FuturICT Journal Publications
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Complex social contagion makes networks more vulnerable to disease outbreaks

Social network analysis is now widely used to investigate the dynamics of infectious disease spread from person to person. Vaccination dramatically disrupts the disease transmission process on a contact network, and indeed, sufficiently high vaccination rates can disrupt the process to such an extent that disease transmission on the network is effectively halted. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread through social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model both the health behavior and the infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This variability in dynamics results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks.

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FuturICT: Exploratory of society: L. E. Cederman, R. Conte, D. Helbing, A. Nowak, F. Schweitzer, A. Vespignani

FuturICT: Exploratory of society: L. E. Cederman, R. Conte, D. Helbing, A. Nowak, F. Schweitzer, A. Vespignani | FuturICT Journal Publications | Scoop.it

FuturICT: Exploratory of Society

L. E. Cederman, R. Conte, D. Helbing, A. Nowak, F. Schweitzer, A. Vespignani

Abstract

A huge flow of quantitative social, demographic and behavioral data is becoming available that traces the activities and interactions of individuals, social patterns, transportation infrastructures and travel fluxes. This has caused, together with innovative computational techniques and methods for modeling social actions in hybrid (natural and artificial) societies, a qualitative change in the ways we model socio-technical systems.

 

For the first time, society can be studied in a comprehensive fashion that addresses social and behavioral complexity. In other words we are in the position to envision the development of large data and computational cyber infrastructure defining an exploratory of society that provides quantitative anticipatory, explanatory and scenario analysis capabilities ranging from emerging infectious disease to conflict and crime surges.

 

The goal of the exploratory of society is to provide the basic infrastructure embedding the framework of tools and knowledge needed for the design of forecast/anticipatory/crisis management approaches to socio technical systems, supporting future decision making procedures by accelerating the scientific cycle that goes from data generation to predictions.

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JOURNAL: THE EUROPEAN PHYSICAL JOURNAL SPECIAL TOPICS  Vol. 214 (November II 2012)"Participatory Science and Computing for Our Complex World".

http://epjst.epj.org/index.php?option=com_toc&url=/articles/epjst/abs/2012/14/contents/contents.html

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