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International Journal of Experimental Research and Review ; 30:359-365, 2023.
Article in English | Scopus | ID: covidwho-2326845


Coronavirus disease 2019 is a new infectious respiratory disease as named by the World Health Organization. This virus is affecting different individuals in diverse manners. Consequently, studies are going on to identify the factors and parameters disturbing predominantly. According to various studies, the immunity of a person determines the effect of the virus on that individual's health. Thus, immunity is determined by multiple factors like climate, population, geographical location, sanitation facilities. In existing studies, the effect of various climatic factors, such as temperature, relative humidity of diverse countries and areas, on COVID-19 spread is taken. To extend these studies, this paper is an effort to consider almost all the topological parameters of significant countries and different states of India for analysing their effects on the recovery rate due to COVID-19. Finally, these parameters are ranked/sorted as per their impact on recovery rates. © 2023 The authors.

Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis ; : 89-111, 2021.
Article in English | Scopus | ID: covidwho-2326736


"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.

Revue d'Intelligence Artificielle ; 34(6):673-682, 2020.
Article in English | Scopus | ID: covidwho-1084320


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.