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Updated: Jan 17, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Reconstructing Somalia's population: A district level analysis
Yamna Ouchtar1, Dahir Abdi Ali2, Yahye Abukar Ahmed3
1Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Abstract:
Somalia has experienced more than 30 years of armed conflict exacerbated by drought and food insecurity, which has led to major migratory flows. Despite these large-scale movements, no census has been carried out since 1975. To support effective planning and service delivery, we reconstructed Somalia's population at district level by taking into account alternative sources of population data, natural growth and known internal and refugee displacement flows.A previous study, published in PLOS Global Public Health, attempted to reconstruct the population of Somalia by district (administrative level 2) on a monthly basis from 2013 to 2022. This initial method was based on the average of available estimates, on the assumption of a fixed rate of natural increase and on the allocation of displaced persons to the various districts. However, it assumed that internally displaced persons (IDPs) would remain in their destination districts indefinitely, leading to unrealistic population declines and inflated IDP numbers. The paper presents an improved reconstruction method using mechanistic and statistical models to overcome these limitations.The updated method incorporates dynamic modelling techniques, reflecting more realistic migration and displacement patterns. The new model indicates that previous estimates significantly underestimated populations in some districts. The revised estimates provide a more balanced distribution, reducing instances of implausibly high or negative population figures. For example, districts thought to be almost depopulated are revealed to have more viable population levels.Key advances include the use of probabilistic rates of return for displaced people and the integration of new data sources, allowing for a more accurate representation of population movements. These results provide a more reliable basis for planning and service delivery, accurately reflecting the impacts of conflict and climate-induced displacement between 2013 and 2024. The improved model presents a nuanced reconstruction of Somalia's population dynamics, essential for informed decision-making.
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