Each year, crowd disasters happen in different areas of the world. How and why do such disasters happen? Are the fatalities caused by relentless behavior of people or a psychological state of panic that makes the crowd 'go mad'? Or are they a tragic consequence of a breakdown of coordination? These and other questions are addressed, based on a qualitative analysis of publicly available videos and materials, which document the planning and organization of the Love Parade in Duisburg, Germany, and the crowd disaster on July 24, 2010. Our analysis reveals a number of misunderstandings that have widely spread. We also provide a new perspective on concepts such as 'intentional pushing' , 'mass panic' , 'stampede' , and 'crowd crushes' . The focus of our analysis is on the contributing causal factors and their mutual interdependencies, not on legal issues or the judgment of personal or institutional responsibilities. Video recordings show that people stumbled and piled up due to a 'domino effect' , resulting from a phenomenon called 'crowd turbulence' or 'crowd quake' . Crowd quakes are a typical reason for crowd disasters, to be distinguished from crowd disasters resulting from 'mass panic' or 'crowd crushes' . In Duisburg, crowd turbulence was the consequence of amplifying feedback and cascading effects, which are typical for systemic instabilities. Accordingly, things can go terribly wrong in spite of no bad intentions from anyone. Comparing the incident in Duisburg with others, we give recommendations to help prevent future crowd disasters. In particular, we introduce a new scale to assess the criticality of conditions in the crowd. This may allow preventative measures to be taken earlier on. Furthermore, we discuss the merits and limitations of citizen science for public investigation, considering that today, almost every event is recorded and reflected in the World Wide Web. Building codes and regulations for mass events have also been written and updated after recent crowd disasters, such as the ones in Bradford () or Hillsborough, Sheffield () [-]. ,,, Today's knowledge about the dynamics of crowds is considerable and summarized in Refs. [-].  Furthermore, a lot of experience in organizing safer mass events has recently been gained from the organization of religious pilgrimage [-]. In recent years, there is also a quickly growing body of literature on evacuation experiments [, , -] and pedestrian simulations [, , -], and various related commercial software products are now available. Thus, how was it possible that  people died and more than  were injured during the Love Parade on July , ? A crucial point for the safety of mass events is that they are (or at least should be) organized in a way that is robust against many kinds of disturbances (such as weather conditions, human errors, etc.). This is why the organization of a mass event includes the elaboration of contingency plans. Why then can crowd disasters still happen? This paper will reveal that the Love Parade disaster was not the result of a single mistake. We will rather show that the Love Parade disaster resulted from the interaction of several contributing factors. It is probably the first time that a detailed analysis can be performed with publicly available documents: not just investigation reports by public authorities , and the media, but also maps from Google Earth  and  degree photographs,  videos accessible through YouTube,  documents released by Wikipedia ,, and Wikileaks,  and other sources. In some sense, this opens up a new age of public investigation. However, to avoid misunderstandings, we would like to underline that our analysis focuses on the course of events and causal interdependencies among them, while they do not draw any conclusions regarding legal issues or personal or institutional responsibilities, which must be judged by other experts.  The remainder of this paper is structured as follows: Section  provides an overview of the situation before and during the Love Parade disaster. This includes a historical background, a description of the festival area (including in-and outflows), and a timeline reconstructed from many video recordings. Section  will analyze various factors contributing to the disaster, while Section  will focus on causal interdependencies and interaction effects. Section  discusses our findings and Section  concludes with lessons learned for the organization of future mass events. The novelty of this paper is four-fold: it concerns () the structured analysis of large amounts of publicly available video recordings of a disaster, () the interpretation of the disaster as a systemic failure (where the interaction of various factors created a systemic instability, causing an overall loss of control), () a revision of common views about crowd disasters, and () the introduction of a scale reflecting the criticality of crowd conditions (and proposed counter-measures).
Helbing and Mukerji analyzed the Love Parade disaster REF .
Crowd disasters as systemic failures: analysis of the Love Parade disaster
EPJ Data Science
EPJ Data Science
Mathematics Computer Science Physics