Space-time mapping of wasting among children under the age of five years in Somalia from 2007 to 2010.

Journal article

Objective

To determine the sub-national seasonal prevalence and trends wasting from 2007 to 2010 among children under the age of five years in Somalia using remote sensing and household survey data from nutritional surveys by location.

Methods

Bayesian hierarchical space-time model in integrated nested Laplace approximations (INLA) was implemented using a stochastic partial differential equation (SPDE) approach to produce risk maps of wasting at 1 x 1 km spatial resolution and predict to seasons in each year of study from 2007 to 2010.

Results

The prevalence of wasting is generally at critical levels throughout the country with most of the areas remaining in the upper classes of critical and very critical levels. There is minimal variation in wasting from year-to-year, but a well-defined seasonal variation is observed. The mean difference of the prevalence of wasting between the dry and wet season ranges from 0% - 5%. The risks of wasting in the South-central zone were highest in the Gedo (37%) and Bay (32%) regions. In Puntland the risk was highest in Nugaal (25%) and in Somaliland the risk was high in Awdal and Woqooyi Galbeed regions with 23%.

Conclusion

There is a clear seasonal variation in wasting with minimal year-to-year variability from 2007 to 2010 in Somalia. The prevalence is high during the long dry season, which affects the prevalence in the preceding long rainy season. Understanding the seasonal fluctuations of wasting in different locations and at different times is important to inform timely interventions

Authors: Kinyoki, D; Berkley, J; Moloney, G; Odundo, E; Kandala, N

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Elsevier
• Journal: Spatial and Spatio-Temporal epidemiology
• Volume: 16
• Pages: 77-87
• Publication date: 2016-01-01
• Acceptance date: 2015-12-31
• DOI: 10.1016/j.sste.2015.12.002
• EISSN: 1877-5853
• ISSN: 1877-5845
• Language: English
• Keywords: Bayesian; Seasonality; Space–time model; Wasting; Malnutrition