scholarly journals Analysis and Prediction for the Spreading of Covid-19 Pandemic in India Using Mathematical Modeling

2020 ◽  
Author(s):  
Nanda Poddar ◽  
Subham Dhar ◽  
Kajal Kumar Mondal ◽  
Gourab Saha
Keyword(s):  
Mathematical Modeling ◽  
Applied Mathematics ◽  
Medical Science ◽  
Spreading Rate ◽  
Living Room ◽  
Daily Lives ◽  
Infected People ◽  
Effective Strategies ◽  
The World ◽  
Novel Coronavirus

In the present time, the biggest problem of the world is the outbreak of novel coronavirus. Novel coronavirus (COVID-19), this one name has become a part of our daily lives over the past few months. Beyond the boundaries of medical science, coronavirus is now the main subject of research in all fields like Applied Mathematics, Economy, Philosophy, Sociology, Politics upto living room. The epidemic has brought unimaginable changes in our traditional habits and daily routines. Thousands of people in our country are fighting with the rest of the world to survive in various new situations. There are different kinds of coronavirus appeared in different times. In this time, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for the coronavirus disease of 2019 (COVID-19). This virus was first identified towards the end of 2019 in the city of Wuhan in the province of Hubei in China. Within very short duration of time and very fast, it has spread throughout a large part of the world. In this study, the main aim is to investigate the spreading rate, death rate, recovery rate due to corona virus infection and to study the future of the coronavirus in India by using mathematical modeling based on the previous data. Mathematical models, in this situation, are the important tools in recruiting effective strategies to fight this epidemic. India is at high risk of spreading the disease and is facing many losses in socio-economic aspects. With current infection rates and existing levels of personal alertness, the number of infected people in India will increase at least in the next three months. Proper social awareness, maintain of social distance, large rate of testing and separation may break the chain of the Coronavirus-2.

Covid-19 Detection using Deep Convolutional Neural Networks from X-Ray Images

2021 ◽  
Vol 4 (2) ◽  
pp. 139-143
Author(s):  
Abdullah Ajmal ◽  
Sundas Ibrar ◽  
Wakeel Ahmad ◽  
Syed Muhammad Adnan Shah
Keyword(s):  
Deep Learning ◽  
Global Economy ◽  
Data Augmentation ◽  
Diagnostic Techniques ◽  
Deep Convolutional Neural Networks ◽  
Data Set ◽  
Daily Lives ◽  
X Ray ◽  
The World ◽  
Novel Coronavirus

Abstract— The Novel Coronavirus generally, knows as COVID-19 which first appeared in Wuhan city of China in December 2019, spread quickly around the world and became a pandemic. It has caused an overwhelming effect on daily lives, Public health, and the global economy. Many people have been affected and have died. It is critical to control and prevent the spread of COVID-19 disease by applying quick alternative diagnostic techniques. COVID-19 cases are rising day by day around the world, the on-time diagnosis of COVID-19 patients is an increasingly long and difficult process. COVID-19 patient test kits are costly and not available for every individual in poor countries. For this purpose, screening patients with the established techniques like Chest X-ray images seems to be an effective method. This study used a deep learning data augmentation on a publicly available data set and train advanced CNN models on it. The proposed model was tested using a state-of-the-art evaluation measures and obtained better results. Our model, the COVID-19 images is available at (https://github.com/ieee8023/covid-chestxray-dataset) and for Non-COVID-19 images is available at (https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia). The maximum accuracy achieved in the validation was 96.67%. Our model of COVID-19 detection achieved an average F measure of 98%, and an Area Under Curve (AUC) of 99%. The results demonstrate that deep learning proved to be an effective and easily deployable approach for COVID-19 detection.

scholarly journals KL-MOB: automated COVID-19 recognition using a novel approach based on image enhancement and a modified MobileNet CNN

2021 ◽  
Vol 7 ◽  
pp. e694
Author(s):  
Mundher Mohammed Taresh ◽  
Ningbo Zhu ◽  
Talal Ahmed Ali Ali ◽  
Mohammed Alghaili ◽  
Asaad Shakir Hameed ◽  
...  
Keyword(s):  
Neural Network ◽  
Loss Function ◽  
X Ray ◽  
Infected People ◽  
Kl Divergence ◽  
Novel Approach ◽  
Starting Point ◽  
The World ◽  
Novel Coronavirus ◽  
Sensitivity Specificity

The emergence of the novel coronavirus pneumonia (COVID-19) pandemic at the end of 2019 led to worldwide chaos. However, the world breathed a sigh of relief when a few countries announced the development of a vaccine and gradually began to distribute it. Nevertheless, the emergence of another wave of this pandemic returned us to the starting point. At present, early detection of infected people is the paramount concern of both specialists and health researchers. This paper proposes a method to detect infected patients through chest x-ray images by using the large dataset available online for COVID-19 (COVIDx), which consists of 2128 X-ray images of COVID-19 cases, 8,066 normal cases, and 5,575 cases of pneumonia. A hybrid algorithm is applied to improve image quality before undertaking neural network training. This algorithm combines two different noise-reduction filters in the image, followed by a contrast enhancement algorithm. To detect COVID-19, we propose a novel convolution neural network (CNN) architecture called KL-MOB (COVID-19 detection network based on the MobileNet structure). The performance of KL-MOB is boosted by adding the Kullback–Leibler (KL) divergence loss function when trained from scratch. The KL divergence loss function is adopted for content-based image retrieval and fine-grained classification to improve the quality of image representation. The results are impressive: the overall benchmark accuracy, sensitivity, specificity, and precision are 98.7%, 98.32%, 98.82% and 98.37%, respectively. These promising results should help other researchers develop innovative methods to aid specialists. The tremendous potential of the method proposed herein can also be used to detect COVID-19 quickly and safely in patients throughout the world.

scholarly journals 2D Similarity Map of Multiple Coronavirus Gene Sequences

2020 ◽  
Author(s):  
Huaxian Zheng ◽  
Jeffrey Zheng
Keyword(s):  
Rna Virus ◽  
Polar Coordinates ◽  
Probability Measures ◽  
Social Environments ◽  
Infected People ◽  
Virus Rna ◽  
A Genome ◽  
Short Period ◽  
The World ◽  
Novel Coronavirus

Abstract The outbreak of a novel coronavirus (SARS-CoV-2) in many countries in the world from late 2019 to 2020 resulted in millions of infected people, and caused serious damage to the social environments with significant changes in human power and material resources in the world. The novel coronavirus is an RNA virus. RNA mutation is common in nature. This makes it extremely difficult to develop a virus vaccine in a short period. The evolution of the virus has been in a mutation state, in which a certain sequence changes associated with time and environments in similar distributions. A larger number of genomes were collected in various open source databases for scientists in further explorations. In this paper, a 2D similarity comparison scheme on the A2 module of the MAS is proposed for extracting internal information among a genome undertaken M segment partitions to provide visual results based on probability measures and quantitative statistics. First, a genome is segmented into corresponding numerical transformations, and then four numbers of meta symbols in each segment are counted.Corresponding probability measures are calculated. Second, the probability is transformed into polar coordinates, and the polar coordinates are mapped into a MxM matrix. Then, a 1D genome can be processed into 2D measures with similarity properties in sequence. Through this correlation matrix, relevant similarity results are analyzed.

scholarly journals Can plastic waste management be a novel solution in combating the novel Coronavirus (COVID-19)? A short research note

2020 ◽  
pp. 0734242X2097844
Author(s):  
Sultan Majed Al-Salem ◽  
Mohammed Sherif El-Eskandarani ◽  
Achilleas Constantinou
Keyword(s):  
Waste Management ◽  
Research And Development ◽  
Short Communication ◽  
Copper Alloys ◽  
Environmental Benefits ◽  
Added Value ◽  
The Novel ◽  
Daily Lives ◽  
The World ◽  
Novel Coronavirus

The year 2020 has been noted to be one of major calamity the world over, in which the majority of efforts in research and development have been dedicated towards combating the threat of the novel Coronavirus (COVID-19). Ever since the announcement of COVID-19 as a pandemic, such efforts were dedicated towards the research of its spread and vaccination. Yet still, the world might reach a resolution via an environmental solution that various entities have overlooked, with a plethora of environmental benefits vis-à-vis waste management. In this short communication, the possibility of using plastic solid waste as a substrate to employ copper, and copper alloys and their nanocomposite nanopowders to be used as permanent surface protective coats, is presented. The fact that we present such materials to be of waste origin, is an added value advantage to their beneficial advantage of developing various commodities and products that could be used in our daily lives. Furthermore, the fact that such recyclable materials are susceptible to antiviral properties and chemicals, is an added value that we should not neglect.

scholarly journals 2D Similarity Map of Multiple Coronavirus Gene Sequences

2021 ◽  
Author(s):  
Huaxian Zheng ◽  
Jeffrey Zheng
Keyword(s):  
Rna Virus ◽  
Polar Coordinates ◽  
Probability Measures ◽  
Social Environments ◽  
Infected People ◽  
Virus Rna ◽  
A Genome ◽  
Short Period ◽  
The World ◽  
Novel Coronavirus

Abstract The outbreak of a novel coronavirus (SARS-CoV-2) in many countries in the world from late 2019 to 2020 resulted in millions of infected people, and caused serious damage to the social environments with significant changes in human power and material resources in the world. The novel coronavirus is an RNA virus. RNA mutation is common in nature. This makes it extremely difficult to develop a virus vaccine in a short period. The evolution of the virus has been in a mutation state, in which a certain sequence changes associated with time and environments in similar distributions. A larger number of genomes were collected in various open source databases for scientists in further explorations. In this paper, a 2D similarity comparison scheme on the A2 module of the MAS is proposed for extracting internal information among a genome undertaken M segment partitions to provide visual results based on probability measures and quantitative statistics. First, a genome is segmented into corresponding numerical transformations, and then four numbers of meta symbols in each segment are counted. Corresponding probability measures are calculated. Second, the probability is transformed into polar coordinates, and the polar coordinates are mapped into a M × M matrix. Then, a 1D genome can be processed into 2D measures with similarity properties in sequence. Through this correlation matrix, relevant similarity results are analyzed.

scholarly journals Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

2020 ◽  
Author(s):  
Quoc-Viet Pham ◽  
Dinh C. Nguyen ◽  
Thien Huynh-The ◽  
Won-Joo Hwang ◽  
Pubudu N. Pathirana
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
State Of The Art ◽  
The State ◽  
Daily Lives ◽  
Recent Advances ◽  
The Arts ◽  
The World ◽  
Novel Coronavirus

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 215 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 14 April 2020, a cumulative total of 1,853,265 (118,854) infected (dead) COVID-19 cases were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify their applications in fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.

scholarly journals COVID-19 Pandemic in Nigeria: A review

2020 ◽  
Vol 3 (1) ◽  
pp. 11-26
Author(s):  
Charles Elikwu ◽  
Oladapo Walker
Keyword(s):  
International Committee ◽  
Dominant Mode ◽  
Main Body ◽  
African Continent ◽  
Rapid Rise ◽  
Wuhan City ◽  
Infected People ◽  
Health Measures ◽  
The World ◽  
Novel Coronavirus

Background: An ongoing outbreak of pneumonia associated with a novel coronavirus was reported in Wuhan city, China. This new virus was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the Coronavirus Study Group (CSG) of the International Committee on Taxonomy of Viruses. That disease, caused by the SARS-CoV-2, has been named coronavirus disease 2019 (COVID-19) by the WHO. The outbreak has since spread across the globe, including countries in Africa. Main body: The dominant mode of transmission is from the respiratory tract, via droplets or indirectly via fomites, and to a lesser extent via aerosols.  The rapidity with which the infection spread throughout the world was unexpected. The disease has now affected 212 countries, areas, or territories, with more than 2.1 million total confirmed cases and over 144 thousand fatalities as at the time of writing. It, therefore, behooves countries of the world to take firm public health measures for the pandemic is to be contained. Conclusion: Nigeria, with a population of at least 170 million people, is of global interest because a rapid rise in the number of infected people will have serious implications not only for the country but for the whole African continent.%MCEPASTEBIN%

Recent Patents and Advances on Nanotechnologies against Coronavirus

2020 ◽  
Vol 14 ◽  
Author(s):  
Roozbeh Abedini-Nassab ◽  
Naeemeh Mahdaviyan
Keyword(s):  
Middle East ◽  
Severe Acute Respiratory Syndrome ◽  
Genome Sequencing ◽  
Middle East Respiratory Syndrome ◽  
Detection Methods ◽  
Prevention Strategies ◽  
Infected People ◽  
The Third ◽  
The World ◽  
Novel Coronavirus

: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the seven known coronaviruses infecting humans; HKU1, 229E, NL63, OC43, acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2, the last three of which can cause severe symptoms in patients. COVID-19, previously known as 2019 novel coronavirus, caused by SARS-CoV-2, was first reported in Wuhan, China, in late 2019, and quickly resulted in a major epidemic across the world. Although the origin of SARS-CoV-2 is not clear yet, genome sequencing results suggest that this is the third reported spillover of an animal coronavirus to humans, from 2002. The development of detection, therapeutic, and prevention strategies for COVID-19 is a fundamental task towards curing infected people and competing with the pandemic. Because of their similarities, scientists believe that treatment/detection methods similar to what were used against the illnesses caused by SARS-CoV or MERS-CoV may be effective for curing/detecting COVID-19. Here, we review the recent nanotechnology techniques used for treating and testing SARS-CoV, MERS-CoV, and SARS-CoV-2, and potential therapeutic options for curing COVID-19.

scholarly journals Understanding the Dynamics of the COVID-19 Pandemic: A Real-Time Analysis of Switzerland’s First Wave

2020 ◽  
Vol 17 (23) ◽  
pp. 8825
Author(s):  
Marina Giachino ◽  
Camille Beatrice G. Valera ◽  
Sabina Rodriguez Velásquez ◽  
Muriel Anna Dohrendorf-Wyss ◽  
Liudmila Rozanova ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Virus Transmission ◽  
Political Organization ◽  
World Health ◽  
Healthcare Facilities ◽  
Real Time Analysis ◽  
The World ◽  
Show Evidence ◽  
Novel Coronavirus ◽  
Health Organization

Since the novel coronavirus outbreak of SARS-CoV-2 from the first cases whereof were reported in Wuhan, China, in December 2019, our globalized world has changed enormously. On the 11th of March 2020, the World Health Organization (WHO) declared COVID-19 a pandemic, and nations around the world have taken drastic measures to reduce transmission of the disease. The situation is similar in Switzerland, a small high-income country in Central Europe, where the first COVID-19 case was registered on the 25th of February 2020. Through literature review as well as correspondence with public health professionals and experts in mathematical modeling, this case study focuses on the outbreak’s impact on Switzerland and on the measures this country has implemented thus far. Along with the rapid spread of the virus, the political organization, economy, healthcare system, and characteristics of the country greatly influence the approach taken in facing the crisis. Switzerland appears to be structurally well-prepared, but, according to mathematical modeling predictions, in order to avoid total collapse of healthcare facilities, the measures taken by the Swiss Government need to reduce the virus transmission chain by at least 70%. Fortunately, updated models on April 22nd show evidence that the non-pharmaceutical measures invoked have decreased transmission by an estimated 89%, proving effective management by the federal government and allowing for progressive deconfinement measures.

scholarly journals An Overview of Drugs Used in COVID-19: A Pharmacotherapeutic Approach

2021 ◽  
pp. 34-54
Author(s):  
Archith Aithal ◽  
Edwin Dias
Keyword(s):  
Vaccine Development ◽  
Virus Disease ◽  
Antiviral Treatment ◽  
Treatment Strategies ◽  
Global Market ◽  
Research Experience ◽  
Infected People ◽  
The World ◽  
Difficult Challenge ◽  
Novel Coronavirus

Coronavirus originated pandemic disease also called Corona Virus Disease 2019 (COVID-19) is spread all over the world causing severe acute respiratory syndrome (SARS) called SARS-CoV-2 poses a difficult challenge to scientists, researchers, and practitioners to discover effective drugs for prevention and treatment. By using a huge amount of clinical data obtained from many SARS-CoV2 infected people, clinicians are trying to gather accurate evidence for effective treatment and also developing a suitable vaccine system for the prevention of spread of infection for many more people. With no proven therapies which can treat and prevent SARS-CoV-2 is developed until now, there is an opportunity for new researchers in virology to make such an attempt at this crucial time. In this regard, currently, two strategies are active. The first kind of strategy is on developing completely new molecules to prevent and treat this disease, or the second strategy is on testing the effectiveness of already available antivirals and antimalarials for possible potential recovery and prevention. This is done by testing several antivirals (Remdesivir, Favipiravir, etc) and antimalarials (Chloroquine, Hydroxychloroquine, etc) for their potential therapies. Studies show that the most promising therapy is the use of antiviral Remdesivir. Remdesivir has shown the potential ability to exhibit vitro activity to control COVID-19. The drug is currently being tested by ongoing randomized trials. Until a widely accepted drug reaches the global market, different antiviral treatment strategies are used under urgent investigation. In this article, we review the latest research developments related to the systematic treatments for COVID-19 reported from various research labs of different countries. The article also provides a summary of various clinical research experience, intermediate results, and treatment guidance to combat the novel coronavirus epidemic based on pharmacotherapeutic analysis, along with insights to the attempts on vaccine development across the world in order to curb the COVID pandemic.

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