The study of how social organizations work, change and develop is central to sociology and to our understanding of the social world and its transformations. At the same time, the underlying principles of organizational dynamics are extremely difficult to investigate. This is partly due to the difficulties of tracking organizations, individuals and their interactions over relatively long periods of time. But it is also due to limitations in the kinds of quantitative methods used to tackle these questions, which are for the most part based on regression analysis. This thesis seeks to improve our understanding of social organizing by using models to explore and describe the logics of the structures and mechanisms underlying organizational change. Particular emphasis is given to the modeling process, the use of new concepts and analogies, and the application of interdisciplinary methods to get new insights into classical sociological questions. The thesis consists of an introductory part and five studies (I-V). Using Swedish longitudinal data on employment in the Stockholm Region, the studies tackle different dimensions of organizational dynamics, from organizational structures and growth processes to labor mobility and employment trajectories. The introductory chapters contextualize the studies by providing an overview of theories, concepts and quantitative methods that are relevant for the modeling of organizational dynamics.  The five studies look into various aspects of organizational dynamics with the help of complementary data representations and non-traditional quantitative methods. Study I analyzes organizational growth statistics for different sectors and industries. The typically observed heavy-tailed statistical patterns for the size and growth rate distributions are broken down into a superposition of interorganizational movements. Study II models interorganizational movements as a labor flow network. Organizations tend to be more tightly linked if they belong to the same ownership sector. Additionally, public organizations have a more stable connection structure. Study III uses a similarity-based method called homogeneity analysis to map out the social space of large organizations in the Stockholm Region. A social distance is then derived within this space, and we find that the interorganizational movements analyzed in Studies I and II take place more often between organizations that are closer in social space and in the same network community. Study IV presents an approach to organizational dynamics based on sequences of employment states. Evidence for a positive feedback mechanism is found for large and highly sequence-diverse public organizations. Finally, Study V features an agent-based model where we simulate a social influence mechanism for organizational membership dynamics. We introduce a parameter analogous to a physical temperature to model contextual influence, and the familiar growth distributions are recovered as an intermediate case between extreme parameter values. The thesis as a whole provides suggestions for a more process-oriented modeling approach to social organizing that gives a more prominent role to the logics of organizational change. Finally, the series of methodological tools discussed can be useful for the analysis of many other social processes and more broadly for the development of quantitative sociological methods. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.</p><p> </p>

En France, dans un contexte d’accident technologique, les consignes de mise en sécurité de la population préconisent le confinement à défaut de l’évacuation, pour laquelle les retours d’expérience à l’échelle d’une ville sont rares. De plus, s’il existe de nombreux documents de gestion du risque et de crise, ces derniers n’intègrent que de manière très marginale la population automobile, pour laquelle l’évacuation demeure pourtant la solution la plus adaptée. Le (bon) déroulement d’un tel processus dépend à la fois de la stratégie mise en place par les autorités publiques (le cas échéant) et des dynamiques de déplacement, rythmées par les choix opérés par chaque automobiliste. En effet, certains comportements individuels peuvent générer des conflits en quelques points du réseau routier et contribuer ainsi à une augmentation du temps nécessaire pour évacuer les automobilistes présents sur l’ensemble du réseau exposé. Ce travail de recherche s’est attaché, par la simulation multi-agents, à développer une méthode capable de rendre compte, dans l’espace et dans le temps, des conséquences que pourraient engendrer telle ou telle stratégie d’évacuation, à Rouen (Normandie). À partir d’une modélisation des déplacements quotidiens, une série de scénarios d’évacuation a été testée, combinant la mise en place ou non d’itinéraires spécifiques, le maintien ou non de la signalétique et l’adoption d’un comportement impatient de conduite par un certain nombre d’automobilistes. L’efficacité de chaque stratégie, définie en termes de durée d’évacuation totale, est complétée par une analyse cartographique et dynamique des zones problématiques (saturées) du réseau rouennais. / In France, when an industrial accident occurs, the population confinement mainly prevails over its evacuation. Moreover, the latter suffers a lack of experience feedbacks, especially at the city scale. In addition, while numerous risk management and crisis documents exist, they marginally integrate the car drivers, for which evacuation does remain the most appropriate solution. The (good) progress of such a process depends both on (1) the public authorities’ strategy and (2) the choices made by each car driver during his trip. Indeed, some individual behaviors can generate conflicts in some points of the road network, and thus increase the duration of the whole network discharge. Thanks to the multi-agents simulation, we developed a method able to report the spatio-temporal consequences generated by different evacuation strategies, in Rouen (Normandy). Based on a daily travel model, a series of evacuation scenarios is tested, combining whether or not specific routes are set up, whether or not signage are maintained, and the adoption of an impatient behavior by some car drivers. The effectiveness of each strategy is defined by the total evacuation duration, and completed by a cartographic and dynamic analysis of the jammed areas of the Rouen network.

NetLogo has become a standard platform for agent-based simulation, yet there appears to be widespread belief that it is not suitable for large and complex models due to slow execution. Our experience does not support that belief. NetLogo programs often do run very slowly when written to minimize code length and maximize clarity, but relatively simple and easily tested changes can almost always produce major increases in execution speed. We recommend a five-step process for quantifying execution speed, identifying slow parts of code, and writing faster code. Avoiding or improving agent filtering statements can often produce dramatic speed improvements. For models with extensive initialization methods, reorganizing the setup procedure can reduce the initialization effort in simulation experiments. Programming the same behavior in a different way can sometimes provide order-of-magnitude speed increases. For models in which most agents do nothing on most time steps, discrete event simulation—facilitated by the time extension to NetLogo—can dramatically increase speed. NetLogo’s BehaviorSpace tool makes it very easy to conduct multiple-model-run experiments in parallel on either desktop or high performance cluster computers, so even quite slow models can be executed thousands of times. NetLogo also is supported by efficient analysis tools, such as BehaviorSearch and RNetLogo, that can reduce the number of model runs and the effort to set them up for (e.g.) parameterization and sensitivity analysis.

Abstract in English / Mathematical modeling of the spread of infectious diseases in a population has always been recognized as a powerful tool that can help decision-makers understand how a disease evolves over time. With the evolution of science and humanity, it has become evident that Mathematical models are too simplistic and have some limitations in modeling environmental phenomena, such as the spread of epidemics in a population, when they are applied without combining them with other sciences. In understanding the dynamics of epidemics in a population, the weakness of these models is their difficulty in grasping the complexity inherent in the spread of diseases in real life because, life is supported by human interactions and behaviors that are understood through networks of social and spatial interactions. Modeling the spread of epidemics which takes this reality into account requires the implementation of new tools to refine the results already obtained by mathematical models. The aim of this thesis is to explore and attempt to extend new developments in mathematical modeling of the spread of infectious diseases by proposing new tools based on mathematical models from differential equations and agent-based models from intelligent agents derived from artificial intelligence. To achieve this objective, the study starts from a comparative study of two ways of modeling and simulation of the spread of infectious diseases in the population, namely mathematical modeling and agent-based modeling with a concrete case study of the spread of tuberculosis based on data from the Democratic Republic of the Congo (DRC). Then comes a coupling study of these two approaches in a single model and its implementation in a multi-scale environment. The results show that the coupled model is more realistic compared to mathematical models generally implemented in the literature. Four case studies are presented in this thesis. Mathematical modeling based on differential equations is used in the first and second cases. The third case is based on intelligent agents model while the last one is based on the coupling of mathematical models and agent-based models. Application of implemented models to the spread of tuberculosis reveals that detection of people with latent tuberculosis and their treatment are among the actions to be taken into account in addition to those currently carried out by the Congolese health system. The models assert that the current TB situation in DRC remains endemic and that the necessary measures need to be taken to reduce the burden of TB, especially to control it, through the tuberculosis elimination strategy and its elimination in the future in accordance with the Sustainable Development Goals. Our hybrid model benefiting from the advantages of EBM and ABM confirms that taking the individual into account as a fully-fledged entity and managing their behavior gives the microscopic aspect of the model set up and brings it closer as much as possible to reality. Mathematical management of the spread of the disease in cities gives a macroscopic aspect to the model. Numerical simulations of this last model on a multi-scale virtual environment affirm that the mobility of individuals from city to city has a significant impact on the spread of tuberculosis in the population. Controlling the rate of population mobility from one city to another is one of the most important measures for large-scale disease control. This model therefore draws its richness from this dynamic at two different scales (two time scales modeling approaches: at the microscopic/individual level (ABM) and macroscopic/city level (ODE)), which gives the emergence of the model at the global level. As a result, it seems that the coupling of mathematical models to agent-based models should be applied when the dynamics of the complex system under consideration is at different scales. Based on our research results, it seems that the choice of an approach must depend on how the modeler would like to achieve the expected results. Mathematical models remain essential due to their analytical and synthetic aspect, but their coupling with intelligent agent-based models makes it possible to refine known results and thus reflect the reality of real life, because the resulting model integrate interactions of individuals and their heterogeneous behaviors that are necessary for understanding the spread of infectious diseases in the population that only mathematical models based on differential equations can not capture. / Mathematical Sciences / Ph D. (Applied Mathematics)

The increasing demand for food and fiber, the need for climate change mitigation and adaptation as well as for environmental protection impose severe challenges on land systems worldwide. Solutions to support the transformation towards a sustainable development of land systems are needed. One response to the multiple challenges is the introduction of policy options aimed at steering land use activities towards a bundle of societal goals. However, it is difficult to empirically foresee the effectiveness and unintended consequences of policy options prior to their deployment. A second response is environmental education because human consumption behavior, among other factors, strongly influences natural ecosystems. However, it is a non-trivial task to develop effective communication strategies for complex topics such as sustainable land management. In both cases, modeling can help to overcome the different obstacles along the way. In this thesis, dynamic process-based social-ecological models at the individual scale are developed and analyzed to study effectiveness and unintended side effects of policy options, which promote agricultural management strategies and were intentionally designed to cope with multiple societal challenges. Two case studies of political intervention are investigated: the promotion of perennial woody crops in European agricultural landscapes for a sustainable bioeconomy and governmental supplementary feeding programs to cope with climate risks in pastoral systems in drylands. These two case studies are complemented by the development of a serious online game on sustainable land management in general that bridges the gap between land use modeling and environmental education. Simulation results of this thesis provide insights into (i) the performance of the politically promoted agricultural management strategies in meeting various intended goals such as poverty alleviation or the maintenance of biodiversity and ecosystem services, (ii) the emergence of unintended (environmental and social) side effects such as land use conflicts, land degradation or cost explosion and (iii) the mitigation of such side effects by appropriately adjusting the design of the policy options. These insights are enabled by representing temporal as well as spatial variability in the developed models. Furthermore, different mechanistic approaches of transferability analyses based on stylized landscapes are developed and applied. They enable to check whether and in what respect policy impacts actually differ substantially between regional contexts, to identify what regional factors steer the impact and to derive indicators for grouping regions of similar policy impacts. Finally, based on a conducted survey-based evaluation and experiences from various applications, the value of the developed serious game for environmental education is revealed and discussed.Altogether, this thesis contributes to model-based decision support for steering transformation towards the sustainable development of land systems in an appropriate way. This is done by developing appropriate social-ecological modeling approaches, by performing specific policy impact analyses in two transformative agricultural systems using these models and by providing a model-based communication tool for environmental education.

La presente investigación se realizó para evaluar el desempeño estructural y funcional del sistema de evacuación, de un edificio educativo superior durante un sismo severo, en atención a lo cual, se analizó mediante el método basado en Agent Based Modelling y Análisis Tiempo-Historia no Lineal. No obstante, el análisis no se limita solo a edificaciones esenciales; se puede aplicar para edificios importantes y comunes que concentran gran cantidad de personas, ya que el lineamiento que se plantea en esta tesis busca una alternativa más que se debe tener en cuenta en los proyectos de la construcción civil. La información estructural y geotécnica del edificio en estudio, se recopila y se introduce en una base de datos para su análisis. Se realiza un procedimiento similar para la información relacionada de los ocupantes. Usando estas informaciones: a) Se determinará la fragilidad estructural y el colapso localizado, b) se establecerá la interacción de la persona con el colapso focalizado. Para el primer aspecto, se utilizará el historial de tiempo no lineal; para el segundo, el modelado basado en agentes se empleará para recrear la reacción de las personas que enfrentan el micro colapso. Los resultados importantes de estas evaluaciones son: 1) Se ha localizado vigas, columnas y muros de corte colapsadas que afectan la evacuación; 2) Se ha ubicado de cuellos de botella, donde presentan gran concentración de personas durante la evacuación; y 3) se ha cuantificado a las personas afectadas, en términos de individuos atrapadas en el edificio que no pudieron evacuar. / The present investigation was carried out to evaluate the structural and functional performance of the evacuation system of a high-rise higher education building during a severe earthquake, which was analyzed using the Agent Based Modeling and Non-Linear Time-History Analysis method. However, the analysis is not limited only to essential buildings; it can be applied to important and common buildings that concentrate a large number of people, such as: Health establishments, airports, shopping centers, stadiums, condominiums, etc., since the guideline proposed in this thesis seeks one more alternative to be taken into account in civil construction projects. The structural and geotechnical information of the building under study is compiled and entered into a database for analysis. A similar procedure is performed for the related occupant information. Using this information: a) the structural fragility and localized collapse will be determined, b) the interaction of the person with the focused collapse will be established. For the first aspect, nonlinear time history will be used; for the second, agent-based modeling will be used to recreate the reaction of people facing the micro collapse. The important results of these evaluations are: 1) collapsed beams, columns and shear walls have been located, which make evacuation routes inoperable; 2) bottleneck areas have been located, where they present high concentration of people during evacuation; and 3) affected people have been quantified, in terms of individuals trapped in the building who could not evacuate. / Tesis

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<p dir="ltr">Tuberculosis (TB) remains a global public health crisis, causing over 10 million new infections and 1.3 million deaths in 2022 alone. TB is caused by <i>Mycobacterium tuberculosis </i>(<i>Mtb</i>), which initiates heterogeneous pathology in the lungs, including granulomas and cavities. Granulomas are organized structures of immune cells, traditionally thought to contain bacteria. Cavities are pathological spaces caused by the destruction of extracellular matrix (ECM), which can worsen disease outcomes and cause long-lasting pulmonary impairment.<i> In vitro </i>methods are commonly used to study host-pathogen interactions in <i>Mtb</i> infection, and recent developments have led to models that represent the TB granuloma environment more closely than traditional cell culture. These advances include the development of 3D models and the inclusion of physiological ECM components like collagen. Increasing complexity has been accomplished in a piece-wise manner – minimally necessary components are included to minimize cost while maintaining throughput and tractability. This creates a need for tools to analyze these systems and, more importantly, integrate the independent data created. We developed an agent-based model to characterize multiple <i>in vitro</i> models of TB and apply it to 1) separate the contributions of dimension and structure to bacterial control in granuloma-like spheroids and 2) explore how the interactions of collagen and matrix metalloproteinases (MMP) contribute to clinically relevant outputs such as bacterial load and ECM destruction. The model provides insights into the role of granuloma structure and the conflicting results of MMP inhibition, generating new hypotheses to be tested in tandem with <i>in vitro</i> models.</p>