4 Determining who is at risk

!UNDER CONSTRUCTION!

Aggregating exposure estimates to survey statistical regions

The population count in each group is aggregated to the spatial units defined by the statistical boundary data. As described above, these spatial units correspond with geographic regions that have representative survey data and vary in size and population across countries. For partially covered grid cells, the population count is weighted by the fraction of the grid cell covered by the statistical region. The results can be summarized in a tabular format providing the estimated population by rural, exposure and accessibility status, for each statisti-cal region. All spatial data are processed and analyzed using R Statistical Software (R Core Team, 2023).

Aligning rural and urban classifications

Calculating the risk indicator

The total number exposed is multiplied by the share households deprived in that administrative unit to deter-mine the number of people who are both exposed and vulnerable in that unit. This is then summed by country, region and globally to provide country, regional and global numbers on exposed and vulnerable. Implicitly, a uniform rate of vulnerability is assumed within each GSAP statistical area.

The number of people at risk to climate related hazards counts people exposed to at least one climate hazard and deprived on at least one dimension of vulnerability. All calculations, random assignment, and aggregation are processed and analyzed using Stata.