About this Research Topic
The World Health Organization (WHO) has declared the 2019 novel coronavirus outbreak (COVID-19) as a pandemic on March 11th. As of the end of April 2020, more than 3 million COVID-19 cases and 200 thousands death have been reported from more than 200 countries. It is therefore important to know what to expect in terms of the growth of the number of cases, and to understand what is needed to arrest the very worrying trends. In this disruptive period of the COVID-19 pandemic, scientists are investing an unprecedented effort to try to forecast and suggest measures to mitigate the ill-fated effects of the pandemic. Although recent literature indicates that travel control and restrictions of public activities are effective in delaying the spreading of the COVID-19 epidemic in China (Heory et al. 2020; Chinazzi et al. 2020), there is still an urgent need for greater understanding of the intrinsic dynamics and effective control methods which can offer in emergency and pandemic management.
This Research Topic aims to extend the angles and collect articles which propose data driven mathematical or statistical models of the spread of the COVID-19, and/or of its foreseen consequences on public health, society, industry, economics and technology. It also focuses on collecting the real-time big data of COVID-19 spreading, and further helps the scientists to establish the efficient databases for the risk management. Furthermore, we also want to understand the impact of the pandemic on the economy and society of the whole world, and provide efficient suggestions for economic recovery and social order maintenance. The editors and reviewers of this special issue will guarantee a fast, but fair, peer-to-peer review procedure, in order to provide to society a reliable injection of scientific insights.
The scopes and topics include but are not limited to:
• nonlinear dynamics and non-equilibrium processes of COVID-19;
• complex system and complex networks modeling of COVID-19;
• computational epidemiology, biophysics, systems biology and computational biology aspects of COVID-19;
• artificial intelligence, machine learning and big data analytics of COVID-19;
• self-organization and emergent phenomena of social organization with COVID-19 pandemics;
• applications to social science, Public health, economics, engineering and other aspects related to COVID-19 pandemics.
Note: Articles on COVID19 submitted to this Research Topic before the 31st of July will be free of charge.
This Research Topic aims to extend the angles and collect articles which propose data driven mathematical or statistical models of the spread of the COVID-19, and/or of its foreseen consequences on public health, society, industry, economics and technology. It also focuses on collecting the real-time big data of COVID-19 spreading, and further helps the scientists to establish the efficient databases for the risk management. Furthermore, we also want to understand the impact of the pandemic on the economy and society of the whole world, and provide efficient suggestions for economic recovery and social order maintenance. The editors and reviewers of this special issue will guarantee a fast, but fair, peer-to-peer review procedure, in order to provide to society a reliable injection of scientific insights.
The scopes and topics include but are not limited to:
• nonlinear dynamics and non-equilibrium processes of COVID-19;
• complex system and complex networks modeling of COVID-19;
• computational epidemiology, biophysics, systems biology and computational biology aspects of COVID-19;
• artificial intelligence, machine learning and big data analytics of COVID-19;
• self-organization and emergent phenomena of social organization with COVID-19 pandemics;
• applications to social science, Public health, economics, engineering and other aspects related to COVID-19 pandemics.
Note: Articles on COVID19 submitted to this Research Topic before the 31st of July will be free of charge.
Keywords: COVID-19, Epidemic Spreading, Pattern Recognition, Mathematical modelling, Transmission dynamics, Disease Prediction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
