Modelling disease outbreaks in realistic urban social networks

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dc.contributor.authorEubank, Stephen
dc.contributor.authorGuclu, Hasan
dc.contributor.authorKumar, V.S. Anil
dc.contributor.authorMarathe, Madhav
dc.contributor.authorSrinivasan, Aravind
dc.contributor.authorToroczkai, Zoltan
dc.contributor.authorWant, Nan
dc.date.accessioned2019-08-14T15:01:57Z
dc.date.available2019-08-14T15:01:57Z
dc.date.issued2004
dc.description.abstractHere we present a highly resolved agent-based simulation tool (EpiSims), which combines realistic estimates of population mobility,based on census and land-use data, with parameterized models for simulating the progress of a disease within a host and of transmission between hosts10. The simulation generates a largescale,dynamic contact graph that replaces the differential equations of the classic approach. EpiSims is based on the Transportation Analysis and Simulation System (TRANSIMS) developed at Los Alamos National Laboratory, which produces estimates of social networks based on the assumption that the transportation infrastructure constrains people’s choices about where and when to perform activities11. TRANSIMS creates a synthetic population endowed with demographics such as age and income, consistent with joint distributions in census data. It then estimates positions and activities of all travellers on a second-by-second basis. For more information on TRANSIMS and its availability, see Supplementary Information. The resulting social network is the best extant estimate of the physical contact patterns among large groups of people—alternative methodologies are limited to physical contacts among hundreds of people or non-physical contacts (such as e-mail or citations) among large groups.
dc.description.urihttp://www.nature.com/nature/journal/v429/n6988/full/nature02541.html
dc.identifierhttps://doi.org/10.13016/re70-ehoq
dc.identifier.citationEubank, Stephen and Guclu, Hasan and Kumar, V.S. Anil and Marathe, Madhav and Srinivasan, Aravind and Toroczkai, Zoltan and Want, Nan (2004) Modelling disease outbreaks in realistic urban social networks. Nature, 429 (6988). pp. 180-183.
dc.identifier.otherEprint ID 1293
dc.identifier.urihttp://hdl.handle.net/1903/23117
dc.subjectPublic Health
dc.subjectResearch
dc.subjectRisk Management
dc.subjectInstructional Tools & Models
dc.subjectAgent-based Models
dc.titleModelling disease outbreaks in realistic urban social networks
dc.typeArticle

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