Anders F Johansson

Saving Human Lives: What Complexity Science and Information Systems can Contribute

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Constructing cities, deconstructing scaling laws.

Cities can be characterized and modelled through different urban measures. Consistency within these observables is crucial in order to advance towards a science of cities. Bettencourt et al. have proposed that many of these urban measures can be predicted through universal scaling laws. We develop a framework to consistently define cities, using commuting to work and population density thresholds, and construct thousands of realizations of systems of cities with different boundaries for England and Wales. These serve as a laboratory for the scaling analysis of a large set of urban indicators. The analysis shows that population size alone does not provide us enough information to describe or predict the state of a city as previously proposed, indicating that the expected scaling laws are not corroborated. We found that most urban indicators scale linearly with city size, regardless of the definition of the urban boundaries. However, when nonlinear correlations are present, the exponent fluctuates considerably.

Gravity versus radiation models: On the importance of scale and heterogeneity in commuting flows

We test the recently introduced radiation model against the gravity model for the system composed of England and Wales, both for commuting patterns and for public transportation flows. The analysis is performed both at macroscopic scales, i.e., at the national scale, and at microscopic scales, i.e., at the city level. It is shown that the thermodynamic limit assumption for the original radiation model significantly underestimates the commuting flows for large cities. We then generalize the radiation model, introducing the correct normalization factor for finite systems. We show that even if the gravity model has a better overall performance the parameter-free radiation model gives competitive results, especially for large scales.

Non-communicable health risks during mass gatherings

Mass gatherings (MGs) have been associated with high rates of morbidity and mortality from non-communicable diseases, accidents, and terrorist attacks, thus posing complex public health challenges. We assessed the health risks and public health responses to MGs to identify an evidence-based framework for public health interventions. Human stampedes and heat-related illnesses are the leading causes of mortality. Minor traumatic injuries and medical complaints are the main contributors to morbidity and, particularly, the need for on-site medical care. Infrastructure, crowd density and mood, weather, age, and sex determine the risks to health. Many predictive models for deployment of medical resources are proposed, but none have been validated. We identified the risks for mortality and morbidity during MGs, most efficient public health interventions, and need for robust research into health risks for non-communicable diseases during MGs.

Crowd and environmental management during mass gatherings

Crowds are a feature of large cities, occurring not only at mass gatherings but also at routine events such as the journey to work. To address extreme crowding, various computer models for crowd movement have been developed in the past decade, and we review these and show how they can be used to identify health and safety issues. State-of-the-art models that simulate the spread of epidemics operate on a population level, but the collection of fine-scale data might enable the development of models for epidemics that operate on a microscopic scale, similar to models for crowd movement. We provide an example of such simulations, showing how an individual-based crowd model can mirror aggregate susceptible-infected-recovered models that have been the main models for epidemics so far.

Infectious disease surveillance and modelling across geographic frontiers and scientific specialties.

Infectious disease surveillance for mass gatherings (MGs) can be directed locally and globally; however, epidemic intelligence from these two levels is not well integrated. Modelling activities related to MGs have historically focused on crowd behaviours around MG focal points and their relation to the safety of attendees. The integration of developments in internet-based global infectious disease surveillance, transportation modelling of populations travelling to and from MGs, mobile phone technology for surveillance during MGs, metapopulation epidemic modelling, and crowd behaviour modelling is important for progress in MG health. Integration of surveillance across geographic frontiers and modelling across scientific specialties could produce the first real-time risk monitoring and assessment platform that could strengthen awareness of global infectious disease threats before, during, and immediately after MGs. An integrated platform of this kind could help identify infectious disease threats of international concern at the earliest stages possible; provide insights into which diseases are most likely to spread into the MG; help with anticipatory surveillance at the MG; enable mathematical modelling to predict the spread of infectious diseases to and from MGs; simulate the effect of public health interventions aimed at different local and global levels; serve as a foundation for scientific research and innovation in MG health; and strengthen engagement between the scientific community and stakeholders at local, national, and global levels.

Cooperation, norms, and revolutions: a unified game-theoretical approach.

Background Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. Methodology and Principal Findings To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoners dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Conclusions and Significance Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well.

Applied pedestrian modeling

With an increasing world population and with more cost effective transportation, mass gatherings become ever more frequent. The total size of such gatherings is often as large as millions of people. Furthermore, everyday life in cities becomes increasingly crowded with people. This development has prompted better solutions to mitigate crowded places and make them safer as well as more efficient in terms of travel time. One way to approach this crowd problem is to use crowd modeling tools to assess and optimize locations where pedestrian crowds move around. Within the last decade, crowd modeling has become a mature science and there now exist well calibrated pedestrian models that can reproduce empirically observed crowd features. In this chapter, we will introduce the field of crowd modeling, explain how crowd models can be calibrated with empirical data, and expand a bit on how navigation works in these models.

SIMULACRA: fast land-use-transportation models for the rapid assessment of urban futures

We are building a series of fast, visually accessible, cross-sectional, hence static urban models for large metropolitan areas that will enable us to rapidly test many different scenarios pertaining to both short-term and long-term urban futures. We call this framework SIMULACRA which is a forum for developing many different model variants which can be finely tuned to different problem contexts and future scenarios. The models are multisector, dealing with residential, retail/service, and employment location, are highly disaggregate, and subject to constraints on land availability and transport capacities. They have an explicit urban economic focus around transport costs, incomes, and house prices and thus encapsulate simple market-clearing mechanisms. Here we will briefly outline this class of models, paying particular attention to their structure and the way physical flows and locations are mirrored by economic flows in terms of costs and prices. Several versions of the model now exist, but we will focus, first, on the simplest ‘one-window’ desktop pilot version with the most obvious graphical interface; and, second, on a much more elaborated framework developed for web access, extensible to web service architectures and other related services. To demonstrate its flexibility and intelligibility, we define the various interfaces and demonstrate how the aggregate model can be calibrated to the wider London region to which it is applied. We will demonstrate the model, albeit briefly with respect to the rapid assessment of different urban futures—“what-if” scenarios, based on the impact of new London airports in the Thames Estuary. The key feature of this entire project is that the model and its variants can be run in a matter of seconds, thus entirely changing the traditional dialogue associated with their use and experimentation.

Toward Project Complexity Evaluation: A Structural Perspective

Complexity is often quoted as an independent variable that challenges the utility of traditional project management tools and techniques. A large body of work has been devoted in exposing its numerous aspects, yet means for quantitatively assessing it have been scarce. Part of the challenge lies in the absence of hard evidence supporting the hypothesis that projects can be considered as complex systems, where techniques for measuring such complexity are better established. In response, this study uses empirical activity networks to account for the technological aspect of five projects. By doing so, the contribution of this study is twofold. First, a procedure for the quantitative assessment of an aspect of project complexity is presented; namely, structural complexity. Second, results of the analysis are used to highlight qualitatively similar behavior with a well-known complex system, the Internet. As such, it suggests a transition from the current, metaphorical view of projects being complex systems to a literal one.From a practical point of view, this study uses readily captured and widely used data, enabling practitioners to evaluate the structural complexity of their projects to explore system pathologies and, hence, improve the decision-making process around project bidding, resource allocation, and risk management.