The effective stewardship of health programs requires approaches that precisely target resources and interventions to meet population needs; one approach involves the use of geographic data modeling. The increased availability of DHS geographic data coincides with greater recognition by policymakers and researchers of the need for valid approaches to estimating health and population indicators for small administrative areas (i.e., smaller than the usual DHS regions) such as districts, counties, and other subprovincial units. In view of this need, The Demographic and Health Surveys (DHS) Program convened a meeting of key stakeholders, the DHS Spatial Interpolation Working Group, in June 2013 to discuss the use of geographic data from DHS population-based surveys for spatial interpolation. Two key themes emerged from the meeting: data considerations and methods considerations. Data considerations included the selection of appropriate indicators for spatial interpolation while methods considerations focused on specific spatial interpolation techniques. The most important criteria for selecting an interpolation method for use with DHS data are 1) an accurate and statistically rigorous map, and 2) inclusion of a corresponding map surface with estimates of the uncertainty or potential error associated with the spatial interpolation. In the coming years The DHS Program will be charged with the dual task of providing guidance on creating interpolated map surfaces using DHS data as well as guidance on the use and interpretation of these types of map surfaces.