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Mathematical Models for Infectious Diseases

Humanity has the ability to control the environment within which it resides. In day-to-day life, humans interact with different beings cohabiting their world. These interactions can sometimes be harmful or destructive to living beings and humans, and as a result, humanity has developed techniques, weapons and sophisticated technological instruments to help reduce the threat. Despite technological advances, we are continuously exposed to new challenges, and constantly face biological threats within our environment. Viruses are one such threat. Invisible to the human eye, they live in the air, soil, and water and on material surfaces and are responsible for a number of diseases that kill millions of people. Most recently, the rise of a new strain of coronavirus called SARS-COV-2 developed into a pandemic that has claimed over 200,000 lives between its first documented case in December 2019 in Wuhan, China, and May 1, 2020.

To combat these invisible enemies, we rely on the study of their behaviors in laboratories, analysis, and prediction. To perform the analysis and prediction, observed facts are converted into models using mathematical tools, including, differentiation, integration and statistical approaches.  These models are analyzed and solved analytically or numerically for prediction using some obtained parameters and initial conditions. This present special issue is devoted to a collection of latest results from theoretical to application on research based on latest infectious diseases with focus topic including but not limited to:

  • SEIR modelling (systems of ordinary differential equations)
  • Spatial models (with partial differential equations)
  • Traveling waves and similar topics
  • Discrete (difference systems) models
  • Agent-based models
  • Models based on stochastic approaches

Lead Guest Editor: Prof. Dr. Abdon Atangana, University of the Free State, South Africa, Email:

Guest editors:

  • Prof. Dr. Muhammad Altaf Khan, City University of Science and Information Technology, Pakistan. email:
  • Prof. Dr. Jose Francisco Gomez Aguila, Centro Nacional de Investigación y Desarrollo Tecnológico. Tecnológico Nacional de México. Email:
  • Prof. Dr. Dumitru Baleanu, Cankaya University, Turkey, email:
  • Prof. Dr. Emile Franc Doungmo Goufo, University of South Africa, email:
  • Dr. Abdullahi Yusuf, Federal University Dutse, Nigeria, email:

Only papers with new and outstanding results related to Corona within this scope will be accepted to be reviewed. Routinely submissions and papers with only theoretical values will be directly rejected without being sent to review.

Important dates:
Opened submission date: 13 April 2020
Submission Deadline: 31 December 2020

Submission Instructions:
Before submitting your manuscript, please ensure you have carefully read the submission guidelines for Advances in Difference Equations. The complete manuscript should be submitted through the journal's submission system. To ensure that you submit to the correct thematic series please select the appropriate thematic series in the drop-down menu upon submission. In addition, indicate within your cover letter that you wish your manuscript to be considered as part of the thematic series on coronavirus/COVID-19. All submissions will undergo rigorous peer-review and accepted articles will be published in the journal as a collection. 

Submissions will also benefit from the usual advantages of open access publication: 

Rapid publication: Online submission, electronic peer review, and production make the process of publishing your article simple and efficient 

High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article 

No space constraints: Publishing online means unlimited space for figures, extensive data and video footage

Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed.

For all information in one page kindly download the PDF below:

Mathematical Models of Infectious Diseases (PDF, 53.2 kB)

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