ABSTRACT
The world is now experiencing the catastrophe of global pandemic ‘COVID-19’, most serious public health crises in this century. Recently, another virus named “Cat Que Virus” (CQV) seems to be causing its terrible repercussions in the worlds’ largest populous country ‘China’, the origin of SARS-CoV during 2002-2003, and the current pandemic SARS-CoV-2 since December 2019. Recently, the presence of IgG antibody among two persons in the state of Karnataka for CQV was reported in India, the worlds’ second-largest populous country. This means the virus is in circulation in the sub-continent. The presence of the vector mosquitoes (Aedes species, Culex species) and the ambient climatic conditions suitable for vector breeding in the country needs to be taken into account while planning to implement holistic strategies appropriate for control and preventive measures. “One Health approach” is the topmost option covering humans, animals/vectors and the environment to curb the spread/transmission of infectious diseases in general. It is also necessary to study the transmission dynamics and pattern of this emerging virus, its life cycle, the natural reservoir of the virus, the intermediate host and the accidental host with respect South-East Asia, so that necessary remedial action can be planned well before an epidemic. At present, the outbreak of CQV is certainly a warning to the general population around the world. Considering the global imminent health threats posed by CQV, there is an urgent need for active surveillance, monitoring, effective vaccination, and a standard treatment modality of this disease. Given the epidemiological aspect of CQV, control and prevention measures are essential to stop the spread of the virus. At present, there is no information available on CQV; however, this current review article has covered the required data, which will be helpful to control the spread of the CQV.
Subject(s)
COVID-19 , Catastrophic Illness , Communicable DiseasesABSTRACT
The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better response and preparedness measures against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic.
Subject(s)
Artificial Intelligence , COVID-19/epidemiology , Delivery of Health Care , Humans , PandemicsABSTRACT
The technology-driven world of the 21st century is currently confronted with a major threat to humankind in the form of the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of April 22, 2020, COVID-19 has claimed 169, 006 human lives and had spread to over 200 countries with more than 2,471,136 confirmed cases. The perpetually increasing figures associated with COVID-19 are disrupting the social and economic systems globally. The losses are unmatched and significantly higher compared to those from previously encountered pathogenic infections. Previously, two CoVs (SARS-CoV and Middle East respiratory syndrome-CoV) affected the human population in 2002 and 2012 in China and Saudi Arabia, respectively. Based on genomic similarities, animal-origin CoVs, primarily those infecting bats, civet cats, and pangolins, were presumed to be the source of emerging human CoVs, including the SARS-CoV-2. The cohesive approach amongst virologists, bioinformaticians, big data analysts, epidemiologists, and public health researchers across the globe has delivered high-end viral diagnostics. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. The rapidly evolving and popular technology of artificial intelligence played a major role in confirming and countering the COVID-19 pandemic using digital technologies and mathematical algorithms. In this review, we discuss the noteworthy advancements in the mitigation of the COVID-19 pandemic, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology, animal reservoirs, laboratory animal models, disease transmission, diagnosis using artificial intelligence interventions, therapeutics and vaccines, and disease mitigation measures to combat disease dissemination.