Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

Diego F Cuadros; Claudia M Moreno; Andrew Tomita; Urisha Singh; Stephen Olivier; Alison Castle; Yumna Moosa; Johnathan A Edwards; Hae-Young Kim; Mark J Siedner; Emily B Wong; Frank Tanser

doi:10.1177/26335565231204119

Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

J Multimorb Comorb. 2023 Sep 28:13:26335565231204119. doi: 10.1177/26335565231204119. eCollection 2023 Jan-Dec.

Authors

Diego F Cuadros¹, Claudia M Moreno², Andrew Tomita^{3

4}, Urisha Singh^{5

6}, Stephen Olivier⁵, Alison Castle^{5

7

8}, Yumna Moosa^{4

5}, Johnathan A Edwards^{9

10

11}, Hae-Young Kim¹², Mark J Siedner^{5

7

8

13}, Emily B Wong^{5

14}, Frank Tanser^{15

16

17}

Affiliations

¹ Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.
² Howard Hughes Medical Institute, Department of Physiology and Biophysics, University of Washington School of Medicine, Seattle, WA, USA.
³ Centre for Rural Health, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.
⁴ KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
⁵ Clinical Research Department, Africa Health Research Institute, KwaZulu-Natal, South Africa.
⁶ Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa.
⁷ Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA.
⁸ Global Health and Population, Harvard Medical School, Boston, MA, USA.
⁹ International Institute for Rural Health, University of Lincoln, Lincolnshire, UK.
¹⁰ Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
¹¹ Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, USA.
¹² Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
¹³ School of Clinical Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
¹⁴ Division of Infectious Diseases, University of Alabama Birmingham, Birmingham, AL, USA.
¹⁵ Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
¹⁶ School of Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
¹⁷ Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa.

Abstract

Introduction: Several low-and middle-income countries are undergoing rapid epidemiological transition with a rising burden of non-communicable diseases (NCDs). South Africa (SA) is a country with one of the largest HIV epidemics worldwide and a growing burden of NCDs where the collision of these epidemics poses a major public health challenge.

Methods: Using data from a large nationally representative survey, the South Africa Demographic and Health Survey (SADHS 2016), we conducted a geospatial analysis of several diseases including HIV, tuberculosis (TB), cardiovascular, respiratory, and metabolic diseases to identify areas with a high burden of co-morbidity within the country. We explored the spatial structure of each disease and associations between diseases using different spatial and visual data methodologies. We also assessed the individual level co-occurrence of HIV and the other diseases included in the analysis.

Results: The spatial distribution for HIV prevalence showed that this epidemic is most intense in the eastern region of the country, mostly within the Gauteng, Mpumalanga, and Kwazulu-Natal provinces. In contrast, chronic diseases had their highest prevalence rates the southern region of the country, particularly in the Eastern and Western Cape provinces. Individual-level analyses were consistent with the spatial correlations and found no statistically significant associations between HIV infection and the presence of any NCDs.

Conclusions: We found no evidence of geospatial overlap between the HIV epidemic and NCDs in SA. These results evidence the complex epidemiological landscape of the country, characterized by geographically distinct areas exhibiting different health burdens. The detailed description of the heterogenous prevalence of HIV and NCDs in SA reported in this study could be a useful tool to inform and direct policies to enhance targeted health service delivery according to the local health needs of each community.

Keywords: HIV; Multimorbidity; South Africa; noncommunicable diseases; spatial epidemiology.

Abstract

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