Abstract:
Spatial analysis has become an increasingly used analytic approach to describe and analyze
spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys
data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct
an evaluation of studies using spatial statistics approaches for national health survey data in the
SSA region. An organized literature search for studies related to spatial statistics and national
health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science
Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final
review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial
description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics
methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria
and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed
nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting
for survey design). We recommend that for future spatial analysis using health survey data in the
SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve
application of spatial statistical methods. We also recommend a wide range of applications using big
health data and the future of data science for health systems to monitor and evaluate impacts that are
not well understood at local levels.
