Small area population forecasting using geospatial big datasets and national census in low and middle income countries

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Africa's population is forecasted to double over the next 40 years, contributing to a high rate ofurbanisation, and as a consequence, this trigger environmental, social-economic and health variations.Small geographic area details are crucial to plan and be abreast of these changes. Despite theirimportance, small area forecasts remain under-explored which limit the potential of low and middlecountries including Namibia to apply evidence-based solutions. Primary data sources for small areaforecasts include population and housing censuses, surveys and administrative data. Although thecensus provides a full count of the population as well as data on fertility, mortality and migration, theseoperations are usually done only every ten years. National statistics offices typically generate projectionsto produce inter-censual estimates; however, these are done at very coarse spatial scales. Hence,making it challenging to capture demographic trends and patterns at finer geographic scales, especiallythrough migration. Mapping from satellites can capture the geographically uneven population growththat is often difficult to predict and account for using standard projection models (Wardrop et al., 2018).Likewise, mobile phone data offer opportunities to capture seasonal variation over time and space inmigration patterns. I am proposing a study that aims to assess how geospatial metrics can improve theaccuracy of population projection models. The study will explore different projection methods withcensus 2011 as a baseline and use top-down models to disaggregate to small areas, and results will bevalidated against 2021 Census data to identify the best estimates.