Reyna Lara, Adriana
Gómez Gardeñes, Jesús (dir.)
Universidad de Zaragoza,
2022
Resumen: Nuestro mundo cada vez más interconectado permite que las enfermedades transmisibles se propaguen rápidamente a escala mundial con una facilidad sin precedentes. A medida que crecen las poblaciones, se acelera la urbanización, se intensifica el cambio climático y aumenta la movilidad, se crea un nuevo y complejo campo de batalla en la lucha contra la aparición de nuevos y viejos patógenos zoonóticos. Para enfrentar, o incluso anticipar, nuevos brotes epidémicos, debemos responder cómo, cuándo, dónde y qué estrategias de prevención y control se deben implementar.
La cantidad cada vez mayor de datos sobre las interacciones humanas, desde los patrones de movilidad humana diaria hasta las interacciones cara a cara, nos brinda la posibilidad de comprender las vías de propagación de enfermedades contagiosas. Es posible crear modelos basados en datos que nos permitan estudiar y predecir escenarios estadísticos de propagación de epidemias en diferentes circunstancias. En esta tesis, basados en la física de los sistemas complejos, mejoramos nuestra comprensión de la modelización de epidemias integrando sistemas de control en la dinámica. Estudiamos las interdependencias entre la estructura de las redes de interacción humana y su funcionalidad para propagar enfermedades infecciosas mientras integramos estrategias de control en la dinámica.
Resumen (otro idioma): Our increasingly interconnected world allows communicable diseases to spread rapidly on a global scale with unprecedented ease. As populations grow, urbanization accelerates, climate change intensifies, and mobility increases, a new and complex battlefield is created in the fight against the emergence of new and old zoonotic pathogens. To face, or even anticipate new epidemic outbreaks, we must answer how, when, where, and which prevention and control strategies should be implemented. The ever-increasing amount of data on human interactions, from daily human mobility patterns to face-to-face interactions, gives us the possibility to understand the pathways of contagious disease spread. It is possible to create data-driven models that allow us to study and predict statistical scenarios of the spread of epidemics under different circumstances. In this thesis, based on the physics of complex systems, we improve our understanding of epidemic modeling by integrating control systems into the dynamics. We study the interdependencies between the structure of human interaction networks and their functionality to spread infectious diseases while integrating control strategies into the dynamics. We address three different problems at different scales: 1) we study the effects of contact tracing in static contact networks, we found the microscopic and macroscopic effects that make this control strategy efficient; 2) we study vector-borne diseases in large geographical areas, and we found the regional vulnerability factor and then construct an efficient immunization ranking; 3) we formulate an adaptive multiscale control of mobility policy in large geographical areas, this model aims to help the health and socioeconomic systems, we found that the combination of restrictions to the mobility and restrictive creation of social bubbles would be for the benefit of both systems.
La cantidad cada vez mayor de datos sobre las interacciones humanas, desde los patrones de movilidad humana diaria hasta las interacciones cara a cara, nos brinda la posibilidad de comprender las vías de propagación de enfermedades contagiosas. Es posible crear modelos basados en datos que nos permitan estudiar y predecir escenarios estadísticos de propagación de epidemias en diferentes circunstancias. En esta tesis, basados en la física de los sistemas complejos, mejoramos nuestra comprensión de la modelización de epidemias integrando sistemas de control en la dinámica. Estudiamos las interdependencias entre la estructura de las redes de interacción humana y su funcionalidad para propagar enfermedades infecciosas mientras integramos estrategias de control en la dinámica.
Resumen (otro idioma): Our increasingly interconnected world allows communicable diseases to spread rapidly on a global scale with unprecedented ease. As populations grow, urbanization accelerates, climate change intensifies, and mobility increases, a new and complex battlefield is created in the fight against the emergence of new and old zoonotic pathogens. To face, or even anticipate new epidemic outbreaks, we must answer how, when, where, and which prevention and control strategies should be implemented. The ever-increasing amount of data on human interactions, from daily human mobility patterns to face-to-face interactions, gives us the possibility to understand the pathways of contagious disease spread. It is possible to create data-driven models that allow us to study and predict statistical scenarios of the spread of epidemics under different circumstances. In this thesis, based on the physics of complex systems, we improve our understanding of epidemic modeling by integrating control systems into the dynamics. We study the interdependencies between the structure of human interaction networks and their functionality to spread infectious diseases while integrating control strategies into the dynamics. We address three different problems at different scales: 1) we study the effects of contact tracing in static contact networks, we found the microscopic and macroscopic effects that make this control strategy efficient; 2) we study vector-borne diseases in large geographical areas, and we found the regional vulnerability factor and then construct an efficient immunization ranking; 3) we formulate an adaptive multiscale control of mobility policy in large geographical areas, this model aims to help the health and socioeconomic systems, we found that the combination of restrictions to the mobility and restrictive creation of social bubbles would be for the benefit of both systems.
Pal. clave: fisica ; estadistica ; epidemiologia ; dinamica de poblaciones
Titulación: Programa de Doctorado en Física
Plan(es): Plan 488
Nota: Presentado: 11 11 2022
Nota: Tesis-Univ. Zaragoza, , 2022
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