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In-line treatments and clinical initiatives to fight against COVID-19 outbreak.

ABSTRACT: In December 2019, when the whole world is waiting for Christmas and New Year, the physicians of Wuhan, China, are astounded by clusters of patients suffering from pneumonia from unknown causes. The pathogen isolated from the respiratory epithelium of the patients is similar to previously known coronaviruses with some distinct features. The disease was initially called nCoV-2019 or SARS-nCoV-2 and later termed as COVID-19 by WHO. The infection is rapidly propagating from the day of emergence, spread throughout the globe and now became a pandemic which challenged the competencies of developed nations in terms of health care management. As per WHO report, 216 countries are affected with SARS-CoV-19 by August 5, 2020 with 18, 142, 718 confirmed cases and 691,013 deaths reports. Such huge mortality and morbidity rates are truly threatening and calls for some aggressive and effective measures to slow down the disease transmission. The scientists are constantly engaged in finding a potential solution to diagnose and treat the pandemic. Various FDA approved drugs with the previous history of antiviral potency are repurposed for COVID-19 treatment. Different drugs and vaccines are under clinical trials and some rapid and effective diagnostic tools are also under development. In this review, we have highlighted the current epidemiology through infographics, disease transmission and progression, clinical features and diagnosis and possible therapeutic approaches for COVID-19. The article mainly focused on the development and possible application of various FDA approved drugs, including chloroquine, remdesivir, favipiravir, nefamostate mesylate, penciclovir, nitazoxanide, ribavirin etc., vaccines under development and various registered clinical trials exploring different therapeutic measures for the treatment of COVID-19. This information will definitely help the researchers to understand the in-line scientific progress by various clinical agencies and regulatory bodies against COVID-19.

SUBMITTER: Agrawal M

PROVIDER: S-EPMC7567661 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: In December 2019, the novel Coronavirus disease (COVID-19) broke out in Wuhan, China leading to major national and international disruptions in healthcare, business, education, transportation, and nearly every aspect of our daily lives. Artificial Intelligence (AI) has been leveraged amid the COVID-19 pandemic, however, little is known about its use for supporting public health efforts.Objective: The scoping review aimed to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature. Thus, it is first review that describes and summarizes features of the identified AI techniques and datasets used for their development and validation.Methods: A scoping review was conducted following the guidelines of PRISMA Extension for Scoping Reviews (PRISMA-ScR). We searched the most commonly used electronic databases (e.g., MEDLINE, EMBASE, PsycInfo) between April 10 and 12, 2020. These terms were selected based on the target intervention (i.e., AI) and the target disease (i.e., COVID-19). Two reviewers independently conducted study selection and data extraction. A narrative approach was used to synthesize the extracted data.Results: We considered 82 studies out of the 435 retrieved studies. The most common use of AI was diagnosing COVID-19 cases based on various indicators. AI was also employed in drug and vaccine discovery or repurposing, and assessing their safety. Further, the included studies used AI for forecasting the epidemic development of COVID-19 and predicting its potential hosts/reservoirs. Researchers utilized AI for patient outcome-related tasks such as assessing the severity of COVID-19, predicting mortality risk, its associated factors, and length of hospital stay. AI was used for Infodemiology to raise awareness to use water, sanitation, and hygiene. The most prominent AI techniques used were Convolutional Neural Network (CNN) followed by Support Vector Machine (SVM).Conclusions: The included studies showed that AI has the potential to fight against COVID-19. However, many of the proposed methods are not yet clinically accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for studies on AI.

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In-line treatments and clinical initiatives to fight against COVID-19 outbreak.

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