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

Submission Deadline: 31 August 2020 (closed)
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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


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

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

Published Papers

  • 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
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