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marjoleinbruijning/covid19-burden-madagascar

Domain:

geospatial

Record type:

project
Creator:
mar
Host:
Mapping the expected burden of Covid-19 in Africa. Spatial estimates of burden by age cfrs for Africa ================ 4/1/2020 --- This project is aimed at projecting and mapping the expected Covid-19 burden in Africa, based on population age distributions. For a similar project focusing on the USA, see this page . For an interactive tool of our project, see here . --- ## Table of Contents * Analysis * Data sources * Calculations * Output Files * Code * Preliminary results * Next Steps * Session Info --- ## Analysis ### Data We use two sources of data from WorldPop: - Africa Continental (@ 1x1 km distribution) - 0 - 65 in 5 year intervals, 65+ is one age group - Country level (\~ 100m resolution)\] - 0 - 1, 1 - 80 in 5 year intervals, 80+ is one age group - If you want to download data for another country, you can use the `wp_age.sh` bash script included here. From your working directory: bash wp_age.sh {output directory} {isocode} {yr} For example: `bash wp_age.sh mada_age MDG 2020` - You will need to have GNU `parallel` and `curl` installed, to use this script. - Then edit the script R/mada\_1x1.R with the new directories & iso code - A table of country iso codes is included here - Shapefiles from malariaAtlas using the R package - I used rmapshaper to simplify polygons for easier plotting (except for admin3 which was too big\!) - The continental shapefiles are a bit patchy and you end up with some invalid geoms **Spatial files and other large files are stored on dropbox\!** - Download here --- ### Calculations For both Madagascar @ \~ 1x1 km scale and AFR at \~ 10 km scale: 1. Aggregate rasters up to make them easier to work with 2. Add male and female populations in each age group 3. Match to admin codes (country iso code, admin 1 - 3) from MalariaAtlas shapefiles 4. Apply cfrs across age groups --- ### Output files These data (zipped csv files) with cell\_id corresponding to raster & admin codes corresponding to shapefiles: - Africa gridded @ 10x10 km: output/afr\_dt.gz - Mada gridded @ 1 …

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