Diagnosis for COVID-19

"COVID-2019,” a recently emerged novel coronavirus disease, is causing serious health issues to the public and becoming more and more fatal every next day. On December 31, 2019, low respiratory infection cases were detected in Wuhan, China, which is in China's Hubei province. The cases were reported to the WHO Office of China and they could not identify the agents for the cause. The first cases were classified to be "pneumonia of unknown etiology.” The investigation program was initiated by the Chinese Center for Disease Control and Prevention (CDC). The etiology of the disease was attributed to a novel virus of the coronavirus (CoV) family. Dr. Tedros Adhanom Ghebreyesus, WHO Director-General, called the disease caused by this CoV the "COVID-19,” which is an acronym for "coronavirus disease 2019.” It is found that "COVID-19” is caused by bête-coronavirus named "severe acute coronavirus-2” (SARS-CoV-2). It belongs to those virus families that appear as pneumonia in the human body. It affects the lower respiratory tract badly. This virus has been identified as another version of the family of severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) [1, 2]. SARS-CoV-2, SARS-CoV, and MERS-CoV possess similarity with them. They have differences in genotypic and phenotypic structure that guide their pathogenesis. So far, as per the findings, this virus originated in bats. It reached humans through contact with unknown animals. The transmission of this virus among humans is via direct contacts, inhalation of infected droplets, and contaminated hands and surfaces. Some of the symptoms of this disease are cough, sore cough, fever, fatigue, and dyspnea/breathlessness. The remedy of this disease is to diagnose the infection at the initial stage, supportive treatment to survive, self-quarantines, mass-quarantines, etc. This paper presents a systematic review of the origin of coronavirus, its types, transmissions, symptoms, and the current developments in diagnosing testing and vaccine trials. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

At the Crossroads of One Health: Lessons Learned from Foot and Mouth Disease in COVID-19 Pandemic

Foot-and-mouth disease (FMD) and Coronavirus Disease 2019 (COVID-19) are transboundary diseases caused by single-stranded positive-sense RNA viruses with similarities in genome replication and viral protein synthesis. In FMD, asymptomatic infection leads to carrier status and persistently infected animals that threaten the animals vaccinated with a trivalent inactivated whole virus vaccine. Similar information on COVID-19 is not yet available. As COVID-19 vaccination is introduced in January 2021 (since 16 January 2021 in India), its outcome can be assessed by the year-end;and while doing so, the experiences gained in the control of FMD in livestock worldwide can be applied, including monitoring of vaccination response, duration of immunity, level of herd immunity developed, and antigenic matching of the vaccine virus. Antigenic divergence of the virus is a major issue in FMD, and different geographical regions in the world use different virus strains in vaccine preparations to antigenically match circulating virus strains in respective regions for control of the disease. Non-synonymous mutations in the critical antigenic determinants of SARS-CoV-2 have been observed, and there is likely the existence/development of antigenic variants. Therefore, during the post-COVID-19 vaccination regime, it will be essential to monitor the suitability of the in-use vaccine strain region-wise from time to time, as there could be an eruption of isolated outbreaks in a country arising due to antigenic variation and variants. In the context of the present scenario of COVID-19 around the Globe and multiple ongoing efforts to develop suitable vaccine(s) to control the disease, it is a must to develop NSP-antibody (that differentiate infected from vaccinated) assays to differentiate infected from vaccinated individuals(DIVI;DIVA in veterinary epidemiology). The techniques used and experiences gained in ongoing FMD control programs in the endemic countries can be applied to COVID-19 control in a country;and finally, the Globe. After achieving the control of COVID-19, the aim would be to eradicate the virus, which will be tough even with vaccination, as the disease/infection may become endemic during the time to come. To achieve this, applying the principles of Progressive Control Pathway for Foot-and-Mouth Disease (PCP-FMD;FAO/OIE) to COVID-19 control will be beneficial in its control. The present review discusses the issue of control of COVID-19. © 2021 by the authors.

MCNN: A deep learning based rapid diagnosis method for COVID-19 from the X-ray images

Due to the rapidly spreading nature of coronavirus, a pandemic situation has emerged around the world. It is affecting society at large that includes the global economy and public health too. It was found in recent studies that the novel and unknown nature of this virus makes it more difficult to identify and treat the affected patient in the early stage. In this context, a time-consuming method named reverse transcription-polymerase chain reaction (RT-PCR) is being used to detect the positive cases of COVID-19, which requires blood samples of the suspects to diagnose the disease. This paper presents a new deep learning-based method to detect COVID-19 cases using chest X-ray images as the recent studies show that the radiology images have relevant features that can be used to predict the COVID-19. The proposed method is developed for binary classification to identify that a person is infected with COVID-19 or not. A total of 2400 X-ray images are taken for the experimental work. It includes 1000, COVID-19, and 1000, non-COVID-19 images, 200, COVID-19, and 200, non-COVID-19 testing images. The proposed method has been compared with the existing state-of-the-art methods on various statistical parameters which give better results with higher accuracy in diagnosing the COVID-19 cases. The proposed method has obtained 98.25% accuracy, 98.49% precision, 98% sensitivity, 98.50% specificity, and 98.25% F1 score. © 2020 Lavoisier. All rights reserved.