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COVID-2019 has become a global pandemic, and a variety of SARS-CoV-2 variants have emerged with the continuous evolution and variation. SARS-CoV-2 Delta VOC (B.1.617.2) has the characteristics of strong transmission, short incubation period of infection, high pathogenicity and rapid disease progression, which has gradually become the main epidemic strain in India and even in the world, leading to countries and regions of the epidemic rebound. In this paper, the current epidemic characteristics and core control measures of SARS-CoV-2 Delta VOC was reviewed.
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Objective: To explore epidemic dynamics of coronavirus disease 2019 (COVID-19) in Xinyang City so as to provide scientific basis for optimizing the prevention and control strategies and evaluating the effects of intervention.
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Objective: To investigate a family cluster of coronavirus disease 2019(COVID-19)in Zibo, so as to analyze the characteristics of the epidemic.
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Objective: To analyze the incidence and epidemic characteristics of local cases infected with SARS-CoV-2 in Yangpu District of Shanghai, China, and provide scientific evidence for the prevention and control of coronavirus disease-19 (COVID-19).
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Aim: This study is aimed to identify the awareness and behavioral perspective on COVID-19 between urban and rural people of Bangladesh during the period of outbreak.
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Objective: Healthcare professionals taking care of COVID-19 patients are considered to be at high risk for acquiring infection, and the protection of healthcare professionals is one of the top priorities. Inadequate knowledge of the disease by healthcare professionals and their inability to access or use personal protective equipment (PPE) required for protection may cause rapidly spreading of infection. In this study, we aimed to evaluate the knowledge levels of healthcare professionals regarding COVID-19 and PPE use.
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Since December 2019, COVID-19 started outbreaks in Wuhan city, and the infection has rapidly spread in worldwide. The coronavirus has strong infectivity and long incubation period. The clinical symptoms of novel coronavirus pneumonia are not typical, the diagnosis mainly depends on 2019-nCoV nucleic acid detection, and the diagnosis and treatment are still groping. In order to help early diagnosis, isolation, treatment and better prevention and control of epidemic transmission, this paper analyzes and summarizes the process of diagnosis and treatment of a case of severe novel coronavirus pneumonia and the related literatures.
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COVID-19, a pandemic caused by a betacoronavirus known as SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) has recorded 18 354 342 number of cases and 696 147 deaths globally as of August 5, 2020. It was first recorded in Wuhan, China in 2019. The virus bears close resemblance to SARS-CoV-1 and MERS-CoV that have emerged and caused outbreaks of deadly human diseases. The main component of the virus responsible for the host range specific tropism and pathogenicity is the S-glycoprotein. The primary route of transmission of infection is through human to human via close contact, usually through spraying of droplets from sneeze or cough of an infected person. The incubation period for COVID-19 following viral infection is between 2 to 14 days. The target cells of SARS-CoV-2 are those cells that highly expressed ACE2 (angiotensin-converting enzyme 2). Viral receptor binds to the ACE2, to allow the virus entry into the cell via endosomal pathway. The host innate immune system detects the viral infection by using pattern recognition receptors which result in activation of downstream signalling cascade. Understanding the virulence factors contributing to pathology, host immune responses and strategies employed by the virus in bypassing host immune response is paramount in developing therapeutic options that can help to tackle the COVID-19 pandemics.
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Introduction: Influenza and COVID-19 are high transmission pathologies which have a different median incubation period. Although the symptoms are similar, people are more likely to be affected by severe and/or critical COVID-19 infection than severe and/or critical influenza infection. It is well proven that school closure and personal protection measures (mask-wearing and social distancing) are effective in reducing the spread of infection. This study aims to highlight the impact of 2020-21 seasonal influenza on the Italian population during the COVID-19 pandemic and to identify possible reasons for that. Materials and methods: To describe the impact of influenza on the population, data from the Integrated Influence Surveillance InfluNet and vaccination coverage in Italy in the 2020-21 season were used. Influenza Like Illness (ILI) incidence rates per thousand patients and influenza vaccination coverage (%) were calculated on the total population and by age group.
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The coronavirus, which appeared in Wuhan city of China and named COVID-19, spread rapidly and caused the death of many people. Early diagnosis is very important to prevent or slow the spread. The first preferred method by clinicians is real-time reverse transcription-polymerase chain reaction (RT-PCR). However, expected accuracy values cannot be obtained in the diagnosis of patients in the incubation period. Therefore, common lung devastation in COVID-19 patients were considered and radiological lung images were used to diagnose. In this study, automatic COVID-19 diagnosis was made from posteroanterior (PA) chest X-Ray images by deep learning method. In the study, using two different deep learning methods, classification was made with different dataset combinations consisting of healthy, COVID, bacterial pneumonia and viral pneumonia X-ray images. The results show that the proposed deep learning-based system can be used in the clinical setting as a supplement to RT-PCR test for early diagnos.