RESUMO
BACKGROUND: Effective management of tuberculosis (TB) and reduction of TB incidence relies on knowledge of where, when and to what degree the disease is present. METHODS: In a retrospective cross-sectional study, we analysed the spatial distribution of notified TB incidence from 1 January 2012 and 31 December 2015 in Siaya and Kisumu Counties, Western Kenya. TB data were obtained from the Division of Leprosy, Tuberculosis and Lung Disease, Nairobi, Kenya, as part of an approved TB case detection study. Cases were linked to their corresponding geographic location using physical address identifiers. Spatial analysis techniques were used to examine the spatial and temporal patterns of TB. Assessment of spatial clustering was carried out following Moran's I method of spatial autocorrelation and the Getis-Ord Gi* statistic. RESULTS: The notified TB incidence varied from 638.0 to 121.4 per 100 000 at the small area level. Spatial analysis identified 16 distinct geographic regions with high TB incidence clustering (GiZScore 2.58, P < 0.01). There was a positive correlation between population density and TB incidence that was statistically significant (rs = 0.5739, P = 0.0001). CONCLUSION: The present study presents an opportunity for targeted interventions in the identified subepidemics to supplement measures aimed at the general population.