Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

How accurate are WorldPop-Global-Unconstrained gridded population data at the cell-level?: A simulation analysis in urban Namibia

Version 1 : Received: 22 February 2021 / Approved: 22 February 2021 / Online: 22 February 2021 (15:36:31 CET)
Version 2 : Received: 14 May 2021 / Approved: 17 May 2021 / Online: 17 May 2021 (15:54:59 CEST)

How to cite: Thomson, D.R.; Leasure, D.R.; Bird, T.; Tzavidis, N.; Tatem, A.J. How accurate are WorldPop-Global-Unconstrained gridded population data at the cell-level?: A simulation analysis in urban Namibia. Preprints 2021, 2021020492 (doi: 10.20944/preprints202102.0492.v2). Thomson, D.R.; Leasure, D.R.; Bird, T.; Tzavidis, N.; Tatem, A.J. How accurate are WorldPop-Global-Unconstrained gridded population data at the cell-level?: A simulation analysis in urban Namibia. Preprints 2021, 2021020492 (doi: 10.20944/preprints202102.0492.v2).

Abstract

Disaggregated population counts are needed to calculate health, economic, and development indicators in Low- and Middle-Income Countries (LMICs), especially in settings of rapid urbanisation. Censuses are often outdated and inaccurate in LMIC settings, and rarely disaggregated at fine geographic scale. Modelled gridded population datasets derived from census data have become widely used by development researchers and practitioners. These datasets are evaluated for accuracy at the spatial scale of the input data which is often much courser (e.g. administrative units) than the neighbourhood or cell-level scale of many applications. We simulate a realistic "true" 2016 population in Khomas, Namibia, a majority urban region, and introduce realistic levels of outdatedness (over 15 years) and inaccuracy in slum, non-slum, and rural areas. We aggregate these simulated realistic populations by census and administrative boundaries (to mimic census data), and generate 32 gridded population datasets that are typical of a LMIC setting using WorldPop-Global-Unconstrained gridded population approach. We evaluate the cell-level accuracy of these simulated datasets using the original "true" population as a reference. In our simulation, we found large cell-level errors, particularly in slum cells, driven by the use of average population densities in large areal units to determine cell-level population densities. Age, accuracy, and aggregation of the input data also played a role in these errors. We suggest incorporating finer-scale training data into gridded population models generally, and WorldPop-Global-Unconstrained in particular (e.g., from routine household surveys or slum community population counts), and use of new building footprint datasets as a covariate to improve cell-level accuracy. It is important to measure accuracy of gridded population datasets at spatial scales more consistent with how the data are being applied, especially if they are to be used for monitoring key development indicators at neighbourhood scales with relevance to small dense deprived areas within larger administrative units.

Subject Areas

LMIC; Global South; indicator; Random Forrest

Comments (1)

Comment 1
Received: 17 May 2021
Commenter: Dana Thomson
Commenter's Conflict of Interests: Author
Comment: (1) Specification that the analysis only applies to WorldPop
(2) Global-Unconstrained models- Statistics are reported by slum, non-slum, and rural areas (instead of just urban/rural)
(3) Inclusion of population-adjusted statistics
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