Happy Halloween....

As today is Halloween, I thought I would write a brief post on zombies and how they can be used to demonstrate disease models (even the Centers for Disease Control and Prevention (CDC) has a post about Zombies preparedness). There are several good examples of using zombie outbreaks as demonstrations for the utility of modeling (or just showing how modeling concepts can be applied to the spread of zombies). 

These range from exploring  the spatial and temporal dynamics of a zombie epidemic (e.g. Sander and Topaz, 2014). To that of the work of Alemi et al. (2015), who produced a "danger map" of what would happen if the continental United States  was overrun with zombies (an interactive version is available here and shown below). In their paper, they demonstrate how epidemiological processes akin to a Susceptible-Infected-Recovered (SIR) model (which we have wrote about before) can be used to model the spread of zombies. As its a zombie model, the SIR changes to a SZR model (Munz et al., 2009), where:

 "S represents the susceptible population, the uninfected humans, Z represents the infected state, zombies, and R represents our removed state, in  this  case  zombies  that  have  been  terminated  by  humans (canonically  by  destroying  their  brain  so  as  to  render  them inoperable)." (Alemi et al., 2015)

Zombie Town USA

Below you can see an attempt of modeling a zombie outbreak (only the SI parts) in one of the buildings on the George Mason Fairfax campus utilizing NetLogo (you can download the model code from here).

More complex individual based models have also been created like the one shown below by Horio and Arrowsmith (2015) which was used to showcase how zombies can be used to describe complex adaptive systems and agent-based modeling.

If readers know of any over good Halloween (horror) like models, please let us know.

References:

Alemi, A.A., Bierbaum, M., Myers, C.R. and Sethna, J.P. (2015), 'You Can Run, You Can Hide: The Epidemiology and Statistical Mechanics of Zombies', Physical Review E, 92(5): 052801.
Horio, B. and Arrowsmith, N. (2015), 'The Pedagogy of Zombies', OR/MS Today, 42(5).
Munz, P., Hudea, I., Imad, J. and Smith, R.J. (2009), 'When Zombies Attack!: Mathematical Modelling of an Outbreak of Zombie Infection', in Tchuenche, J.M. and Chiyaka, C. (eds.), Infectious Disease Modelling Research Progress, Nova Science Publishers, Hauppauge, NY, pp. 133-150.
Sander, E. and Topaz, C.M. (2014), 'The Zombie Swarm: Epidemics In The Presence of Social Attraction And Repulsion', in Smith, R. (ed.) Mathematical Modelling of Zombies, University of Ottawa Press, Ottawa, Canada, pp. 265-300.

AAG2018: Innovations in Urban Analytics

Call for Papers, AAG2018: Innovations in Urban Analytics

We welcome paper submissions for our session at the Association of American Geographers Annual Meeting on 10-14 April, 2018, in New Orleans.

Session Description

New forms of data about people and cities, often termed ‘Big’, are fostering research that is disrupting many traditional fields. This is true in geography, and especially in those more technical branches of the discipline such as computational geography / geocomputation, spatial analytics and statistics, geographical data science, etc. These new forms of micro-level data have lead to new methodological approaches in order to better understand how urban systems behave. Increasingly, these approaches and data are being used to ask questions about how cities can be made more sustainable and efficient in the future.

This session will bring together the latest research in urban analytics. We are particularly interested in papers that engage with the following domains:

• Agent-based modelling (ABM) and individual-based modelling;
• Machine learning for urban analytics;
• Innovations in consumer data analytics for understanding urban systems;
• Real-time model calibration and data assimilation;
• Spatio-temporal data analysis;
• New data, case studies, demonstrators, and tools for the study of urban systems;
• Complex systems analysis;
• Geographic data mining and visualization;
• Frequentist and Bayesian approaches to modelling cities.

Please e-mail the abstract and key words with your expression of intent to Nick Malleson (n.s.malleson@leeds.ac.uk) by 18 October, 2017 (one week before the AAG abstract deadline). Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at: http://annualmeeting.aag.org/submit_an_abstract. An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.

For those interested specifically in the interface between research and policy, they might consider submitting their paper to the session “Computation for Public Engagement in Complex Problems” (http://www.gisagents.org/2017/10/call-for-papers-computation-for-public.html).

Key Dates

• 18 October, 2017: Abstract submission deadline. E-mail Nick Malleson by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent.
• 23 October, 2017: Session finalization and author notification.
• 25 October, 2017: Final abstract submission to AAG, via the link above. All participants must register individually via this site. Upon registration you will be given a participant number (PIN). Send the PIN and a copy of your final abstract to Nick Malleson (n.s.malleson@leeds.ac.uk). Neither the organizers nor the AAG will edit the abstracts.
• 8 November, 2017: AAG session organization deadline. Sessions submitted to AAG for approval.
• 9-14 April, 2018: AAG Annual Meeting.

Session Organizers

• Nick Malleson, University of Leeds, UK
• Alison Heppenstall, University of Leeds, UK
• Andrew Crooks, George Mason University, US
• Tuuli Toivonen, University of Helsinki, Finland
• Alex Singleton, University of Liverpool, UK
• Ed Manley, UCL, UK

Generation of Realistic Mega-City Populations and Social Networks for ABM

At the upcoming 2017 Annual conference of the Computational Social Science Society of the Americas, Annetta Burger, Talha Oz, William Kennedy and myself have a paper entitled: "Generation of Realistic Mega-City Populations and Social Networks for Agent-Based Modeling". 

In the paper we discuss some of our current work of generating synthetic human populations with realistic social networks with respect to the New York mega-city and surrounding region. Below you can read the abstract of the paper and see our workflow along with some initial results. The full reference to the paper and a link to the pdf can be found at the bottom of the post.

Abstract:

Agent-based modeling is a means for researchers to conduct large-scale computer experiments on synthetic human populations and study their behaviors under different conditions. These models have been applied to questions regarding disease spread in epidemiology, terrorist and criminal activity in sociology, and traffic and commuting patterns in urban studies. However, developing realistic control populations remains a key challenge for the research and experimentation. Modelers must balance the need for representative, heterogeneous populations with the computational costs of developing large population sets. Increasingly these models also need to include the social network relationships within populations that influence social interactions and behavioral patterns. To address this we used a mixed method of iterative proportional fitting and network generation to build a synthesized subset population of the New York megacity and region. Our approach demonstrates how a robust population and social network relevant to specific human behavior can be synthesized for agent-based models. 

Keywords: Agent-based Models, Geographical Systems, Population Synthesis, Social Networks, Megacity.

Full Reference: 

Burger, A., Oz, T., Crooks, A.T. and Kennedy, W.G. (2017). Generation of Realistic Mega-City Populations and Social Networks for Agent-Based Modeling, The Computational Social Science Society of Americas Conference, Santa Fe, NM. (pdf)

Call for Papers – Computation for Public Engagement in Complex Problems

Call for Papers – Computation for Public Engagement in Complex Problems: From Big Data, to Modeling, to Action 

We welcome paper submissions for our session(s) at the Association of American Geographers Annual Meeting on 9-14 April, 2018, in New Orleans.  

Session Description: In line with one of the major themes of this conference, we explore the opportunities and challenges that geo-computational tools offer to support public engagement, deliberation and decision-making to address complex problems that link human, socioeconomic and biophysical systems at a variety of different spatial and temporal scales (e.g., climate change, resource depletion, and poverty). Modelers and data scientists have shown increasing interest in the intersection between science and policy, acknowledging that, for all the computational advances achieved to support policy and decision-making, these approaches remain frustratingly foreign to the public they are meant to serve. On one hand, there is a persistent gap in the public’s understanding of and reasoning about complex systems, resulting in unintended and undesirable consequences. On the other hand, there is significant public skepticism about the knowledge generated by the modeling community and its ability to inform policy and decision-making.

We invite theoretical, methodological, and empirical papers that explore advances in geo-computational approaches, including part or all the process to address complex problems: from data collection and analysis, to the development and use of models, to supporting action with data analysis and modeling. We are interested in any work that contributes towards the overall goal of supporting public engagement and action around complex problems, including—but not limited to—the following topics:

• epistemological perspectives; 
• extracting behavioral rules from novel and established data sets; 
• innovative applications of complex systems techniques, and 
• addressing the challenge of complex systems model calibration and validation. 

Please e-mail the abstract and key words with your expression of intent to Moira Zellner (mzellner@uic.edu) by October 18, 2017 (one week before the AAG abstract deadline). Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at: http://annualmeeting.aag.org/submit_an_abstract. An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.

 Timeline summary: 

• October 18, 2017: Abstract submission deadline. E-mail Moira Zellner (mzellner@uic.edu) by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent. 
• October 23, 2017: Session finalization and author notification. 
• October 25, 2017: Final abstract submission to AAG, via the link above. All participants must register individually via this site. Upon registration you will be given a participant number (PIN). Send the PIN and a copy of your final abstract to Moira Zellner. Neither the organizers nor the AAG will edit the abstracts. 
• November 8, 2017: AAG session organization deadline. Sessions submitted to AAG for approval. 
• April 9-14, 2018: AAG Annual Meeting.  

Organizers:

• Moira Zellner, Department of Urban Planning and Policy, University of Illinois at Chicago.
• Andrew Crooks, Department of Computational and Data Sciences, George Mason University 
• Tom Evans, Department of Geography, Indiana University 
• Jeon-Young Kang, Department of Geography, SUNY at Buffalo 
• Jared Aldstadt, Department of Geography, SUNY at Buffalo 
• Arika Ligmann-Zielinska, Department of Geography, Michigan State University