Portuguese participation in the summer and winter Olympic Games, Olympic Medallists or Portuguese Olympic Champions, were addressed. In order to respond to new challenges faced by schools due to the emergence of the COVID-19 pandemic, the activities implemented in 2020 are also discussed, they aimed to make the Olympic Education Program more flexible and dynamic, by making available, online, new sets of contents and activity proposals.
ABSTRACT
The article seeks to explore some contradictions about the structurally residual participation of the Brazilian capitalist state in the costs of reproduction and maintenance of the labor force. Such participation appears to be even more residual in the context of the Covid-19 pandemic. From a critical perspective, bibliographic research was used as a methodological resource to mediate the analytical construction presented here. The text highlights state participation in the reproduction of the labor force, underlining the constitution of the Brazilian state, of a dependent type, placing it in the context of the advance of neoliberalism. In addition, we sought to make brief inferences about the worsening of living and working conditions in the context of the pandemic. As a result, it is argued that the type of capital development and the structural constitution of the Brazilian State maintains and deepens gradually and steadily the responsibility of workers for the costs of reproduction and maintenance of workforce in past, present and future.
ABSTRACT
Recent studies highlight the importance of digital surveillance to gather individual health information due to the global pandemic caused by the new COVID-19 disease. This paper analyses its legal and ethical implications at the interface between the individual right to privacy and the collective interests of public health. We framed the discussion in law, deontology and utilitarianism. The lasted theories and human rights, especially privacy, are crucial in our argument. Health-derived dilemmas and efforts to solve them, especially by information technologies, bioethics and law, exist at these perspectives' interface. In particular, we analysed the intersection between autonomy, the right to privacy, and the so-called 'right to be forgotten' in the public health context. In other words, we studied the right to obtain from the controller the erasure of health data - a radical means of control over personal data established in Article 17 of the General Data Protection Regulation (GDPR). Given the lack of specifics regarding collection and re-use of such data under the broad scope of public health purposes, implied consent does not address the issue of proportionality. We highlight legal safeguards' insufficiency, suggesting applying the `right to be forgotten' according to an ethical interpretation.
ABSTRACT
Objectives: To develop a flow to ensure care for all people with severe acute respiratory syndrome coronavirus 2, offering from intensive care to palliative care, in an equitable and fair manner.