In our new paper we present a systematic literature review on geographic information analysis and web-based geoportals to explore malnutrition in Sub-Saharan Africa.
563 articles are identified from the searches, from which a total of nine articles and eight geoportals meet inclusion criteria. The review suggests that the spatial dimension of malnutrition is analyzed most often at the regional and national level using geostatistical analysis methods. Therefore, heterogeneous geographic information at different spatial scales and from multiple sources is combined by applying geoinformation analysis methods such as spatial interpolation, aggregation and downscaling techniques. Geocoded malnutrition data from the Demographic and Health Survey Program are the most common information source to quantify the prevalence of malnutrition on a local scale and are frequently combined with regional data on climate, population, agriculture and/or infrastructure. Only aggregated geoinformation about malnutrition prevalence is freely accessible, mostly displayed via web map visualizations or downloadable map images. The lack of detailed geographic data at household and local level is a major limitation for an in-depth assessment of malnutrition and links to potential impact factors.
We propose that the combination of malnutrition-related studies with most recent GIScience developments such as crowd-sourced geodata collection, (web-based) interoperable spatial health data infrastructures as well as (dynamic) information fusion approaches are beneficial to deepen the understanding of this complex phenomenon.
Further reading
Marx, S., Phalkey, R., Aranda, C., Profe, J., Sauerborn, R. & Höfle, B. (2014): Geographic information analysis and web-based geoportals to explore malnutrition in Sub-Saharan Africa: a systematic review of approaches. BMC Public Health. Vol. 14(1), DOI: 10.1186/1471-2458-14-1189
This research was funded by the Heidelberg Center for the Environment (HCE) of the Heidelberg University, www.hce.uni-heidelberg.de. We acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG) and Heidelberg University within the funding program Open Access Publishing.