Carla Taramasco

Evolution of social networks: the example of obesity

The present paper deals with the effect of the social transmission of nutrition habits in a social and biological age-dependent context on obesity, and accordingly on type II diabetes and among its complications, the neurodegenerative diseases. The evolution of social networks and inside a network the healthy weight of a person are depending on the context in which this person has contacts and exchanges concerning his alimentation, physical activity and sedentary habits, inside the dominant social network in which the person lives (e.g., scholar for young, professional for adult, home or institution for elderly people). Three successive steps of evolution will be considered for social networks (like for neural one’s): initial random connectivity, destruction and consolidation of links following a new transition rule called homophilic until an asymptotic architectural organization and configuration of states. The application of such a network dynamics concerns the sequence overweight/obesity/type II diabetes and neurodegenerative diseases.

Random modelling of contagious diseases.

Modelling contagious diseases needs to include a mechanistic knowledge about contacts between hosts and pathogens as specific as possible, e.g., by incorporating in the model information about social networks through which the disease spreads. The unknown part concerning the contact mechanism can be modelled using a stochastic approach. For that purpose, we revisit SIR models by introducing first a microscopic stochastic version of the contacts between individuals of different populations (namely Susceptible, Infective and Recovering), then by adding a random perturbation in the vicinity of the endemic fixed point of the SIR model and eventually by introducing the definition of various types of random social networks. We propose as example of application to contagious diseases the HIV, and we show that a micro-simulation of individual based modelling (IBM) type can reproduce the current stable incidence of the HIV epidemic in a population of HIV-positive men having sex with men (MSM).

Serious Games and Personalization of the Therapeutic Education

Therapeutic education uses currently serious games techniques, to have more impact on persons with a chronic disease at their place of living. This requires to customize the game so that the person attempts to change in his lifestyle and dietary habits, according to the specific advices given at relevant moments by the therapeutic monitoring. Thus, taking better account of alimentary and sedentary own habits, and those of his family or professionnel environment, it is possible to build a personalized educational tool, which evolves according the transformations of the pathotology (toward stabilization or to complication), taking into account an actimetry objectified by sensors, complementing and overlapping the information obtained by subjective reporting declarative procedures of dialogue with the virtual coach, during the game. We take as an example the sequence obesity/type 2 diabetis, which affects between 4% and 10% of older people in most developed and developing countries

Archimedean copula and contagion modeling in epidemiology

The aim of this paper is first to find interactions between compartments of hosts in the Ross-Macdonald Malaria transmission system. So, to make clearer this association we introduce the concordance measure and then the Kendalls tau and Spearmans rho. Moreover, since the population compartments are dependent, we compute their conditional distribution function using the Archimedean copula. Secondly, we get the vector population partition into several dependent parts conditionally to the fecundity and to the transmission parameters and we show that we can divide the vector population by using

Information Design of Biological Networks: Application to Genetic, Immunologic, Metabolic and Social Networks

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From susceptibility to frailty in social networks: The case of obesity

-th quantiles and test the independence between the subpopulations of susceptibles and infecteds. Third, we calculate the

Discrete dynamics of contagious social diseases: Example of obesity.

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Smart Homes and Sensors for Surveillance and Preventive Education at Home: Example of Obesity

-th quantiles with the Poisson distribution. Fourth, we introduce the proportional risk model of Cox in the Ross-Macdonald model with the copula approach to find the relationship between survival functions of compartments.

Serious Game as New Health Telematics Tool for Patient Therapy Education: Example of Obesity and Type 2 Diabetes

The restitution of biological information in the framework of a new discipline, the information design, aims to develop new user-friendly tools for facilitating the comprehension of the medical or biological reality by a polymorphic end-user (patient, physician, or researcher in bioinformatics, biomathematics and life sciences). For that purpose, challenging problems will be presented: i) how to represent in a hierarchical way different components (up trees, strong connected components, down trees, ...) of the biological network interaction graph, ii) how to describe the state dynamics on a network, with both its transient and asymptotic behaviours, iii) how to combine anatomic and functional information about nodes and edges of the interaction graph, and iv) how to take into account the evolutions of the architecture, notably the dynamics about the number of nodes and interaction links, e.g., in case of a rapid demographic change in social networks. Proposal of solutions will be presented for the two first challenges and some issues will be clarified for the two last ones.

Dynalets: A New Representation of Periodic Biological Signals and Spectral Data

ABSTRACT The obesity pandemic is represented by a discrete-time Hopfield Boolean network embedded in continuous-time population dynamics. The influence of the social environment passes through a system of differential equations, whereby obesity spreads by imitation of the most influential neighbors, those who have the highest centrality indices in the network. This property is called “homophily.” Susceptibility and frailty are redefined using network properties. Projections of the spread of obesity are validated on data collected in a French high school.