High resolution national population mapping: Bottom-up population estimation modelling
Description
Background
Gridded population estimates are particularly useful as they provide decision-makers and data users with the flexibility to aggregate population estimates into different spatial units in existing enumeration areas or custom areas. They can be aggregated over various levels of administrative units, but also over areal units that don't follow administrative boundaries, such as a hospital catchment area, enabling integration and analyses with a range of other spatial datasets that are not possible using standard census counts mapped to administrative boundaries. The modelled datasets do not however replace the need for a full census, which usually includes a more precise collection of demographics and socioeconomics, as well as a housing census.
WorldPop produces a range of different gridded population estimate datasets and tools, and choosing the best to use depends on your needs and situation. Where little recent population enumeration data exist for a country and timely estimates that account for recent demographic changes are required, the 'bottom-up' approach is likely to provide more accurate estimates. This differs from the 'top-down' approach, and differences are outlined here: https://www.worldpop.org/methods/populations/, as well as in the documents provided in this work package. In brief, sample data from as many trustworthy and recent survey datasets as possible are used with detailed geospatial datasets to build a statistical model to estimate population numbers and age/sex breakdowns in unsampled locations, together with measurements of uncertainty. This approach can also be used to fill gaps in a census where full enumeration is not possible due to conflict, poor access or financial limitations. An introductory video on bottom-up population modelling can be found here: https://www.worldpop.org/methods/population-estimation-for-sustainable-development/.
Advantages of 'bottom-up' modelled population estimates:
-More accurate outputs than top-down approaches where census data are outdated and/or census projections from these are highly uncertain
-Measurement and mapping of uncertainty highlights where caution in using the data should be exercised and where further data collection could be prioritised
Disadvantages of 'bottom-up' modelled population estimates:
-Tailored modelling to the country of interest takes effort and often engagement with governments, which can be slow
-Typically estimates are tied to a single year
The Work Package
This work package consists of a set of reports, papers, videos, tutorials, tools and datasets to provide users with a comprehensive introduction to 'bottom-up' population estimation modelling. This includes (i) An overview document on the value of modelled population estimates for census support, (ii) academic papers reviewing and providing an overview of population modelling methods, (iii) links to modelled datasets and metadata on the WorldPop Open Population Repository (WOPR), (iv) link to a tool for interacting with the modelled population estimates (WOPRVision), (vi) academic papers documenting the models for Nigeria, DR Congo and Burkina Faso, (vii) a tutorial introducing users to bottom-up Bayesian population modelling methods and examples.