Discrete dynamics of contagious social diseases: Example of obesity

Abstract

Modeling contagious diseases needs to incorporate information about social networks through which the disease spreads as well as data about demographic and genetic changes in the susceptible population. In this paper, we propose a theoretical framework (conceptualization and formalization) which seeks to model obesity as a process of transformation of one's own body determined by individual (physical and psychological), inter-individual (relational, i.e., relative to the relationship between the individual and others) and socio-cultural (environmental, i.e., relative to the relationship between the individual and his milieu) factors. Individual and inter-individual factors are tied to each other in a socio-cultural context whose impact is notably related to the visibility of anybody being exposed on the public stage in a non-contingent way. The question we are dealing with in this article is whether such kind of social diseases, i.e., depending upon socio-environmental exposure, can be considered as "contagious". In other words, can obesity be propagated from individual to individual or from environmental sources throughout an entire population?

Estimation of Daily Reproduction Numbers during the COVID-19 Outbreak

“…The third challenge is the estimation of the daily reproduction number over the contagiousness period, which was precisely the topic of the present paper. A fourth interesting challenge for this community is the extension of the methods developed in the present paper to the contagious non-infectious diseases (i.e., without causal infectious agent), such as social contagious diseases [59][60][61], the best example being that of the pandemic linked to obesity, for which many concepts and modelling methods remain available.…”

SI epidemic model applied to COVID-19 data in mainland China

“…Another interesting prospect is the extension of methods developed in the present paper to the contagious non-infectious diseases (i.e. without causal infectious agent), such as social contagious diseases, the best example being that of the pandemic linked to obesity [29][30][31], for which many concepts and modelling methods remain available.…”

Phase transitions in stochastic non-linear threshold Boolean automata networks on Z2: The boundary impact

“…Since decades, researches in discrete mathematics and fundamental computer science have put the emphasis on the modelling abilities of automata networks concerning interaction networks. In particular, since their introduction in the works of McCulloch and Pitts [31] and Kauffman [29,28], Boolean automata networks (bans for short) have been at the centre of numerous studies in the field of biological networks modelling, like neural networks [20,24,25,21,9,8], genetic regulation networks [30,43,44,41,32,4,36] and more recently social networks [16,12]. This can be easily explained by their very high level of abstraction that makes them ideal objects to capture formally the essence of interactions and to focus on qualitative aspects of their dynamics (e.g., the information transmissions).…”