Special Issue "Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control"

Submission Deadline: 31 August 2020 (closed)
Guest Editors
Dr. K. S. Nisar, Prince Sattam bin Abdulaziz University, Saudi Arabia
Dr. Ilyas Khan, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Dr. Muhammad Rafiq, University of Central Punjab, Lahore, Pakistan
Dr. Amjad Shaikh, AKI’s Poona College of Arts, Science and Commerce, Camp. Pune, India

Summary

COVID-19 continues to spread rapidly and one of the uncontrolled infectious around the globe. Almost every country has reported cases, but the burden is asymmetrically distributed. Scientists from various disciplines are trying to find strategies to control and spread of COVID-19. Teamwork can find various types of solutions/suggestions to control such dangerous diseases. In this line, this issue interested to study or analyze the current scenario of the world with the help of mathematical aspects. Potential topics include, but are not limited to the following:

 

1. Analysis and Forecasting COVID 19 growth globally by using computer programming, algorithms, machine learning techniques, etc.

2. Analysing the dynamic for each county for unifying trends, and attempt to interpret them in conjunction with nation-wide control of these dynamics.

3. Computational aspects of infectious diseases, especially, COVID-19.

4. Impact of lockdown in different countries and further suggestion.

5. Formulation of system dynamic model of epidemic spread, incorporated with population and mobility data with the control strategies.

6. The Economic impact of ongoing Pandemic and solutions.

7. Multidisciplinary research on infectious diseases and observations.

8. Effective strategies for helping individuals in dealing with social and physical distancing.

9. Transmission dynamics and simulations of Epidemic models on infectious diseases involving fractional differential operators.

 

Warm reminder: Please select Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control when you submit your article in CMC submission system



Keywords
Infectious diseases, Analysis, Control, computational mathematics related to the pandemic, COVID-19.

Published Papers
  • Analysis and Forecasting COVID-19 Outbreak in Pakistan Using Decomposition and Ensemble Model
  • Abstract COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world. Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases. In this study, we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases, deaths, and recoveries in Pakistan for the upcoming month until the end of July. For the decomposition of data, the Ensemble Empirical Mode Decomposition (EEMD) technique is applied. EEMD decomposes the data into small components, called Intrinsic Mode Functions (IMFs). For individual IMFs modelling, we use the Autoregressive Integrated Moving… More
  •   Views:167       Downloads:101        Download PDF

  • Numerical Analysis of Novel Coronavirus (2019-nCov) Pandemic Model with Advection
  • Abstract Recently, the world is facing the terror of the novel corona-virus, termed as COVID-19. Various health institutes and researchers are continuously striving to control this pandemic. In this article, the SEIAR (susceptible, exposed, infected, symptomatically infected, asymptomatically infected and recovered) infection model of COVID-19 with a constant rate of advection is studied for the disease propagation. A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system. The continuous model is transposed into a discrete numerical model by discretizing the domains, finitely. To analyze the disease dynamics,… More
  •   Views:200       Downloads:163        Download PDF

  • Epidemiological Analysis of the Coronavirus Disease Outbreak with Random Effects
  • Abstract Today, coronavirus appears as a serious challenge to the whole world. Epidemiological data of coronavirus is collected through media and web sources for the purpose of analysis. New data on COVID-19 are available daily, yet information about the biological aspects of SARS-CoV-2 and epidemiological characteristics of COVID-19 remains limited, and uncertainty remains around nearly all its parameters’ values. This research provides the scientific and public health communities better resources, knowledge, and tools to improve their ability to control the infectious diseases. Using the publicly available data on the ongoing pandemic, the present study investigates the incubation period and other time… More
  •   Views:197       Downloads:151        Download PDF

  • Modeling the COVID-19 Pandemic Dynamics in Iran and China
  • Abstract The epidemic outbreak COVID-19 was first detected in the Wuhan city of China and then spread worldwide. It is of great interest to the researchers for its high rate of infection spread and its significant number of fatalities. A detailed scientific analysis of this phenomenon is yet to come. However, it is of interest of governments and other responsible institutions to have the right facts and figures to take every possible necessary action such as an arrangement of the appropriate quarantine activities, estimation of the required number of places in hospitals, assessment of the level of personal protection, and calculating… More
  •   Views:453       Downloads:218        Download PDF

  • Deep Learning and Holt-Trend Algorithms for Predicting Covid-19 Pandemic
  • Abstract The Covid-19 epidemic poses a serious public health threat to the world, where people with little or no pre-existing human immunity can be more vulnerable to its effects. Thus, developing surveillance systems for predicting the Covid-19 pandemic at an early stage could save millions of lives. In this study, a deep learning algorithm and a Holt-trend model are proposed to predict the coronavirus. The Long-Short Term Memory (LSTM) and Holt-trend algorithms were applied to predict confirmed numbers and death cases. The real time data used has been collected from the World Health Organization (WHO). In the proposed research, we have… More
  •   Views:332       Downloads:226        Download PDF

  • Modeling COVID-19 Pandemic Dynamics in Two Asian Countries
  • Abstract The current epidemic outbreak COVID-19 first took place in the Wuhan city of China and then spread worldwide. This deadly disease affected millions of people and compelled the governments and other concerned institutions to take serious actions. Around 0.28 million people have died from the COVID-19 outbreak as of May 11, 2020, 05:41 GMT, and the number is still increasing exponentially. The results of any scientific investigation of this phenomenon are still to come. However, now it is urgently needed to evaluate and compare the disease dynamics to improve the quarantine activities and the level of individual protection, to at… More
  •   Views:399       Downloads:284        Download PDF

  • Computation Analysis of Brand Experience Dimensions: Indian Online Food Delivery Platforms
  • Abstract Online Food Delivery Platforms (OFDPs) has witnessed phenomenal growth in the past few years, especially this year due to the COVID-19 pandemic. This Pandemic has forced many governments across the world to give momentum to OFD services and make their presence among the customers. The Presence of several multinational and national companies in this sector has enhanced the competition and companies are trying to adapt various marketing strategies and exploring the brand experience (BEX) dimension that helps in enhancing the brand equity (BE) of OFDPs. BEXs are critical for building brand loyalty (BL) and making companies profitable. Customers can experience… More
  •   Views:473       Downloads:297        Download PDF

  • Dynamical Behaviors of Nonlinear Coronavirus (COVID-19) Model with Numerical Studies
  • Abstract The development of mathematical modeling of infectious diseases is a key research area in various fields including ecology and epidemiology. One aim of these models is to understand the dynamics of behavior in infectious diseases. For the new strain of coronavirus (COVID-19), there is no vaccine to protect people and to prevent its spread so far. Instead, control strategies associated with health care, such as social distancing, quarantine, travel restrictions, can be adopted to control the pandemic of COVID-19. This article sheds light on the dynamical behaviors of nonlinear COVID-19 models based on two methods: the homotopy perturbation method (HPM)… More
  •   Views:390       Downloads:289        Download PDF

  • Modelling and Simulation of COVID-19 Outbreak Prediction Using Supervised Machine Learning
  • Abstract Novel Coronavirus-19 (COVID-19) is a newer type of coronavirus that has not been formally detected in humans. It is established that this disease often affects people of different age groups, particularly those with body disorders, blood pressure, diabetes, heart problems, or weakened immune systems. The epidemic of this infection has recently had a huge impact on people around the globe with rising mortality rates. Rising levels of mortality are attributed to their transmitting behavior through physical contact between humans. It is extremely necessary to monitor the transmission of the infection and also to anticipate the early stages of the disease… More
  •   Views:500       Downloads:690        Download PDF

  • Prediction of COVID-19 Cases Using Machine Learning for Effective Public Health Management
  • Abstract COVID-19 is a pandemic that has affected nearly every country in the world. At present, sustainable development in the area of public health is considered vital to securing a promising and prosperous future for humans. However, widespread diseases, such as COVID-19, create numerous challenges to this goal, and some of those challenges are not yet defined. In this study, a Shallow Single-Layer Perceptron Neural Network (SSLPNN) and Gaussian Process Regression (GPR) model were used for the classification and prediction of confirmed COVID-19 cases in five geographically distributed regions of Asia with diverse settings and environmental conditions: namely, China, South Korea,… More
  •   Views:1123       Downloads:708        Download PDF

  • Optimal Control Model for the Transmission of Novel COVID-19
  • Abstract As the corona virus (COVID-19) pandemic ravages socio-economic activities in addition to devastating infectious and fatal consequences, optimal control strategy is an effective measure that neutralizes the scourge to its lowest ebb. In this paper, we present a mathematical model for the dynamics of COVID-19, and then we added an optimal control function to the model in order to effectively control the outbreak. We incorporate three main control efforts (isolation, quarantine and hospitalization) into the model aimed at controlling the spread of the pandemic. These efforts are further subdivided into five functions; u1(t) (isolation of the susceptible communities), u2(t) (contact… More
  •   Views:498       Downloads:331        Download PDF

  • An Effective Numerical Method for the Solution of a Stochastic Coronavirus (2019-nCovid) Pandemic Model
  • Abstract Nonlinear stochastic modeling plays a significant role in disciplines such as psychology, finance, physical sciences, engineering, econometrics, and biological sciences. Dynamical consistency, positivity, and boundedness are fundamental properties of stochastic modeling. A stochastic coronavirus model is studied with techniques of transition probabilities and parametric perturbation. Well-known explicit methods such as Euler Maruyama, stochastic Euler, and stochastic Runge–Kutta are investigated for the stochastic model. Regrettably, the above essential properties are not restored by existing methods. Hence, there is a need to construct essential properties preserving the computational method. The non-standard approach of finite difference is examined to maintain the above basic… More
  •   Views:782       Downloads:504        Download PDF

  • Analysis and Dynamics of Fractional Order Mathematical Model of COVID-19 in Nigeria Using Atangana-Baleanu Operator
  • Abstract We propose a mathematical model of the coronavirus disease 2019 (COVID-19) to investigate the transmission and control mechanism of the disease in the community of Nigeria. Using stability theory of differential equations, the qualitative behavior of model is studied. The pandemic indicator represented by basic reproductive number R0 is obtained from the largest eigenvalue of the next-generation matrix. Local as well as global asymptotic stability conditions for the disease-free and pandemic equilibrium are obtained which determines the conditions to stabilize the exponential spread of the disease. Further, we examined this model by using Atangana–Baleanu fractional derivative operator and existence criteria… More
  •   Views:858       Downloads:532        Download PDF


  • Potential Inhibitory Effect of Vitamins Against COVID-19
  • Abstract Coronavirus disease 2019 (COVID-19) is a current pandemic that has affected more than 195 countries worldwide. In this severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, when treatment strategies are not yet clear and vaccines are not available, vitamins are an excellent choice to protect against this viral infection. The rationale behind this study was to examine the inhibitory effect of vitamins B, C, and D against the main protease of SARSCoV-2 and angiotensin-converting enzyme 2 (ACE2), which have critical rolesin the immune system. Molecular docking, performed by using MOE-Dock of the Chemical Computing Group, was used to understand the… More
  •   Views:1252       Downloads:779        Download PDF




  • Analysis of Twitter Data Using Evolutionary Clustering during the COVID-19 Pandemic
  • Abstract People started posting textual tweets on Twitter as soon as the novel coronavirus (COVID-19) emerged. Analyzing these tweets can assist institutions in better decision-making and prioritizing their tasks. Therefore, this study aimed to analyze 43 million tweets collected between March 22 and March 30, 2020 and describe the trend of public attention given to the topics related to the COVID-19 epidemic using evolutionary clustering analysis. The results indicated that unigram terms were trended more frequently than bigram and trigram terms. A large number of tweets about the COVID-19 were disseminated and received widespread public attention during the epidemic. The high-frequency… More
  •   Views:2140       Downloads:1063        Download PDF