A Review on Spatial & Transform Domain Digital Watermarking Techniques
A Scoping Review of Spatial Analysis Approaches Using Health Survey Information in Sub-Saharan Africa
1
Biostatistics Enquiry Unit, Due south African Medical Research Council, Pretoria 0001, South Africa
2
Department of Statistics, Academy of Pretoria, Pretoria 0002, South Africa
iii
School of Mathematics, Statistics and Computer science, University of KwaZulu-Natal, Pietermaritzburg 3209, South Africa
4
Partitioning of Epidemiology and Biostatistics, Academy of Stellenbosch, Cape Town 8000, South Africa
5
Ingerod, SE-454 94 Brastad, Sweden
*
Author to whom correspondence should be addressed.
Received: 10 February 2020 / Revised: i April 2020 / Accepted: 3 April 2020 / Published: 28 April 2020
Abstract
Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, only 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 information 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 Itemize, and Scientific discipline Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the concluding review. Spatial smoothing and prediction methods were predominant (north = 108), followed past spatial clarification assemblage (north = 25), and spatial autocorrelation and clustering (n = nineteen). Bayesian statistics methods and lattice data modelling were predominant (due north = 108). Well-nigh studies focused on malaria and fever (n = 47) followed by wellness services coverage (n = 38). Merely fifteen studies employed nonstandard spatial analyses (east.g., spatial model assessment, articulation spatial modelling, accounting for survey design). We recommend that for hereafter spatial analysis using wellness survey data in the SSA region, there must exist an meliorate 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 wellness data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels. View Full-Text
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MDPI and ACS Style
Manda, S.; Haushona, North.; Bergquist, R. A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa. Int. J. Environ. Res. Public Wellness 2020, 17, 3070. https://doi.org/ten.3390/ijerph17093070
AMA Style
Manda S, Haushona N, Bergquist R. A Scoping Review of Spatial Analysis Approaches Using Wellness Survey Data in Sub-Saharan Africa. International Journal of Environmental Research and Public Wellness. 2020; 17(9):3070. https://doi.org/10.3390/ijerph17093070
Chicago/Turabian Style
Manda, Samuel, Ndamonaonghenda Haushona, and Robert Bergquist. 2020. "A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa" International Journal of Environmental Enquiry and Public Wellness 17, no. ix: 3070. https://doi.org/10.3390/ijerph17093070
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Source: https://www.mdpi.com/1660-4601/17/9/3070
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