ABSTRACT
The ongoing pandemic of the novel coronavirus SARS-CoV-2 (COVID-19) has created a major challenge for the public health worldwide. The reported cases indicate that the outbreak is more widespread than initially assumed. Around 18 million people have been infected with 689,000 reported deaths (August 2020;the number is increasing daily);with a high mutation rate, this virus poses an even more serious threat worldwide. The actual source of COVID-19 is still un-clear;even if the initial reports link it to the Chinese seafood wet market in Wuhan, other animals such as birds, snakes, and many small mammals including bats are also linked with this novel coro-navirus. The structure of the COVID-19 shows distinctive proteins among which spike proteins have a pivotal role in host cell attachment and virus-cell membrane fusion in order to facilitate virus infection. Currently, no specific antiviral treatment or vaccine is available. Various drug can-didates, including SARS-CoV and MERS-CoV protease inhibitors, neuraminidase inhibitors, RNA synthesis inhibitors, ACE2 inhibitors and lungs supportive therapy, are under trials. Cell-based therapy also appeared with remarkable treatment possibilities. In this article, we endeavored to succinctly cover the current and available treatment options, including pharmaceuticals, cell-based therapy, and traditional medicine. We also focused on the extent of damages by this novel coron-avirus in India, Pakistan, and Bangladesh;the strategies adopted and the research activities initiat-ed so far by these densely populated countries (neighboring China) are explained in this review.Copyright © 2021 Bentham Science Publishers.
ABSTRACT
In this study, we leverage the fusion of edge computing, artificial intelligence (AI) methods, and facilities provided by B5G to build a heterogeneous set of AI techniques for COVID-19 outbreak prediction. Advancement in the areas of AI, edge computing, the Internet of Things (IoT), and fast communication networks provided by beyond 5G (B5G) networks has opened doors for new possibilities by fusing these technologies and techniques. In a pandemic outbreak, such as COVID-19, the need for rapid analysis, decision making, and prediction of future trends becomes paramount. On a global map, the distributed processing and analysis of data at the source is now possible and much more efficient. With the features provided by B5G, such as low latency, larger area coverage, higher data rate, and realtime communication, building new intelligent and efficient frameworks is becoming easier. In this study, our aim is to achieve higher accuracy in prediction by fusing multiple AI methods and leveraging the B5G communication architecture. We propose a distributed architecture for training AI methods on edge devices, with the results of edge-trained models then propagated to a central cloud AI method, which then combines all the received edge-trained models into a global and final prediction model. The experimental results of five countries (United States, India, Italy, Bangladesh, and Saudi Arabia) show that the proposed distributed AI on edges can predict COVID-19 outbreak better than that of each individual AI method in terms of correlation coefficient scores.