During the transition from the year 2019 to the year 2020, the world was introduced to a new virus that commenced affecting its cities and the people residing in them.

March 11th 2020 marked the day that the WHO declared the world is coping with a pandemic.

Covid-19, the virus causing this pandemic, has spread extensively from Wuhan, China to cities like New York, Madrid, Moscow and Bergamo.

Cities are complex systems[1], and the entrance of an uninvited virus adds to their unpredictable, dynamic nature.

Some cities were put under lockdown, restricting the movement and economic activities of their citizens, while others did not wish interfering with the natural flow of urban life, imposing minimal limitations.

While cities around the world are adapting to the life alongside Covid-19, this unusual situation creates a fertile ground for contemplation about urban living during a pandemic and its aftermath.

TAU City Center invites students across the globe to share their thoughts and impressions on how their city has been affected by and coped with Covid-19.

This Project aims to display different perspectives reagrding urban living during the Covid-19 pandemic.

Source: en-urban.tau.ac.il

The Department of Network and Data Science (DNDS) at the Central European University (CEU) carries out research in network science, with a special focus on the foundations and applications of network science to practical data-driven problems. A key element of the mission of DNDS is to work across disciplines to bring network and data science tools to many fields of the social sciences and related areas. DNDS translates these ideas into research projects – our faculty have won several major grants, from European Union and US funding agencies. DNDS offers a PhD Program and an Advanced Certificate Program in Network Science and will host a BA in Quantitative Social Sciences starting, presumably, in 2021. Data science tools and the network science approach offer a unique perspective to tackle complex problems, impenetrable to linear-proportional thinking. Building on decades of development of fundamental understanding of networks, the modern data deluge has opened up unprecedented opportunities to study and understand the structure and function of social, economic, political and information systems. Data-driven network science aims at explaining complex phenomena at larger scales emerging from simple principles of network link formation.

Source: www.ceu.edu

The Complex Systems Society announces the seventh edition of the CSS Scientific Awards. These awards are conferred once a year in two categories: the senior scientific award will recognize outstanding contributions of Complex Systems scholars at whatever stage of their careers, whereas the junior scientific award is aimed at recognizing excellent scientific record of young researchers (within 10 years of PhD completion).

See https://cxdig.wordpress.com/calls/64 and https://cxdig.wordpress.com/calls/65.

Deadline: June 15, 2020.

See https://cxdig.wordpress.com/community/css-awards for the list of previous awardees.

Source: cssociety.org

During the last decade, economic development efforts have been marked by both a return of industrial policy [1–3] and the growing need to consider social and environmental sustainability [4–7]. At the intersection of both of these topics, we find important policy efforts, such as Europe’s Green Deal [8], and also a growing academic literature on economic complexity [9,10], green growth [11], green innovation [12,13], and sustainability. On the one hand, this literature is exploring how the product space [3] and the principle of relatedness [14] can facilitate an economy’s transition into green products [15–18]. On the other hand, this literature is exploring the connection between environmental sustainability and the complexity of an economy [19–22]. In fact, evidence thus far shows that economies tend to reduce emissions when they become sufficiently complex [21–23], and also, that higher complexity economies tend to experience lower levels of income inequality [7] and higher levels of human development [24].

The purpose of this Special Issue is to stimulate, promote, and gather research at the intersection between environmental sustainability, social sustainability, and economic complexity. We are looking for contributions exploring these and other topics:

 

• Relatedness and the development of green products/jobs/industries;
• Sustainability and global value chains;
• Economic complexity, environmental sustainability, and the environmental Kuznets curve;
• Economic complexity, inequality, and sustainable human development;
• Green Growth;
• Green Innovation.

Source: www.mdpi.com

Discover the role forecasts and computer models play in understanding pandemics

With the world in the grip of the coronavirus pandemic, there has been a surge of interest in scientific modelling of the outbreak.

On this course, you’ll explore the social, economic, and political factors in the spread of a pandemic such as COVID-19, examining how scientists try to forecast the spread and severity of epidemics, and what we can and can’t know.

You’ll use interactive graphical programs to explore the dynamics of epidemics, learning how to critique the underlying models, and how science and computer models can support policymakers in times of pandemic crisis.

Source: www.futurelearn.com