Synthetic Population for Virginia, US (ver. 2.4.0)

Version 1.1

Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2024, "Synthetic Population for Virginia, US (ver. 2.4.0)", https://doi.org/10.18130/V3/5LSDCY, University of Virginia Dataverse, V1

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Other Location for Dataset	net.science: https://net.science/files/dec1520f-d285-4ecf-b9c9-2fc6114a879b/
Dataset Description	The synthetic population for the state of Virginia is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (HISP). The population includes people and households with demographic characteristics along with residential locations and general activity locations at parcel-level resolution and accuracy. All individuals are assigned activity sequences and activity locations through statistical matching methods. Finally, a contact network is constructed. The precise way in which this is done depends on the intended scenario. Here the target application is epidemic spread of influenza-like diseases, and the construction of the network is done at each location through a modified Erdos-Renyi random graph.
Subject	Medicine, Health and Life Sciences; Computer and Information Science; Mathematical Sciences; Social Sciences
License/Data Use Agreement	CC BY 4.0


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Citation Metadata

Persistent Identifier	doi:10.18130/V3/5LSDCY
Publication Date	2024-03-19
Title	Synthetic Population for Virginia, US (ver. 2.4.0)
Other Location for Dataset	net.science: https://net.science/files/dec1520f-d285-4ecf-b9c9-2fc6114a879b/
Author	Mortveit, Henning S. (Biocomplexity Institute and Initiative, University of Virginia) Adiga, Abhijin (Biocomplexity Institute and Initiative, University of Virginia) Baek, Hannah (Biocomplexity Institute and Initiative, University of Virginia) Bhattacharya, Parantapa (Biocomplexity Institute and Initiative, University of Virginia) Eubank, Stephen (Biocomplexity Institute and Initiative, University of Virginia) Machi, Dustin Marathe, Madhav (Biocomplexity Institute and Initiative, University of Virginia) Porebski, Przemyslaw (Biocomplexity Institute and Initiative, University of Virginia) Swarup, Samarth (Biocomplexity Institute and Initiative, University of Virginia) Venkatramanan, Srinivasan (Biocomplexity Institute and Initiative, University of Virginia) Wilson, Mandy (Biocomplexity Institute and Initiative, University of Virginia) Xie, Dawen (Biocomplexity Institute and Initiative, University of Virginia)
Point of Contact	Use email button above to contact. Mortveit, Henning S. (Biocomplexity Institute and Initiative, University of Virginia)
Dataset Description	The synthetic population for the state of Virginia is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (HISP). The population includes people and households with demographic characteristics along with residential locations and general activity locations at parcel-level resolution and accuracy. All individuals are assigned activity sequences and activity locations through statistical matching methods. Finally, a contact network is constructed. The precise way in which this is done depends on the intended scenario. Here the target application is epidemic spread of influenza-like diseases, and the construction of the network is done at each location through a modified Erdos-Renyi random graph.
Subject	Medicine, Health and Life Sciences; Computer and Information Science; Mathematical Sciences; Social Sciences
Data Creation Date	2023-03-01
Depositor	Porebski, Przemyslaw
Deposit Date	2024-03-19

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