Modeling Infection with Multi-agent Dynamics

Details Modeling Infection with Multi-agent Dynamics Modeling Infection with Multi-agent Dynamics

2012-04-01

arxiv.org/abs/1204.0168v1

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Scientific paper

10.1007/978-3-642-29047-3_21

Developing the ability to comprehensively study infections in small populations enables us to improve epidemic models and better advise individuals about potential risks to their health. We currently have a limited understanding of how infections spread within a small population because it has been difficult to closely track an infection within a complete community. The paper presents data closely tracking the spread of an infection centered on a student dormitory, collected by leveraging the residents' use of cellular phones. The data are based on daily symptom surveys taken over a period of four months and proximity tracking through cellular phones. We demonstrate that using a Bayesian, discrete-time multi-agent model of infection to model real-world symptom reports and proximity tracking records gives us important insights about infec-tions in small populations.

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