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                <text>The global anxiety and a significant threat to public health due to the current COVID-19 pandemic reiterate the need for active surveillance for the zoonotic virus diseases of pandemic potential. Influenza virus due to its wide host range and zoonotic potential poses such a significant threat to public health. Swine serve as a “mixing vessel” for influenza virus reassortment and evolution which as a result may facilitate the emergence of new strains or subtypes of zoonotic potential. In this context, the currently available scientific data hold a high significance to unravel influenza virus epidemiology and evolution. With this objective, the current systematic review summarizes the original research articles and case reports of all the four types of influenza viruses reported in swine populations worldwide. A total of 281 articles were found eligible through screening of PubMed and Google Scholar databases and hence were included in this systematic review. The highest number of research articles (n = 107) were reported from Asia, followed by Americas (n = 97), Europe (n = 55), Africa (n = 18), and Australia (n = 4). The H1N1, H1N2, H3N2, and A(H1N1)pdm09 viruses were the most common influenza A virus subtypes reported in swine in most countries across the globe, however, few strains of influenza B, C, and D viruses were also reported in certain countries. Multiple reports of the avian influenza virus strains documented in the last two decades in swine in China, the United States, Canada, South Korea, Nigeria, and Egypt provided the evidence of interspecies transmission of influenza viruses from birds to swine. Inter-species transmission of equine influenza virus H3N8 from horse to swine in China expanded the genetic diversity of swine influenza viruses. Additionally, numerous reports of the double and triple-reassortant strains which emerged due to reassortments among avian, human, and swine strains within swine further increased the genetic diversity of swine influenza viruses. These findings are alarming hence active surveillance should be in place to prevent future influenza pandemics.</text>
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                <text>The global anxiety and a significant threat to public health due to the current COVID-19 pandemic reiterate the need for active surveillance for the zoonotic virus diseases of pandemic potential. Influenza virus due to its wide host range and zoonotic potential poses such a significant threat to public health. Swine serve as a “mixing vessel” for influenza virus reassortment and evolution which as a result may facilitate the emergence of new strains or subtypes of zoonotic potential. In this context, the currently available scientific data hold a high significance to unravel influenza virus epidemiology and evolution. With this objective, the current systematic review summarizes the original research articles and case reports of all the four types of influenza viruses reported in swine populations worldwide. A total of 281 articles were found eligible through screening of PubMed and Google Scholar databases and hence were included in this systematic review. The highest number of research articles (n = 107) were reported from Asia, followed by Americas (n = 97), Europe (n = 55), Africa (n = 18), and Australia (n = 4). The H1N1, H1N2, H3N2, and A(H1N1)pdm09 viruses were the most common influenza A virus subtypes reported in swine in most countries across the globe, however, few strains of influenza B, C, and D viruses were also reported in certain countries. Multiple reports of the avian influenza virus strains documented in the last two decades in swine in China, the United States, Canada, South Korea, Nigeria, and Egypt provided the evidence of interspecies transmission of influenza viruses from birds to swine. Inter-species transmission of equine influenza virus H3N8 from horse to swine in China expanded the genetic diversity of swine influenza viruses. Additionally, numerous reports of the double and triple-reassortant strains which emerged due to reassortments among avian, human, and swine strains within swine further increased the genetic diversity of swine influenza viruses. These findings are alarming hence active surveillance should be in place to prevent future influenza pandemics.</text>
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                <text>Cancer patients with coronavirus disease 2019 (COVID-19) have been reported to have double the case fatality rate of the general population. A systematic search of PubMed, Embase, and Cochrane Central was done for studies on cancer patients with COVID-19. Pooled proportions were calculated for categorical variables. Odds ratio (OR) and forest plots (random-effects model) were constructed for both primary and secondary outcomes. This systematic review of 38 studies and meta-analysis of 181 323 patients from 26 studies included 23 736 cancer patients. Our meta-analysis shows that cancer patients with COVID-19 have a higher likelihood of death (n = 165 980, OR = 2.54, 95% confidence interval [CI] = 1.47 to 4.42), which was largely driven by mortality among patients in China. Cancer patients were more likely to be intubated. Among cancer subtypes, the mortality was highest in hematological malignancies (n = 878, OR = 2.39, 95% CI = 1.17 to 4.87) followed by lung cancer (n = 646, OR = 1.83, 95% CI = 1.00 to 3.37). There was no association between receipt of a particular type of oncologic therapy and mortality. Our study showed that cancer patients affected by COVID-19 are a decade older than the normal population and have a higher proportion of comorbidities. There was insufficient data to assess the association of COVID-19-directed therapy and survival outcomes in cancer patients. Cancer patients with COVID-19 disease are at increased risk of mortality and morbidity. A more nuanced understanding of the interaction between cancer-directed therapies and COVID-19-directed therapies is needed. This will require uniform prospective recording of data, possibly in multi-institutional registry databases.</text>
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                <text>Abstract Several comorbidities have been shown to be associated with coronavirus disease 2019 (COVID-19) related severity and mortality. However, considerable variation in the prevalence estimates of comorbidities and their effects on COVID-19 morbidity and mortality have been observed in prior studies. This systematic review and meta-analysis aimed to determine geographical, age, and gender related differences in the prevalence of comorbidities and associated severity and mortality rates among COVID-19 patients. We conducted a search using PubMed, Scopus, and EMBASE to include all COVID-19 studies published between January 1st, 2020 to July 24th, 2020 reporting comorbidities with severity or mortality. We included studies reporting the confirmed diagnosis of COVID-19 on human patients that also provided information on comorbidities or disease outcomes. We used DerSimonian and Laird random effects method for calculating estimates. Of 120 studies with 125,446 patients, the most prevalent comorbidity was hypertension (32%), obesity (25%), diabetes (18%), and cardiovascular disease (16%) while chronic kidney or other renal diseases (51%, 44%), cerebrovascular accident (43%, 44%), and cardiovascular disease (44%, 40%) patients had more COVID-19 severity and mortality respectively. Considerable variation in the prevalence of comorbidities and associated disease severity and mortality in different geographic regions was observed. The highest mortality was observed in studies with Latin American and European patients with any medical condition, mostly older adults (≥ 65 years), and predominantly male patients. Although the US studies observed the highest prevalence of comorbidities in COVID-19 patients, the severity of COVID-19 among each comorbid condition was highest in Asian studies whereas the mortality was highest in the European and Latin American countries. Risk stratification and effective control strategies for the COVID-19 should be done according to comorbidities, age, and gender differences specific to geographical location.</text>
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                <text>Korean Society of Epidemiology</text>
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                <text>A systematic review and meta-analysis of the efficacy and safety of remdesivir in COVID-19 patients</text>
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                <text>Sumanta Saha, Sujata Saha</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Background: This systematic review compares the efficacy and safety of remdesivir between its recipient and non-recipient COVID-19 patients from the recently published randomized controlled trials (RCT).   Methods: For eligible trials comparing the above outcomes, a literature search took place in the PubMed database. The reviewed trials data were abstracted and critically appraised using the Cochrane tool. Then, a random-effect meta-analysis followed to compare the risk between the compared interventions in risk ratio (RR). By plying the I2 and Chi2 statistics, the heterogeneity estimation happened. A sensitivity analysis iterated the preliminary meta-analysis using a fixed-effect model.  Results: Two eligible RCTs included in this review sourced data from about 833 COVID-19 patients from 115 hospitals in Asia, Europe, and the US. The risk of bias was primarily low. Random-effect meta-analysis suggested a clinical improvement (RR: 1.09; 95% CI: 1.02, 1.16; P=0.02; I2: 0%) and decrease in the risk of any serious side effects (RR: 0.64; 95% CI: 0.43, 0.94; P</text>
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            <name>Date</name>
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                <text>2021</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>India, covid-19, Remdesivir, Coronavirus infection, Randomized Controlled Trial</text>
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            <name>Identifier</name>
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              <elementText elementTextId="49047">
                <text>10.47108/jidhealth.Vol4.Iss1.99</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="49048">
                <text>Epidemiology and Health</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="49049">
                <text>Korean Society of Epidemiology</text>
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            </elementTextContainer>
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            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <elementText elementTextId="49050">
                <text>Medicine, Medicine (General)</text>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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                <elementText elementTextId="1">
                  <text>Coronavirus</text>
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              </elementTextContainer>
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            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
              <elementTextContainer>
                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
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    </collection>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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    <elementSetContainer>
      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="71251">
                <text>A systematic review of contamination (aerosol, splatter and droplet generation) associated with oral surgery and its relevance to COVID-19</text>
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          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="71252">
                <text>Jennifer E. Gallagher, Sukriti K.C., Ilona G. Johnson, Waraf Al-Yaseen, Rhiannon Jones, Scott McGregor, Mark Robertson, Rebecca Harris, Nicola Innes, William G. Wade</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Abstract Introduction The current COVID-19 pandemic caused by the SARS-CoV-2 virus has impacted the delivery of dental care globally and has led to re-evaluation of infection control standards. However, lack of clarity around what is known and unknown regarding droplet and aerosol generation in dentistry (including oral surgery and extractions), and their relative risk to patients and the dental team, necessitates a review of evidence relating to specific dental procedures. This review is part of a wider body of research exploring the evidence on bioaerosols in dentistry and involves detailed consideration of the risk of contamination in relation to oral surgery. Methods A comprehensive search of Medline (OVID), Embase (OVID), Cochrane Central Register of Controlled Trials, Scopus, Web of Science, LILACS and ClinicalTrials.Gov was conducted using key terms and MeSH (Medical Subject Headings) words relating to the review questions. Methodological quality including sensitivity was assessed using a schema developed to measure quality aspects of studies using a traffic light system to allow inter- and intra-study overview and comparison. A narrative synthesis was conducted for assessment of the included studies and for the synthesis of results. Results Eleven studies on oral surgery (including extractions) were included in the review. They explored microbiological (bacterial and fungal) and blood (visible and/or imperceptible) contamination at the person level (patients, operators and assistants) and/or at a wider environmental level, using settle plates, chemiluminescence reagents or air samplers; all within 1 m of the surgical site. Studies were of generally low to medium quality and highlighted an overall risk of contaminated aerosol, droplet and splatter generation during oral surgery procedures, most notably during removal of impacted teeth using rotatory handpieces. Risk of contamination and spread was increased by factors, including proximity to the operatory site, longer duration of treatment, higher procedural complexity, non-use of an extraoral evacuator and areas involving more frequent contact during treatment. Conclusion A risk of contamination (microbiological, visible and imperceptible blood) to patients, dental team members and the clinical environment is present during oral surgery procedures, including routine extractions. However, the extent of contamination has not been explored fully in relation to time and distance. Variability across studies with regards to the analysis methods used and outcome measures makes it difficult to draw robust conclusions. Further studies with improved methodologies, including higher test sensitivity and consideration of viruses, are required to validate these findings.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="71254">
                <text>2020</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="71255">
                <text>10.1038/s41405-020-00053-2</text>
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            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="71256">
                <text>Epidemiology and Health</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="71257">
                <text>Korean Society of Epidemiology</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="71258">
                <text>Dentistry</text>
              </elementText>
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  <item itemId="1653" public="1" featured="0">
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="1">
                  <text>Coronavirus</text>
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              </elementTextContainer>
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            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
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                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="15821">
                <text>A Systematic Review of COVID-19 Epidemiology Based on Current Evidence</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="15822">
                <text>Min Ah Park, Alex R Cook, Jue Tao Lim, Yinxiaohe Sun, Borame L. Dickens</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="15823">
                <text>As the novel coronavirus (SARS-CoV-2) continues to spread rapidly across the globe, we aimed to identify and summarize the existing evidence on epidemiological characteristics of SARS-CoV-2 and the effectiveness of control measures to inform policymakers and leaders in formulating management guidelines, and to provide directions for future research. We conducted a systematic review of the published literature and preprints on the coronavirus disease (COVID-19) outbreak following predefined eligibility criteria. Of 317 research articles generated from our initial search on PubMed and preprint archives on 21 February 2020, 41 met our inclusion criteria and were included in the review. Current evidence suggests that it takes about 3-7 days for the epidemic to double in size. Of 21 estimates for the basic reproduction number ranging from 1.9 to 6.5, 13 were between 2.0 and 3.0. The incubation period was estimated to be 4-6 days, whereas the serial interval was estimated to be 4-8 days. Though the true case fatality risk is yet unknown, current model-based estimates ranged from 0.3% to 1.4% for outside China. There is an urgent need for rigorous research focusing on the mitigation efforts to minimize the impact on society.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="15824">
                <text>2020</text>
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            </elementTextContainer>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="15825">
                <text>COVID-19, SARS-CoV-2, Epidemiology, Basic reproduction number, Incubation period, serial interval</text>
              </elementText>
            </elementTextContainer>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="15826">
                <text>DOI: 10.3390/jcm9040967</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="15827">
                <text>Journal of Clinical Medicine</text>
              </elementText>
            </elementTextContainer>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="15828">
                <text>MDPI AG</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Medicine</text>
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            </elementTextContainer>
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            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="15830">
                <text>EN</text>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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              <name>Description</name>
              <description>An account of the resource</description>
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                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
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              </elementTextContainer>
            </element>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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              <elementText elementTextId="86741">
                <text>A Systematic Review of Non-Contact Sensing for Developing a Platform to Contain COVID-19</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="86742">
                <text>Qammer  H. Abbasi, Xiaodong Yang, Muhammad  Bilal Khan, Zhiya Zhang, Mohammed Ali Mohammed Al-hababi, Lin Li, Wei Zhao</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="86743">
                <text>The rapid spread of the novel coronavirus disease, COVID-19, and its resulting situation has garnered much effort to contain the virus through scientific research. The tragedy has not yet fully run its course, but it is already clear that the crisis is thoroughly global, and science is at the forefront in the fight against the virus. This includes medical professionals trying to cure the sick at risk to their own health; public health management tracking the virus and guardedly calling on such measures as social distancing to curb its spread; and researchers now engaged in the development of diagnostics, monitoring methods, treatments and vaccines. Recent advances in non-contact sensing to improve health care is the motivation of this study in order to contribute to the containment of the COVID-19 outbreak. The objective of this study is to articulate an innovative solution for early diagnosis of COVID-19 symptoms such as abnormal breathing rate, coughing and other vital health problems. To obtain an effective and feasible solution from existing platforms, this study identifies the existing methods used for human activity and health monitoring in a non-contact manner. This systematic review presents the data collection technology, data preprocessing, data preparation, features extraction, classification algorithms and performance achieved by the various non-contact sensing platforms. This study proposes a non-contact sensing platform for the early diagnosis of COVID-19 symptoms and monitoring of the human activities and health during the isolation or quarantine period. Finally, we highlight challenges in developing non-contact sensing platforms to effectively control the COVID-19 situation.</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="86745">
                <text>covid-19, Non-contact, WiFi, CSI, SDR</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="86746">
                <text>10.3390/mi11100912</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="86747">
                <text>Epidemiology and Health</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="86748">
                <text>Korean Society of Epidemiology</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="86749">
                <text>Mechanical engineering and machinery</text>
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              <name>Title</name>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>A Systematic, Unbiased Mapping of CD8+ and CD4+ T Cell Epitopes in Yellow Fever Vaccinees</text>
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                <text>Morten Nielsen, Morten Nielsen, Anette Stryhn, Michael Kongsgaard, Michael Rasmussen, Mikkel Nors Harndahl, Thomas Østerbye, Maria Rosaria Bassi, Søren Thybo, Mette Gabriel, Morten Bagge Hansen, Jan Pravsgaard Christensen, Allan Randrup Thomsen, Soren Buus</text>
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            <description>An account of the resource</description>
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                <text>Examining CD8+ and CD4+ T cell responses after primary Yellow Fever vaccination in a cohort of 210 volunteers, we have identified and tetramer-validated 92 CD8+ and 50 CD4+ T cell epitopes, many inducing strong and prevalent (i.e., immunodominant) T cell responses. Restricted by 40 and 14 HLA-class I and II allotypes, respectively, these responses have wide population coverage and might be of considerable academic, diagnostic and therapeutic interest. The broad coverage of epitopes and HLA overcame the otherwise confounding effects of HLA diversity and non-HLA background providing the first evidence of T cell immunodomination in humans. Also, double-staining of CD4+ T cells with tetramers representing the same HLA-binding core, albeit with different flanking regions, demonstrated an extensive diversification of the specificities of many CD4+ T cell responses. We suggest that this could reduce the risk of pathogen escape, and that multi-tetramer staining is required to reveal the true magnitude and diversity of CD4+ T cell responses. Our T cell epitope discovery approach uses a combination of (1) overlapping peptides representing the entire Yellow Fever virus proteome to search for peptides containing CD4+ and/or CD8+ T cell epitopes, (2) predictors of peptide-HLA binding to suggest epitopes and their restricting HLA allotypes, (3) generation of peptide-HLA tetramers to identify T cell epitopes, and (4) analysis of ex vivo T cell responses to validate the same. This approach is systematic, exhaustive, and can be done in any individual of any HLA haplotype. It is all-inclusive in the sense that it includes all protein antigens and peptide epitopes, and encompasses both CD4+ and CD8+ T cell epitopes. It is efficient and, importantly, reduces the false discovery rate. The unbiased nature of the T cell epitope discovery approach presented here should support the refinement of future peptide-HLA class I and II predictors and tetramer technologies, which eventually should cover all HLA class I and II isotypes. We believe that future investigations of emerging pathogens (e.g., SARS-CoV-2) should include population-wide T cell epitope discovery using blood samples from patients, convalescents and/or long-term survivors, who might all hold important information on T cell epitopes and responses.</text>
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                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="47003">
                <text>Immunogenicity, peptide-MHC tetramers, Yellow fever vaccination, CD4+ and CD8+ T cell epitope discovery, forward-reverse immunology, immunodominance and immunodomination</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <name>Identifier</name>
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              <elementText elementTextId="47004">
                <text>10.3389/fimmu.2020.01836</text>
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            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
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                <text>Epidemiology and Health</text>
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            <name>Publisher</name>
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                <text>Korean Society of Epidemiology</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Immunologic diseases. Allergy</text>
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        <src>https://www.socictopen.socict.org/files/original/7d41ae74177b2409732d4ca02a13d2d6.pdf</src>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>A Systems Approach to Assess Transport and Diffusion of Hazardous Airborne Particles in a Large Surgical Suite: Potential Impacts on Viral Airborne Transmission</text>
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              <elementText elementTextId="81657">
                <text>Marc Garbey, Guillaume Joerger, Shannon Furr</text>
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            <description>An account of the resource</description>
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                <text>Airborne transmission of viruses, such as the coronavirus 2 (SARS-CoV-2), in hospital systems are under debate: it has been shown that transmission of SARS-CoV-2 virus goes beyond droplet dynamics that is limited to 1 to 2 m, but it is unclear if the airborne viral load is significant enough to ensure transmission of the disease. Surgical smoke can act as a carrier for tissue particles, viruses, and bacteria. To quantify airborne transmission from a physical point of view, we consider surgical smoke produced by thermal destruction of tissue during the use of electrosurgical instruments as a marker of airborne particle diffusion-transportation. Surgical smoke plumes are also known to be dangerous for human health, especially to surgical staff who receive long-term exposure over the years. There are limited quantified metrics reported on long-term effects of surgical smoke on staff’s health. The purpose of this paper is to provide a mathematical framework and experimental protocol to assess the transport and diffusion of hazardous airborne particles in every large operating room suite. Measurements from a network of air quality sensors gathered during a clinical study provide validation for the main part of the model. Overall, the model estimates staff exposure to airborne contamination from surgical smoke and biological material. To address the clinical implication over a long period of time, the systems approach is built upon previous work on multi-scale modeling of surgical flow in a large operating room suite and takes into account human behavior factors.</text>
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                <text>2020</text>
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                <text>covid-19, Surgical smoke, particle transport, multiscale model, surgical suite, airborne virus</text>
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                <text>10.3390/ijerph17155404</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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                <text>Epidemiology and Health</text>
              </elementText>
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            <name>Publisher</name>
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                <text>Korean Society of Epidemiology</text>
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            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Medicine</text>
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            </elementTextContainer>
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