DOI: 10.6084/m9.figshare.28095128.v1
title: <b>Beyond absolute space: Modeling disease dispersion and reactive actions from a multi-spatialization perspective</b>

description: <b>Overview</b>This document provides instructions on how to use the data and code associated with the manuscript titled “<b>Beyond absolute space: Modeling disease dispersion and reactive actions from a </b><b>multi-spatialization perspective</b>”. The following sections will guide you through the setup, data structure, code execution, expected output, and any additional notes necessary for reproducing the results presented in the manuscript.<b>Table of Contents</b>· Requirements· Data files· Code structure· Running the code· Expected Output· Troubleshooting==========================================================RequirementsOperating system· Windows 7 or higher (recommended)· UbuntuSoftware· Python (version 2.7 or higher) or Jupyter NotebookRequired libraries: numpy, pandas, scipy, matplotlib, pgmpyData filesSurvey_data_processed_Anonymized.csvProtectiveAction_Anonymized.csvThese two data files have been pre-processed from the raw survey data to support the Python code for generating Figures 3, 4, 5, and 6. To protect the privacy and confidentiality of human research participants, all personal information has been excluded in the pre-processing.The data files include anonymized individual record IDs, self-reported weekly symptoms (for themselves and others), protective actions taken, and the service places they visited each week (20 types). The data files also include information regarding the daily volume of visits and the presence of infectious visitors at the 20 types of service places.Code structure· <i>/ Firstlayer_ModifyandUpload.ipynb</i>This is the code file for the first layer of the Bayesian network analysis and SHAP analysis.· <i>/</i><i> </i><i>SecondLayerProtectiveAction.ipynb</i>This is the code file for the second layer of the Bayesian network analysis and SHAP analysis.Running the Code· To run the Python code (preferably in Jupyter Notebook), ensure that all dependencies are installed by running: <i>pip install pandas pgmpy</i>. These dependencies are specified at the beginning of the file.Expected Output· Running the provided Python script will generate the specified figures below. Note that the labels and axis text of the figures are adjusted in the manuscript for readability and to ensure consistency with the manuscript.<i>Firstlayer_ModifyandUpload.ipynb</i>· <b>Figure 3 – Generated in the script (Cell 3, line 85).</b><b>· Figure 4 – Generated in the script (Cell 4, line 101).</b><i>SecondLayerProtectiveAction.ipynb</i>· <b>Figure5 – Generated in the script (Cell 3, line 65).</b><b>· Figure 6 – Generated in the script (line 150). Part of the Figure 5 was generated in ArcGIS Pro.</b>Note:· <b>Table 1 is created directly in Microsoft PowerPoint. Refer to Figures & Table.pptx.</b><b>· Figures 1 and 2 is created directly in Microsoft PowerPoint. Refer to Figures & Table.pptx.</b>TroubleshootingIf you encounter issues while running the script, check the following:· Missing Data Files: Ensure all required data files are in the same directory as the script or that the correct file paths are specified.· Library/Package Errors: Ensure that all necessary libraries and packages are installed. Use pip install as needed.