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As part of the ESCAPE research program on mass evacuation strategies for population in crisis management, we carried out a survey in the Rouen agglomeration in 2018. This survey focused on knowledge of the warning signal and safety instructions in populations exposed to industrial risk during the day. The accident at the Lubrizol factory on September 26, 2019 gives acuity to certain results of this study which may shed light on the current debate on methods of alerting, transmitting safety instructions and protecting populations.More than 70% of those questioned do not know the national warning signal emitted by sirens and almost 60% do not know the instructions associated with it in the context of an industrial accident. This lack of knowledge would translate into a variety of reflex reactions in the event of an alert being triggered, ranging from indifference to flight, while awaiting additional information. Non-resident populations and tourists have the lowest levels of knowledge of industrial risk safety instructions. When they are known, the instructions are interpreted differently and followed according to the means of travel used by the people at the time of the survey. For the motorist, the abandonment of the vehicle raises many questions and encourages him to continue his journey or flee the area. For the pedestrian, finding shelter can be a real challenge in an urban environment. The vast majority of security personnel and facility managers we interviewed said that they would not allow people into their facility in the event of an alert. The following suggestions for improvement can thus be proposed: (i) a more regular preventive information policy which affects the entire population attending and not only residing in an area at industrial risk, (ii) multi-channel warning and communication means to inform the populations present in a danger zone and (iii) stronger involvement of establishments welcoming the public and their staff in keeping people safe. These three components are elements to be initiated or reinforced to reduce the exposure and vulnerability of populations faced with an industrial accident.

In order to fight against the transmission of dengue, yellow fever, chikungunya and Zika viruses, significant resources were allocated to the process of restricting the propagation of their main vector, the Aedes aegypti mosquito. Research on this mosquito’s living areas is thus necessary to characterize more precisely the areas that need to be monitored and treated. An alternative to field surveys consists of evaluating the characteristics of these living areas through spatialized models. It is in this context that we developed the simulation model MOMA (Model Of Mosquito Aedes aegypti), an agent-based model which integrates a vast set of biological and behavioral knowledge about the mosquito in a simulation environment based on the needs and constraints specific to Aedes aegypti. In this paper, we present MOMA and a study of the effects of local configurations on the dispersion capacity of mosquito cohorts. The simulations in this study were carried out using data from an urban neighborhood in the city of Delhi (India). This virtual laboratory, constructed in collaboration with entomologists, thus makes it possible to represent the mosquito’s living areas, which are either restricted or facilitated by spatial amenities conditioning its needs and its capacity of movement during its lifetime.Keywords: dengue, health, agent-based model, risk, urban area, modeling/modelling

In order to fight against the transmission of dengue, yellow fever, chikungunya and Zika viruses, significant resources were allocated to the process of restricting the propagation of their main vector, the Aedes aegypti mosquito. Research on this mosquito’s living areas is thus necessary to characterize more precisely the areas that need to be monitored and treated. An alternative to field surveys consists of evaluating the characteristics of these living areas through spatialized models. It is in this context that we developed the simulation model MOMA (Model Of Mosquito Aedes aegypti), an agent-based model which integrates a vast set of biological and behavioural knowledge about the mosquito in a simulation environment based on the needs and constraints specific to Aedes aegypti. In this paper, we present MOMA and a study of the effects of local configurations on the dispersion capacity of mosquito cohorts. The simulations in this study were carried out using data from an urban neighbourhood in the city of Delhi (India). This virtual laboratory, constructed in collaboration with entomologists, thus makes it possible to represent the mosquito’s living areas, which are either restricted or facilitated by spatial amenities conditioning its needs and its capacity of movement during its lifetime.

This paper presents MAGeo (Modeling Agent in Geography), a user-friendly agent-based simulation tool dedicated to spatialized and multilevel researches. Model development with MAGeo does not require any particular programming skills. The conceptual model is realized through graphical objects, such as boxes and links to organize them. Model's ontology is based on the following three entities: Agent - Organization - Behavior that allow the building of multilevel model. The modeler has access to the simulation window in order to develop its model's dynamic. Simulation model is built using cursors and other graphical tools to parametrize the model, as well as maps and graphs to explore the model's behavior. MAGeo is readily accessible to social scientists which aim to develop spatialized and complex models but don’t possess programming skill. Because learning MAGeo and developing model is not time-consuming, MAGeo is also well designed for teaching complex system. Finally, its graphical approach produces perfect systemic and multilevel graphics for communication in multidisciplinary teams.

Industrial accidents are a major risk in many countries. Despite this observation, effective preventive action is not being developed and studies of the behaviors of vulnerable populations remain under-explored. According to safety instructions, residents must take shelter and remain indoors but other behaviors may be observed such as: running away from the affected area, panicking, or following people around. In order to assess the attitudes of people and the effects of local contingencies that could interfere with official advice in the event of a toxic cloud, a specific agent-based model called TOXI-CITY has been developed. The aim of this explorative model is to determine whether a minimum number of well-informed agents (i.e. those who follow the emergency protocol) can save a maximum number of uninformed and impressionable ones. Simulations indicate that the initial number of agents and the spatial configuration of the grid strongly influence final survival rates. A non-linear pattern emerged: survival rates increase when well-informed agent rates are low (below 30%) while increasing the percentage of informed agents (from 70%) seems to improve only slightly the chances of survival.

The appearance of S-curve in the treatment of a space-time data is very often associated to a spatial diffusion. This systematic assimilation of the S-curve to the logistic model is misleading, , it leads to an amalgam which masks the diversity of mathematical models to capture really different phenomena of diffusion.The aims of this paper is to show some examples of diffusion which are all expressed by a S-curve but which correspond in fact to different models. Three models are presented:- logistic model is the most usually used by geographers despite his independency from space. We compare here a spatialized and probabilistic version of this model with its analytical and deterministic form.- as opposed to the first one, the front diffusion model imposes a strong space constraint, the contact being prevalent in the diffusion. In this case, diffusion is not subjected to a global constraint but depends on the length and on the form of the front at any moment.- the third model is composite, it proceeds of the logistic growth forced by local constraints and of propagation of a front.These three models are studied in their analytical forms and are compared with their dynamic simulated. We show a continuity between these 3 models entering within the framework of a broader class of parameterized models. Moreover their combinations give an expansion of other models making it possible to apply to a great variety of problems.

The question of complexity and its increasing application to social sciences is challenging the modelling of spatial systems. New concepts and new methods have been proposed and invite to reformulate classical modelling frames. This approach demands to open a better-informed dialogue between the disciplines which supply models and tools and those where the existing knowledge is reformulated inside this new frame. Creating an « artificial geography » is not straightforward. It is rather easy to translate urban theories within the paradigm of complex systems, but their modelling, for instance by using multi-agent systems, still raises many conceptual and practical difficulties. We underline here some problems in defining significant urban entities and exploring the evolution of their spatial relationships over time. We briefly present which options have been selected for developing the SIMPOP2 model which is conceived to simulate the evolution of systems of cities over long periods of time.

This paper presents the main contributions of an agent-based approach for modelling and simulating the processes of diffusion in geographical space. This approach is compared with the macro modelling traditionally employed to describe such phenomenons. The logistic model is thus presented as representative of this category of model. The agent-based models represent a possible alternative to a macroscopic approach of the processes of diffusion. Related to the theories of self-organization, it is assumed that the phenomena observed on a certain level are the result of the many interactions which occur on one or more lower levels. As a simulation tool predisposed to the analysis of such a dynamic, the multi-agent systems are briefly presented. This paper ends with a brief example of application, the modelling and the simulation of the diffusion of an agricultural innovation model (Hägerstrand's model revisited).