10.18130/V3/PNGMRJMortveit, Henning S.Henning S.MortveitBiocomplexity Institute and Initiative, University of VirginiaAdiga, AbhijinAbhijinAdigaBiocomplexity Institute and Initiative, University of VirginiaBaek, HannahHannahBaekBiocomplexity Institute and Initiative, University of VirginiaBhattacharya, ParantapaParantapaBhattacharyaBiocomplexity Institute and Initiative, University of VirginiaEubank, StephenStephenEubankBiocomplexity Institute and Initiative, University of VirginiaMachi, DustinDustinMachiBiocomplexity Institute and Initiative, University of VirginiaMarathe, MadhavMadhavMaratheBiocomplexity Institute and Initiative, University of VirginiaPorebski, PrzemyslawPrzemyslawPorebskiBiocomplexity Institute and Initiative, University of VirginiaSwarup, SamarthSamarthSwarupBiocomplexity Institute and Initiative, University of VirginiaVenkatramanan, SrinivasanSrinivasanVenkatramananBiocomplexity Institute and Initiative, University of VirginiaWilson, MandyMandyWilsonBiocomplexity Institute and Initiative, University of VirginiaXie, DawenDawenXieBiocomplexity Institute and Initiative, University of VirginiaUniversity of Virginia Dataverse2024Computer and Information ScienceMathematical SciencesMedicine, Health and Life SciencesSocial SciencesMortveit, Henning S.Henning S.MortveitBiocomplexity Institute and Initiative, University of Virginia2023-03-012026-08-28https://net.science/files/57f3a977-aab9-4886-92fc-b9c0b4aabad8975337181056620683233652826766652187568521572607363004832225571403458242162243135239507511631634140text/tab-separated-valuesapplication/pdfapplication/x-xzapplication/x-xzapplication/x-xzapplication/x-xzapplication/x-xzapplication/x-xzapplication/x-xzapplication/x-gzipapplication/x-xzapplication/x-xzapplication/x-xz3.0CC BY 4.0The synthetic population for the state of Washington 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.