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                <text>Restricting rural-urban connect to combat infectious disease epidemic as India fights COVID-19</text>
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                <text>Anjana Singh, Ravi Kant, Raman Kumar, Ajeet Singh Bhadoria, Archisman Mohapatra, Surabhi Mishra</text>
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                <text>With declaration of 2019 novel coronavirus disease (COVID-19) as a pandemic on 11 March 2020 by World Health Organization, India came to alert for its being at next potential risk. It reached alert Level 2, i.e. local transmission for virus spread in early March 2020 and soon thereafter alert Level 3, i.e. community transmission. With on-going rise in COVID-19 cases in country, Government of India (GoI) has been taking multiple intense measures in coordination with the state governments, such as urban lockdown, active airport screening, quarantining, aggressive calls for 'work from home', public awareness, and active case detection with contact tracing in most places. Feedback from other countries exhibits COVID-19 transmission levels to have shown within country variations. With two-third of Indian population living in rural areas, present editorial hypothesizes that if India enters Level 3, rural hinterland would also be at risk importation (at least Level 1). Hence, we have to call for stringent containment on rural-urban and inter-state fringes. This along with other on-going measures can result in flattening curve and also in staggering 'lockdowns', and thus, helping sustain national economy.</text>
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                <text>DOI: 10.4103/jfmpc.jfmpc_451_20</text>
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                <text>Nasopharyngeal wash in preventing and treating upper respiratory tract infections: Could it prevent COVID-19?</text>
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                <text>Virendra Singh, Sheetu Singh, Neeraj Sharma, Daya Krishan Mangal, Udaiveer Singh, Tejraj Singh</text>
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                <text>Rapid transmission of the severe acute respiratory syndrome coronavirus 2 has led to the novel coronavirus disease 2019 (COVID-19) pandemic. The current emphasis is on preventive strategies such as social distancing, face mask, and hand washing. The technique of nasopharyngeal wash to prevent the virus from inhabiting and replicating in the nasal and pharyngeal mucosa has been suggested to be useful in reducing symptoms, transmission, and viral shedding in cases of viral acute respiratory tract infections. In rapid systematic review, we found studies showing some improvement in prevention and treatment of upper respiratory tract infections. We postulate that hypertonic saline gargles and nasal wash may be useful in prevention and for care of patients with COVID-19. The present evidence emphasizes the need of randomized controlled trials to evaluate the role and mechanism of nasopharyngeal wash in COVID-19.</text>
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                <text>coronavirus, nasal irrigation, COVID-19, jal-neti, nasal wash, oral gargles</text>
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                <text>DOI: 10.4103/lungindia.lungindia_241_20</text>
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                <text>Lung India</text>
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                <text>Diseases of the respiratory system</text>
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                <text>Urban forests at the time of COVID-19 protect us from fine dust</text>
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                <text>Sanesi G, Marchetti M, Salbitano F, Fares S, Vacchiano G</text>
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                <text>In these days, the role that fine particles in urban areas could play in facilitating the pandemic spread of the COVID-19 virus is becoming increasingly important. It is also well known that exposure to air pollution and in particular to fine dust favors diseases involving the respiratory system. In this context of strong concern, we argue that urban forests can contribute to reduce the concentrations of particulates or in any increase their dispersion. Not all tree species have the same performance in removing particulates. In this short article, recent works are commented that classify urban forest species according to their ability to reduce particulate matter ambient concentrations, and we conclude highlighting the significant role that urban forests could play in improving air quality and human wellbeing in the future.</text>
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                <text>DOI: 10.3832/efor3494-017</text>
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                <text>Italian Society of Silviculture and Forest Ecology (SISEF)</text>
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                <text>THE LATEST PANDEMIC: COVİD-19 &amp; EYE</text>
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                <text>Erdal Yüzbaşıoğlu</text>
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                <text>Coronaviruses (CoV) are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). A novel coronavirus (nCoV) is a new strain that has not been previously identified in humans.  Coronaviruses are zoonotic, meaning they are transmitted between animals and people.  Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from dromedary camels to humans. Several known coronaviruses are circulating in animals that have not yet infected humans. Common signs of infection include respiratory symptoms, fever, cough, shortness of breath and breathing difficulties. In more severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure and even death(1).</text>
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                <text>Ophthalmology</text>
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                <text>Coronavirus host divergence and novel coronavirus (SARS-CoV-2) outbreak</text>
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                <text>Kadir Yesilbag, Gizem  AYTOĞU</text>
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                <text>SARS-CoV-2 (novel coronavirus, nCoV-2019) outbreak started in November 2019 in China has created a public health concern all around the world. Since infected patients transported out of China, the outbreak status was quickly changed into pandemic. Comparison of available genome sequences of the virus strains enlightened most questions as the cell receptors (ACE2) responsible for the virus tropism which determines possible organs and tissues to be affected by the virus as well as possible involvement of the age groups and host diversity. SARS-Cov-2, new member of Coronaviridae shares some clinical and epidemiological aspects similar to previous high pathogenic human coronavirus, SARS-CoV, existed in 2002. The most outstanding property of SARS-CoV-2 is high transmission rate (reproduction number, R0=˷3.58) between suspected and susceptible people. While bats are pointed as the original host and pangolins as an intermediate host, possibility of other species contribution is still unknown. According to recent data, reptiles i.e. snakes seem to be out of the group for possible intermediate hosts. Also there is no data supporting involvement of domestic animals even pets or food producing in the infection spectrum. This review summarizes the key findings of ongoing pandemia since the day disease existed. Molecular divergences now show that disease agent evolved into two types (S and L). Mutations and natural selections besides recombination will still continue to be the common feature of coronaviruses. Though implementation of common global measures and treatments other than rapid sharing the information will contribute prevention efforts and reducing the number of losses.</text>
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                <text>2020</text>
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                <text>zoonosis, coronavirus, animal origin, COVID-19, COVID, sars-covs</text>
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                <text>DOI: </text>
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            <name>Source</name>
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              <elementText elementTextId="25853">
                <text>Clinical and Experimental Ocular Trauma and Infection</text>
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              <elementText elementTextId="25854">
                <text>Clinical and Experimental Ocular Trauma and Infection</text>
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                <text>Ophthalmology</text>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
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                <text>Detection of coronavirus Disease (COVID-19) based on Deep Features and Support Vector Machine</text>
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                <text>Prabira Kumar Sethy, Santi Kumari Behera, Pradyumna Kumar Ratha, Preesat Biswas</text>
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                <text>The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken. In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images. For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation. The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose. The SVM classifies the corona affected X-ray images from others. The methodology consists of three categories of Xray images, i.e., COVID-19, pneumonia and normal. The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people. SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models. The SVM produced the best results using the deep feature of ResNet50. The classification model, i.e. ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95.33%,95.33%,2.33% and 95.34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS). Again, the highest accuracy achieved by ResNet50 plus SVM is 98.66%. The result is based on the Xray images available in the repository of GitHub and Kaggle. As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach. Also, a comparison analysis of other traditional classification method is carried out. The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM. In traditional image classification method, LBP plus SVM achieved 93.4% of accuracy.</text>
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                <text>2020</text>
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                <text>diagnosis, SVM, coronavirus, Deep features, COVID-19</text>
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                <text>DOI: 10.33889/IJMEMS.2020.5.4.052</text>
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              <elementText elementTextId="25862">
                <text>International Journal of Mathematical, Engineering and Management Sciences</text>
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              <elementText elementTextId="25863">
                <text>International Journal of Mathematical, Engineering and Management Sciences</text>
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                <text>Technology, Mathematics</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>COVID-19 pandemic in India: A clarion call for better preparedness</text>
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              <elementText elementTextId="25866">
                <text>Parvaiz A Koul, Raja Dhar</text>
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                <text>DOI: 10.4103/lungindia.lungindia_318_20</text>
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                <text>Lung India</text>
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              <elementText elementTextId="25870">
                <text>Wolters Kluwer Medknow Publications</text>
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                <text>Diseases of the respiratory system</text>
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                  <text>Dominio científico: Coronavirus</text>
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      <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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                <text>Dermatosurgery practice and implications of COVID-19 pandemic: Recommendations by IADVL SIG Dermatosurgery (IADVL Academy)</text>
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                <text>Sanjeev Gupta, Chander Grover, Karalikkattil T Ashique, Syed Mubashir, C Madura, Ankur Talwar, Anup K Lahiry, Sidhartha Das, Nilesh Goyal, Anirudh D Gulanikar</text>
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                <text>DOI: 10.4103/idoj.IDOJ_237_20</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="25876">
                <text>Indian Dermatology Online Journal</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="25877">
                <text>Wolters Kluwer Medknow Publications</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="25878">
                <text>Dermatology</text>
              </elementText>
            </elementTextContainer>
          </element>
        </elementContainer>
      </elementSet>
    </elementSetContainer>
  </item>
</itemContainer>
