Data Extraction for Dashboard creation - worldbank/HNP GitHub Wiki

I collaboration with our colleagues, we are going to extract data for the public facing dashboards on a country basis. The data are produced in three sets, geometry files, stats files, and tiff files:

GEOMETRY Package

  • adm0.geojson – primary key is WB_ADM0_CO.
  • adm1.geojson – primary key is WB_ADM0_C1.
  • adm2.geojson – primary key is WB_ADM0_C2.
  • urban_areas_hd.geojson – primary key is geohash (represents the geohash of the centroid)
    • HD_URBAN_###.geojson – primary key is geohash (represents the geohash of the centroid). The ### in the filename is linked to the ID field in urban_areas_hd

For all of these scales, we will attempt to attribute the following values - each country will use best available data, and will document its source; however, not all data will be available for all countries:

  • Comorbidity: multiply DHS results from StatCompiler (or better data when available) through WorldPop to summarize total population in each feature, and average rate.
  • Population by age: summarize WorldPop demographics
  • Healthcare system capacity: ???
  • Mobility data: Aivin has calculated mobility statistics at the fishnet level, then Keith applied temporal statistics to generated singular metrics.
  • Hotspots - this will focus on the building height and population density metrics developed within the World Bank

STATS Package

The statistics in the stats currently come in two forms, BASE and DHS.

Base stats

  • R10_SUM – total population (from WorldPop)
  • P1_SUM – urban population
  • P2_SUM – vulnerable population (based on hospitalization and demographics)
  • LC_## - pixel counts of landcover class. The numbers come from Globcover 2015, and the numbers are described in the Globcover legend, p.19

DHS

Columns have clear column names. Numbers are derived by multiplying the DHS numbers through the WorldPop data and then summarized by region through zonal stats

github.com/worldbank/HNP/blob/master/tables/RiskSchema.json

TIFF Package

  • LC.tif - Globcover 2015: Globcover legend, p.19
  • WP_2020_1km.tif - WorldPop modelled population at 1km resolution for 2020.
  • WP_2020_1km_urban_pop.tif - WorldPop above clipped to the urban extents generated according to population density and total population thresholds.
  • WP2020_vulnerability_map.tif - Vulnerable population achieved through WorldPop demographic information and CoVID hospitalization rates