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A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa

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  • Samuel Manda

    (Biostatistics Research Unit, South African Medical Research Council, Pretoria 0001, South Africa
    Department of Statistics, University of Pretoria, Pretoria 0002, South Africa
    School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Pietermaritzburg 3209, South Africa)

  • Ndamonaonghenda Haushona

    (Biostatistics Research Unit, South African Medical Research Council, Pretoria 0001, South Africa
    Division of Epidemiology and Biostatistics, University of Stellenbosch, Cape Town 8000, South Africa)

  • Robert Bergquist

    (Ingerod, SE-454 94 Brastad, Sweden)

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.

Suggested Citation

  • Samuel Manda & Ndamonaonghenda Haushona & Robert Bergquist, 2020. "A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa," IJERPH, MDPI, vol. 17(9), pages 1-20, April.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3070-:d:351558
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    1. Damaris K. Kinyoki & Samuel O. Manda & Grainne M. Moloney & Elijah O. Odundo & James A. Berkley & Abdisalan M. Noor & Ngianga-Bakwin Kandala, 2017. "Modelling the Ecological Comorbidity of Acute Respiratory Infection, Diarrhoea and Stunting among Children Under the Age of 5 Years in Somalia," International Statistical Review, International Statistical Institute, vol. 85(1), pages 164-176, April.
    2. Diego F. Cuadros & Laith J. Abu-Raddad, 2016. "Geographical Patterns of HIV Sero-Discordancy in High HIV Prevalence Countries in Sub-Saharan Africa," IJERPH, MDPI, vol. 13(9), pages 1-12, August.
    3. Ngianga-Bakwin Kandala & Saverio Stranges, 2014. "Geographic Variation of Overweight and Obesity among Women in Nigeria: A Case for Nutritional Transition in Sub-Saharan Africa," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-11, June.
    4. Ngianga-Bakwin Kandala & Gebrenegus Ghilagaber, 2006. "A Geo-Additive Bayesian Discrete-Time Survival Model and its Application to Spatial Analysis of Childhood Mortality in Malawi," Quality & Quantity: International Journal of Methodology, Springer, vol. 40(6), pages 935-957, December.
    5. Kotsadam, Andreas & Østby, Gudrun & Rustad, Siri Aas & Tollefsen, Andreas Forø & Urdal, Henrik, 2018. "Development aid and infant mortality. Micro-level evidence from Nigeria," World Development, Elsevier, vol. 105(C), pages 59-69.
    6. Kpienbaareh, Daniel & Atuoye, Kilian N. & Ngabonzima, Anaclet & Bagambe, Patrick G. & Rulisa, Stephen & Luginaah, Isaac & Cechetto, David F., 2019. "Spatio-temporal disparities in maternal health service utilization in Rwanda: What next for SDGs?," Social Science & Medicine, Elsevier, vol. 226(C), pages 164-175.
    7. Julius Ssempiira & Betty Nambuusi & John Kissa & Bosco Agaba & Fredrick Makumbi & Simon Kasasa & Penelope Vounatsou, 2017. "Geostatistical modelling of malaria indicator survey data to assess the effects of interventions on the geographical distribution of malaria prevalence in children less than 5 years in Uganda," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-20, April.
    8. Adebayo, Samson B. & Fahrmeir, Ludwig & Klasen, Stephan, 2004. "Analyzing infant mortality with geoadditive categorical regression models: a case study for Nigeria," Economics & Human Biology, Elsevier, vol. 2(2), pages 229-244, June.
    9. Burroway, Rebekah & Hargrove, Andrew, 2018. "Education is the antidote: Individual- and community-level effects of maternal education on child immunizations in Nigeria," Social Science & Medicine, Elsevier, vol. 213(C), pages 63-71.
    10. Kandala, Ngianga-Bakwin & Emina, Jacques B. & Nzita, Paul Denis K. & Cappuccio, Francesco P., 2009. "Diarrhoea, acute respiratory infection, and fever among children in the Democratic Republic of Congo," Social Science & Medicine, Elsevier, vol. 68(9), pages 1728-1736, May.
    11. Aoun, Nael & Matsuda, Hirotaka & Sekiyama, Makiko, 2015. "Geographical accessibility to healthcare and malnutrition in Rwanda," Social Science & Medicine, Elsevier, vol. 130(C), pages 135-145.
    12. Oscar Ngesa & Henry Mwambi & Thomas Achia, 2014. "Bayesian Spatial Semi-Parametric Modeling of HIV Variation in Kenya," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-11, July.
    13. David Shapiro & Michel Tenikue, 2017. "Women’s education, infant and child mortality, and fertility decline in urban and rural sub-Saharan Africa," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(21), pages 669-708.
    14. Gudrun Østby & Henrik Urdal & Andreas Forø Tollefsen & Andreas Kotsadam & Ragnhild Belbo & Christin Ormhaug, 2018. "Organized Violence and Institutional Child Delivery: Micro-Level Evidence From Sub-Saharan Africa, 1989–2014," Demography, Springer;Population Association of America (PAA), vol. 55(4), pages 1295-1316, August.
    15. United Nations, 2016. "The Sustainable Development Goals 2016," Working Papers id:11456, eSocialSciences.
    16. Anselin, Luc & Getis, Arthur, 1992. "Spatial Statistical Analysis and Geographic Information Systems," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 19-33, April.
    17. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    18. Emanuele Giorgi & Peter J. Diggle & Robert W. Snow & Abdisalan M. Noor, 2018. "Geostatistical Methods for Disease Mapping and Visualisation Using Data from Spatio‐temporally Referenced Prevalence Surveys," International Statistical Review, International Statistical Institute, vol. 86(3), pages 571-597, December.
    19. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    20. Gavin Tansley & Nadine Schuurman & Ofer Amram & Natalie Yanchar, 2015. "Spatial Access to Emergency Services in Low- and Middle-Income Countries: A GIS-Based Analysis," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-12, November.
    21. Ezra Gayawan & Samson B. Adebayo, 2013. "A Bayesian semiparametric multilevel survival modelling of age at first birth in Nigeria," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(45), pages 1339-1372.
    22. Kedir N. Turi & Mary J. Christoph & Diana S. Grigsby-Toussaint, 2013. "Spatial Distribution of Underweight, Overweight and Obesity among Women and Children: Results from the 2011 Uganda Demographic and Health Survey," IJERPH, MDPI, vol. 10(10), pages 1-15, October.
    23. Kneib, Thomas, 2006. "Mixed model-based inference in geoadditive hazard regression for interval-censored survival times," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 777-792, November.
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