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The increasing availability of complex survey data, and the continued needfor estimates of demographic and health indicators at a fine spatial andtemporal scale, which leads to issues of data sparsity, has led to the need forspatio-temporal smoothing methods that acknowledge the manner in which the datawere collected. The open source R package SUMMER implements a variety ofmethods for spatial or spatio-temporal smoothing of survey data. The emphasisis on small-area estimation. We focus primarily on indicators in a low andmiddle-income countries context. Our methods are particularly useful for datafrom Demographic Health Surveys and Multiple Indicator Cluster Surveys. Webuild upon functions within the survey package, and use INLA for fast Bayesiancomputation. This paper includes a brief overview of these methods andillustrates the workflow of accessing and processing surveys, estimatingsubnational child mortality rates, and visualizing results with both simulateddata and DHS surveys.

Space-Time Smoothing of Demographic and Health Indicators using the R Package SUMMER