by David Majuch Kunjok, John Gachohi Mwangi, Salome Kairu-Wanyoike, Johnson Kinyua, Susan Mambo
IntroductionKenya ranks among the top 30 countries with a high tuberculosis (TB) burden globally. With a TB prevalence of 558 per 100,000, only 46% of TB cases are diagnosed and treated, leaving 54% undiagnosed and at risk of spreading the disease. This study analyzed the spatial distribution of tuberculosis diagnostic delays and their association with health care accessibility and socioeconomic inequalities in Nairobi County, Kenya.
Materials and methodsThe cross-sectional study included 222 newly diagnosed bacteriologically confirmed Mycobacterium tuberculosis (Mtb) patients from Mbagathi County Hospital (MCH), Mama Lucy Kibaki Hospital (MLKH), and Rhodes Chest Clinic (RCC) in Nairobi County, Kenya. Patients were recruited consecutively through census sampling and categorized into two groups: delayed diagnosis (≥21 days from symptom onset) and non-delayed ( Result
Spatial analyses identified 28 statistically significant clusters of delayed TB diagnoses within Nairobi County. Spatial autocorrelation analysis using Moran’s I revealed a significant clustered distribution (Moran’s Index = 0.471, z-score = 3.370, p 2.58, p Discussion and conclusion
The study revealed significant spatial clustering of delayed TB diagnoses in Nairobi County, particularly in informal settlements. In contrast, timely diagnoses were predominantly clustered in high-income areas like Lang’ata and Karen. These clusters were significantly associated with lower household income and increased travel time to health facilities which underscored the need for targeted implementation of TB diagnostic services and control measures in the wards with the highest delays.