Modeling Infection with Multi-agent Dynamics
Year: 2012
Type: article
Study design: Observational Study
Abstract: . Developing the ability to comprehensively study infections in small populations enables us to improve epidemic models and better advise individu-als about potential risks to their health. We currently have a limited understand-ing of how infections spread within a small population because it has been dif-ficult 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 da-ta are based on daily symptom surveys taken over a period of four months and proximity tracking through cellular phones. We demonstrate that using a Baye-sian, 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.
Authors: Wen Dong, Katherine Heller, Y Pentl
Institutions: MIT Media Lab, Massachusetts Institute of Technology
Language: English
Subfield: Applied Mathematics
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3122724921