A statistical network analysis of the HIV/AIDS epidemics in Cuba
Résumé
The Cuban contact-tracing detection system set up since 1986 made the collection of detailed epidemic data at the individual level possible. In this study, we reconstructed the related network counting 5389 vertices and 4073 edges and analysed its structure by means of recent developments in the field of graph theory, shedding light onto a variety of mechanisms underlying the spread of the disease and the role of contact-tracing. In particular, degree distributions, clustering/assortativity coefficients and path lengths were statistically measured. Because of the size of the graph (with a giant component of 2386 nodes and 3168 edges), basic graph representations failed to provide a clear view of the network structure. Clustering based on modularity optimization was implemented to detect community structures and obtain a better visualization and understanding of the social network, in combination to the study of the other covariates. It showed that the graph has a heterogeneous density, globally low, with some clusters of high intra-connectivity and lowly connected to the outside however. Though descriptive, the results presented in this article pave the way for properly incorporating heterogeneity and structure in the dynamics of stochastic SIR epidemic models taking place on the underlying social network.
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