A novel Bayesian geospatial method for estimating tuberculosis incidence reveals many missed TB cases in Ethiopia

BMC Infectious Diseases

Table 2 Predictors of incidence, and case detection rate in the binomial mixture model

	Coefficient, median (95% CrI)	Odds*, Odds ratio (95% CrI)
State-space model
β₀ (intercept)	−5.5 (−6.1, −4.9)	0.004 (0.002, 0.007)*
β₁ (population density)^a	0.1 (0.1, 0.14)	1.1 (1.1,1.2)
β₂ (temporal lag)^b	0.003 (−0.1, 0.1)	1.0 (0.9, 1.1)
β₃ (spatial lag)^b	0.5 (0.3, 0.7)	1.6 (1.4, 2.0)
Case detection model		CDR, median (95% CrI)
CDR in kebeles with no health facility		0.59 (0.55, 0.63)
CDR in kebeles with a health facility		0.69 (0.62, 0.77)

^a Population per square km, ^b: number of incident TB cases/100,000 population/year
CDR- case detection rate

ISSN: 1471-2334