Viral pandemics and infectious diseases have always constituted an imminent threat to humanity since early history. However, scientific advancements in science, public health, medications and vaccines were pivotal in the containment and even the elimination of many of those threats.
The Coronavirus disease (COVID-19) continues as the main cause of hospitalization and death and as a main public health risk since the first case was registered in December 2019. It was declared a global pandemic on March 11, 2020. The recent emergence of variants creates a major cause of concern since they can lead to an epidemic rebound especially with the possibility of the emergence of vaccine resisting, deadlier or more transmissible future variants.
The aim of this Research Topic is to publish articles (research papers, reviews, reports) analyzing spread patterns of infectious diseases using several mathematical, statistical, computational and biophysical methods covering compartmental models, Agent-Based models (ABM), spatiotemporal analysis, data-driven analysis, artificial intelligence and analytic methods. Papers focusing on vaccines, and simulating their role in the prohibition of spreads in relation to their efficacies, availability and scope of implementation on the international and national levels are encouraged.
The topics include but are not limited to:
- Nonlinear dynamics, non-equilibrium processes, complex systems and self-organization modelling of infectious diseases.
- Computational epidemiology, biophysics, medical physics, and computational biology of infectious diseases/COVID-19.
- Statistical, spatiotemporal and big data analytics of COVID-19.
- Applications from the social sciences, public health, economics, engineering in relation to COVID-19 pandemics.
- Modeling, simulations and forecasting of spread patterns, vaccine efficiency, behavioral aspects and public policies.
Viral pandemics and infectious diseases have always constituted an imminent threat to humanity since early history. However, scientific advancements in science, public health, medications and vaccines were pivotal in the containment and even the elimination of many of those threats.
The Coronavirus disease (COVID-19) continues as the main cause of hospitalization and death and as a main public health risk since the first case was registered in December 2019. It was declared a global pandemic on March 11, 2020. The recent emergence of variants creates a major cause of concern since they can lead to an epidemic rebound especially with the possibility of the emergence of vaccine resisting, deadlier or more transmissible future variants.
The aim of this Research Topic is to publish articles (research papers, reviews, reports) analyzing spread patterns of infectious diseases using several mathematical, statistical, computational and biophysical methods covering compartmental models, Agent-Based models (ABM), spatiotemporal analysis, data-driven analysis, artificial intelligence and analytic methods. Papers focusing on vaccines, and simulating their role in the prohibition of spreads in relation to their efficacies, availability and scope of implementation on the international and national levels are encouraged.
The topics include but are not limited to:
- Nonlinear dynamics, non-equilibrium processes, complex systems and self-organization modelling of infectious diseases.
- Computational epidemiology, biophysics, medical physics, and computational biology of infectious diseases/COVID-19.
- Statistical, spatiotemporal and big data analytics of COVID-19.
- Applications from the social sciences, public health, economics, engineering in relation to COVID-19 pandemics.
- Modeling, simulations and forecasting of spread patterns, vaccine efficiency, behavioral aspects and public policies.
