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                <text>In the light of the COVID-19 virus pandemic that has attacked the earth planet, all nations in the world are becoming suffered more and more from the increasing number of infected cases. The medical infrastructure in most countries aren’t fit to deal with such pandemic, hospitals in these countries are unable to accommodate a such number of the infected cases that have recently been recorded[1],[5]. This pandemic has put countries in a great predicament; they never expected to face a pandemic of this size [1], [5]. Palestine is one of these pandemic victims, COVID-19 virus has started spreading in Palestine on fifth March of 2020 [4]. Palestinian government and leadership have announced immediately by its Prime Minister   Dr Mohammad Shtayyeh the case of emergency in Palestine to prevent this dangerous pandemic from spreading, by closing all schools and universities, crowding prevention, limiting motion and asking people strongly for home-stay [1], [2], [4]. With this step, Palestine has been recorded as one of the most quick-response countries of facing the COVID-19 pandemic in the world [4]. Although the emergency case is still very active in Palestine, the Palestine government and people are still very worry and afraid from the coming future, this is for two main reasons, the first is the inability of Palestine medical infrastructure to process the large numbers of infected cases, the second is the social-cultural system in Palestine that has strong relationships and traditions that promotes social communication in Palestine which may help the COVID-19 virus for more spreading. So, this study aims to help Palestinian government to be ready as possible to face this pandemic in the coming days, by designing a computerized model to predict the expected numbers of the infected cases that may be recorded in the coming days.</text>
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                <text>Lizhen Wang,1 Yueting Duan,1 Wenming Zhang,2 Juan Liang,2 Jianxiang Xu,3 Yongqing Zhang,3 Changgang Wu,3 Yangling Xu,3 Hua Li2 1Department of Tuberculosis, Liaocheng Infectious Disease Hospital, Liaocheng, Shandong, People&amp;rsquo;s Republic of China; 2Intensive Care Unit, Liaocheng Infectious Disease Hospital, Liaocheng, Shandong, People&amp;rsquo;s Republic of China; 3Department of Respiration, Liaocheng Infectious Disease Hospital, Liaocheng, Shandong, People&amp;rsquo;s Republic of ChinaCorrespondence: Hua LiDepartment of Respiration, Liaocheng Infectious Disease Hospital, 45 Jianshe Eastern Road, Dongchang, Liaocheng, Shandong 252000, People&amp;rsquo;s Republic of ChinaEmail weiyichunguang@163.comIntroduction: Over 40,000 cases of coronavirus (CoV) disease 2019 (COVID-19) have been confirmed in China. The causative agent, 2019 novel CoV (2019-nCoV), has spread rapidly to more than 25 countries worldwide. Human-to-human transmission has accounted for most of the infections outside Wuhan. Most studies to date on COVID-19 have focused on disease etiology and the genomics of 2019-nCoV, with few reports on the epidemiologic and clinical characteristics of infected patients.Methods: We report early clinical features of 26 patients with confirmed COVID-19 who were admitted to Liaocheng Infectious Disease Hospital in Shandong Province.Results: The median age of the 26 patients with COVID-19 in this study was 42 years. The most common occupation was retail staff (16 patients, 61.54%), with 11 patients or their family members working at the same supermarket. Only 2 patients had visited Wuhan since December 2019; the other cases of 2019-nCoV infection arose from patient-to-patient transmission. Twelve patients had more than one sign or symptom; however, seven patients had no sign or symptom. The average time from symptom onset to admission was 4.5 days. CT revealed signs of bronchitis in 2 patients and unilateral and bilateral pneumonia in 9 and 15 patients, respectively. The patients received the following treatments: antiviral therapy (100%), Chinese medicine (76.92%), antibiotics (50%), gastric mucosal protection (19.23%), immunotherapy (7.69%), and glucocorticoids (3.85%). Most patients (25/26) required &amp;ge; 1 treatment.Discussion: In contrast to previous reports, most patients (24/26) had not been in close contact with individuals from Wuhan. Additionally, 11 patients or their family members worked at the same supermarket, suggesting active viral transmission in a location frequented by a large number of people. Close monitoring is essential for preventing the large-scale spread of the virus in such places.Keywords: coronavirus disease 2019, human-to-human transmission, epidemiologic characteristics, clinical characteristics</text>
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                <text>Latar belakang: Sejak diumumkan pertama kali pada Desember 2019, jumlah penderita COVID-19 terus meningkat. Seiring dengan perkembangan penyakit ini yang begitu pesat, berbagai masalah pun mulai bermunculan. Serial kasus ini ditulis untuk mengangkat pengalaman dalam penanganan pasien keganasan dalam keterbatasannya pada masa pandemi COVID-19. Kasus: Pertama, pasien peripheral T-cell lymphoma yang sudah kemoterapi CHOP 4 siklus di Singapura dan akan melanjutkan siklus selanjutnya bulan April 2020. Kedua, pasien dengan pleomorphic spindle cell sarcoma regio toraks posterior metastasis ke paru dan tulang sudah mendapatkan kemoterapi lini kedua dengan regimen Gemcitabine/Docetaxel di Singapura, dan akan melanjutkan kemoterapi selanjutnya akhir Maret 2020, akan tetapi pasien mengalami neutropenia dan menolak ke rumah sakit untuk injeksi karena takut. Ketiga, pasien dengan karsinoma payudara Her-2 type yang sedang menjalani terapi target Kadcyla di London. Pasien pertama dan ketiga tidak dapat melanjutkan terapi di luar negeri karena pandemi COVID-19. Simpulan: Pandemi COVID-19 secara langsung menyebabkan perubahan besar dalam layanan rumah sakit. Penundaan pengobatan pada pasien kanker yang dapat dilakukan atau melanjutkan pengobatan dengan peningkatan kewaspadaan akan transmisi COVID-19 merupakan opsi yang dapat dilakukan dan dipertimbangkan secara matang oleh klinisi.</text>
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                <text>JBN (Jurnal Bedah Nasional)</text>
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                <text>Siluh Nyoman Alit Nuryani, Luh Gede Lisnawati</text>
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                <text>Nurses during COVID-19 pandemic outbreak will be front line health care worker providing care for all patient including cancer patients. Cancer patients were vulnerable group that need to be prevented from getting COVID-19. This study will describe the roles of nurses to protect cancer patients during this outbreak. The role of nurses preventing transmission in outpatient including conducting medical distancing to reduce number of patient visit health care. This can be done through screening by phone. Chemotherapy unit, nurses can prevent transmission through physical distancing, providing education and surface cleaning more often than usual in between patient. Oncology ward, nurses need to educate patient family regarding no hospital policy visit. This will reduce number of exposure people to people. The use of PPE wisely due to shortage of resources in may hospital facilities by reducing number of team member entering patient’s room, selectively usage of PPE required for certain nursing procedures, and nurses can perform number of procedures at once whenever nurses enter patients’ room.  During this crisis, nurses also need to maintain their mental health by managing their stress and anxiety by balancing between work and rest during shifts, eat sufficient food and healthy, and avoid alcohol and tobacco. Stay connected with friends and family through digital media. Hence, nurses can stay healthy so they care for patients during this pandemic.</text>
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                <text>Universitas Udayana</text>
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                <text>We prepared the three-dimensional model of the SARS-CoV-2 (aka 2019-nCoV) 3C-like protease (3CLpro) using the crystal structure of the highly similar (96% identity) ortholog from the SARS-CoV. All residues involved in the catalysis, substrate binding and dimerisation are 100% conserved. Comparison of the polyprotein PP1AB sequences showed 86% identity. The 3C-like cleavage sites on the coronaviral polyproteins are highly conserved. Based on the near-identical substrate specificities and high sequence identities, we are of the opinion that some of the previous progress of specific inhibitors development for the SARS-CoV enzyme can be conferred on its SARS-CoV-2 counterpart.  With the 3CLpro molecular model, we performed virtual screening for purchasable drugs and proposed 16 candidates for consideration. Among these, the antivirals ledipasvir or velpatasvir are particularly attractive as therapeutics to combat the new coronavirus with minimal side effects, commonly fatigue and headache.  The drugs Epclusa (velpatasvir/sofosbuvir) and Harvoni (ledipasvir/sofosbuvir) could be very effective owing to their dual inhibitory actions on two viral enzymes.</text>
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                <text>DOI: 10.12688/f1000research.22457.1</text>
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                <text>Epidemiology of Coronavirus COVID-19: Forecasting the Future Incidence in Different Countries</text>
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                <text>Johannes Stübinger, Lucas Schneider</text>
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                <text>This paper forecasts the future spread of COVID-19 by exploiting the identified lead-lag effects between different countries. Specifically, we first determine the past relation among nations with the aid of dynamic time warping. This procedure allows an elastic adjustment of the time axis to find similar but phase-shifted sequences. Afterwards, the established framework utilizes information about the leading country to predict the Coronavirus spread of the following nation. The presented methodology is applied to confirmed Coronavirus cases from 1 January 2020 to 28 March 2020. Our results show that China leads all other countries in the range of 29 days for South Korea and 44 days for the United States. Finally, we predict a future collapse of the healthcare systems of the United Kingdom and Switzerland in case of our explosion scenario.</text>
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                <text>coronavirus, COVID-19, Epidemiology, incidence, dynamic time warping, Lead-lag effects</text>
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                <text>DOI: 10.3390/healthcare8020099</text>
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                <text>MDPI AG</text>
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                <text>Medicine</text>
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                <text>EN</text>
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