Data Sheet 1_Prediction of U.S. daily mask wearing and social distancing using psychologically valid agents during three waves of COVID-19.pdf
| Title: | Data Sheet 1_Prediction of U.S. daily mask wearing and social distancing using psychologically valid agents during three waves of COVID-19.pdf |
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| Authors: | Choh Man Teng; Peter Pirolli; Archna Bhatia; Kathleen Carley; Bonnie Dorr; Christian Lebiere; Brodie Mather; Konstantinos Mitsopoulos; Don Morrison; Mark Orr; Tomek Strzalkowski |
| Publication Year: | 2025 |
| Subject Terms: | Epidemiology; cognitive model; COVID-19; decision making; behavior; ACT-R |
| Description: | We present Regional Psychologically Valid Agents (R-PVAs) as a modeling approach to predicting transmission-reducing behaviors and epidemiology. The approach builds upon computational cognitive theory and formalizes aspects of theories of individual-level behavior change. We present R-PVA models of social distancing and mask wearing in response to dynamics in the physical and information environments in the 50 U.S. states. The models achieve strong goodness-of-fits for predicting day-to-day mask-wearing (R 2 = 0.93) and social distancing (R 2 = 0.62) for the first three waves of COVID-19, prior to the rollout of vaccines. |
| Document Type: | dataset |
| Language: | unknown |
| DOI: | 10.3389/fepid.2025.1532553.s001 |
| Availability: | https://doi.org/10.3389/fepid.2025.1532553.s001; https://figshare.com/articles/dataset/Data_Sheet_1_Prediction_of_U_S_daily_mask_wearing_and_social_distancing_using_psychologically_valid_agents_during_three_waves_of_COVID-19_pdf/29062121 |
| Rights: | CC BY 4.0 |
| Accession Number: | edsbas.33AE47CC |
| Database: | BASE |