Advances in Small Area Population Estimation in the Absence of National Census Data

Population data at small area scales are essential for effective decision-making, affecting public health, disaster response, and resource allocation, amongst other issues. While national censuses remain the foundational source of population data, they may face challenges such as high cost, infrequency, and coverage gaps, which can hinder timely data availability. Geospatial statistical approaches to address these challenges using limited microcensus surveys have been demonstrated, and the field has advanced substantially in recent years, with significant developments in both data sources and modelling methodologies. New approaches now enable the use of routine health intervention campaign data, improved satellite-derived settlement mapping, and novel Bayesian frameworks to produce high-quality small area population estimates where traditional enumeration is difficult or outdated. Various countries are increasingly applying these techniques to support census operations, health program planning, and humanitarian response. This Perspective reviews recent advances in ‘bottom-up’ population mapping approaches, highlighting innovations in input data, statistical methods, and validation techniques. We examine ongoing challenges, including partial observation of buildings under forest canopies, population displacement detection, and institutional adoption. Finally, we discuss emerging opportunities to enhance these approaches through better integration with traditional data systems, capacity strengthening and co-production with national institutions, often facilitated by UN organisations, such as United Nations Population Fund (UNFPA), and the use of novel data streams to develop more timely, accurate, and useful small area population estimates for planning and humanitarian purposes.