Category: Call for Papers
The novel coronavirus SARS-CoV-2 causes a severe, potentially fatal acute respiratory syndrome, COVID-19, that has paralyzed our societies, leading to prolonged self-isolation and quarantine. Indeed, COVID-19 is a major threat to humans, with alarming levels of spread and death tolls. The WHO situation report published on 30 March 2020 estimated that confirmed cases were almost 700 000, with more than 33 000 deaths. Being that COVID-19 is a global threat, tackling the pandemic requires a global effort involving not only all countries, but also the scientific community at large, across all fields and disciplines.
This call invites the Control Community to contribute from different perspectives to the fight against COVID-19, including the development of appropriate theoretical foundations of epidemiology that may impact the response to future outbreaks of viral or bacterial infections. Several new data sets conveying either epidemiological or clinical information are being made available daily; however, fast data integration at different levels is needed. Modeling and control insight can be crucial to explain and predict the complex dynamics of the disease evolution, and to devise the best strategies to contain the contagion and treat COVID-19 patients.
Our control community can contribute to the solution of several problems, using our technical tools.
Topics of interest include, but are not limited to, the following:
All manuscripts will be peer-reviewed before their acceptance for publication.
The deadline for manuscript submission is June 30th, 2020.
Esteban A. Hernandez-Vargas
Institute of Mathematics, UNAM, Mexico & Frankfurt Institute for Advanced Studies, Germany
University of Trento, Italy
Northeastern University, USA
University of Canterbury, New Zealand
Victor M. Preciado
University of Pennsylvania, USA
College of Engineering Kookmin University, South Korea
Imperial College London, UK
Contact: Esteban Abelardo Hernandez Vargas
Tags: control and modeling
Keywords: COVID-19, Modeling, Control, Networks
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