Spatial patterns of extensively drug-resistant tuberculosis and associations with sociodemographic factors in Durban, South Africa Open Access

Peterson, Meaghan (Spring 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/nv935292q?locale=en
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Abstract

Background: Extensively drug-resistant tuberculosis (XDR-TB) poses profound challenges to tuberculosis control because of few remaining treatment options, leading to poor outcomes and ongoing transmission. Recent data suggest at least 69% of XDR-TB cases are due to transmission of resistant strains in KwaZulu-Natal, South Africa. To further clarify factors driving transmission, we aimed to describe where XDR-TB is occurring in the urban district of eThekwini, in KwaZulu-Natal province, and characterize sociodemographic factors of communities with high XDR-TB case burden.

 

Methods: We enrolled XDR-TB patients diagnosed from 2011-2014 in KwaZulu-Natal. GPS coordinates for participant homes were recorded and those with home location in eThekwini (Durban) were included for analysis. ArcGIS was used for spatial data analysis and hotspot evaluation (based on population-adjusted incidence) of XDR-TB patients’ home locations at the main place level. Sociodemographic features of communities identified as hotspots through spatial analysis were examined using data from the 2011 census. For a subset of participants, we geocoded and mapped non-home congregate locations to compare overall spatial distribution to the distribution of homes alone.

 

Results: Among 132 enrolled participants, 75 (57%) were female and 87 (66%) lived in urban or suburban locations. Fifteen main places were identified as hotspots for XDR-TB patient homes with > 95% confidence. Four spatial mapping methods supported findings of one large cluster northwest of Durban. Communities identified as XDR-TB hotspots had lower educational attainment, higher percentage of school-aged children not attending school, higher unemployment, and higher percentage of homes without flush toilet. We geocoded non-home congregate locations (e.g. workplaces, schools, churches) for 43 (33%) participants. Mapping of these congregate settings showed a shift in case density towards the Durban metro area, largely driven by locations of workplaces.

 

Conclusions: Distribution of XDR-TB case homes is clustered in our study area and hotspots have more indicators of poverty than non-hotspots. Prevention efforts targeting these communities may be effective in reducing XDR-TB incidence. Additionally, identifying shared congregate settings of XDR-TB cases may be useful in identifying areas to target for efforts to halt community transmission.

Table of Contents

CHAPTER I: LITERATURE REVIEW 1

Global Tuberculosis Epidemic 1

Drug Resistant Tuberculosis 5

Prevalence and Detection 6

Etiology of Drug Resistance 7

TB in South Africa 8

Drug-Resistant TB in South Africa 9

Drug-Resistant TB in KwaZulu-Natal 11

TB Prevention and Risk Factors 13

Measurement of Sociodemographic Factors 15

Poverty Indices 17

Findings of Sociodemographic Studies 18

Gaps in Knowledge 19

Spatial Analysis in Public Health and TB 20

Spatial Considerations in Infectious Disease Epidemiology 21

Cluster Detection 23

Practical Limitations in GIS 24

Spatial Findings in TB 25

Gaps in Knowledge 26

Conclusion 27

CHAPTER II: MANUSCRIPT 28

Introduction 28

Methods 31

Study Population and Setting 31

Study Variables and Data Sources 31

Data Analysis 33

Ethical Considerations 34

Results 35

Participants 35

Spatial Analysis 35

Activity Space Analysis 36

Sociodemographic Factors 37

Discussion 37

REFERENCES 43

TABLES 51

FIGURES 53

CHAPTER III: PUBLIC HEALTH IMPLICATIONS 55

 

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