Epidemiological Challenges in Pandemic Coronavirus Disease (COVID-19): Role of Artificial Intelligence

Abstract

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV- 2). The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as, deep learning, in (i) rapid disease detection from x-ray/computerized tomography (CT)/ high-resolution computed tomography (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) identification of the epicenter in each country/state and forecasting the disease from social networking data, (iv) prediction of drug-protein interactions for repurposing the drugs, and (v) socio-economic impact and prediction of future relapses, has attracted much attention. In the present manuscript, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real time polymerase chain reaction (qRT-PCR) and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, possibility of future relapses and socio-economic impact are also discussed. We inspect how the virus transmits depending on different factors, such as, population density and mobility among others. We depict how AI-based mobile app for contact tracing and surveys can prevent the transmission. A modified deep learning technique can assess affinity of the most probable drugs to treat COVID-19. Here a few effective antiviral drugs, such as, Geneticin, Avermectin B1, and Ancriviroc among others, have been reported with their appropriate validation from previous investigations.

SARS-CoV-2: Has artificial intelligence stood the test of time

“…AI is not yet playing a significant role in the fight against COVID-19. Dasgupta et al [55] 2020 et al [57] 2020 Global Global Results of this cohort study showed that the spatiotemporal spread of reported COVID-19 cases could be predicted at a global level by analyzing openly available geolocated Twitter social media data. COVID Near You [58] 2020 US, Canada, Mexico All three countries.…”

Battling COVID-19 using machine learning: A review

“…Shi et al, used machine learning techniques for data acquisition, diagnosis and prognosis of infected patients. Biological data mining was used to perform COVID-19 detection in (Dasgupta et al, 2020). Another paper (Tayarani N, 2021), discussed the uses of AI in battling COVID-19.…”