Geographic distribution and predictors of diagnostic delays among possible TB patients in Uganda
METHODS: We conducted a secondary analysis of adults undergoing TB evaluation within a public health demonstration project in Uganda. Using Global Moran’s I (GMI) and Getis-Ord GI* statistics, we evaluated for residential clustering and hotspots associated with patient-related and health system-related delays. We performed multivariate logistic regression to identify individual predictors of both types of delays.
RESULTS: Of 996 adults undergoing TB evaluation (median age: 37 years, IQR 28–49), 333 (33%) experienced patient delays, and 568 (57%) experienced health system delays. Participants were clustered (GMI 0.47–0.64, P 0.001) at the sub-county level, but there were no statistically significant hotspots for patient or health system delays. Married individuals were less likely to experience patient delays (OR 0.6, 95% CI 0.48–0.75; P < 0.001). Those aged 38–57 years (OR 1.2, 95% CI 1.07–1.38; P = 0.002) were more likely than those aged 58 years to experience patient delays. Knowledge about TB (OR 0.8, 95% CI 0.63–0.98; P = 0.03) protected against health system delays.
CONCLUSIONS: We did not identify geographic hotspots for TB diagnostic delays. Instead, delays were associated with individual factors such as age, marital status and TB knowledge.
Keywords: Africa; GIS; delayed diagnosis; tuberculosis
Document Type: Research Article
Affiliations: 1: Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda; 2: Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda;, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 3: Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda;, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA 4: Departments of Veterinary Medicine and Animal Resources 5: Biotechnical and Biolab Sciences, and 6: Biosecurity, Ecosystem and Veterinary Public Health, College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, Kampala, Uganda 7: Lung Institute, and 8: Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda; 9: Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda;, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, Pulmonary, Critical Care and Sleep Medicine Section, Yale School of Medicine, New Haven, CT, USA; 10: Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda;, Clinical Epidemiology Unit, Makerere University, College of Health Sciences, Kampala, Uganda
Publication date: September 21, 2023
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