Data for A spatio-temporal framework for a location centric response to COVID-19 risk management with social sensitivity

Published: 16-03-2021| Version 1 | DOI: 10.17632/89yv2dgyxx.1
Ibrahim Niankara


This zipped data file contains R formatted Data and Meta-data used in the research project titled: "A spatio-temporal framework for a location centric response to COVID-19 risk management with social sensitivity". the file is organized in two sub-folders: *The first folder named "Econometric Estimation data and Codes" contains all data for the implemented econometric model estimations, along with the numerical descriptive statistics. *The second folder named "Indices Data and Spatial Visualization Codes" contains the data for creating the two novel indices capturing society's preferences for Covid-19 risk mitigation measures across various sub-national jurisdictions and overtime; along with spatial meta-data for their mapping and visualization.


Steps to reproduce

Together the full zipped data file, pool together information from three sources: * The "2020 World Bank High Frequency Phone Survey (HFPS)" for evaluating the impact of COVID-19. More specifically, its version implemented in Rounds 1, 3 and 5 in Burkina Faso; and carried out between June 2020 and December 2020. This raw BFA 2020 COVID-19 HFPS data was collected by Burkina Faso's National Institute of Statistics and Demography (INSD), with technical and financial support provided by the World Bank. Rounds 1,3 and 5 of this data source is used to produce the two indices presented in the paper, which provide systematic sub-regional cross-temporal indicators for understanding households' perceptions of the various measures implemented in response to the Covid-19 pandemic in Burkina Faso. (see "R135INDEX in folder: "Indices Data and Spatial Visualization Codes"); additionally, Round 3 information from this data source is also used in conjunction with round 3 derived index measures "to explore the impact of Covid-19 mitigation policy preferences on self-reported preventive behaviors in Burkina Faso" in a cross-sectional Regression Analysis. (see "WBCovDatHH_BF5" in folder "Econometric Estimation data and Codes"). The indices from all three rounds are then aggregated across households' at both the regional level and provincial level and combined with the regional and provincial shape files for Spatio-temporal Descriptive Mapping and Visualization. (see folder: "Econometric Estimation data and Codes"); * Level 1 and level 2 of the (regional and provincial) spatial Meta data ("shape files", with extensions “.sf”) extracted from the "GADM database of Global Administrative Areas” Version 3.6 (released May 6, 2018); and Retrieved March 12, 2019 from These shape files are lists of spatial coordinates (13 regions, and 45 Provinces) of Burkina Faso, which are combined with regional and provincial data aggregates of the "Two Novel Indices", for all Descriptive Mapping and Visualization. (see "regionOutcomeDat1" and "ProvinceOutcomeDat2" in folder: "Indices Data and Spatial Visualization Codes") * Raw regional and provincial ("polynomial files", with extensions “.sp”) also extracted from the GADM database, for subsequent treatment to produce the R Data frames "xtr" and "xtp" (see folder: "Econometric Estimation data and Codes"). which are required in the model specification of the Econometric Analysis (in the form of Spatial Copula Regressions, with Random Regional and Provincial Effects) implemented in the paper.