How to optimize tuberculosis case finding: explorations for Indonesia with a health system model

BMC Infectious Diseases

Table 3 Predicted effect of three interventions (A, B, C) on a cohort of TB patients (%)

			With intervention
Scenario	Model outcome	No intervention	A	B	C
Baseline^a	Death	16.6	14.2	15.5	16.5
	Partially cured	19.6	20.7	20.1	11.5
	Cured	52.8	55.7	54.1	61.0
	Spontaneous recovery	11.1	9.5	10.3	11.0
More important alternative health sector^b	Death	18.1	15.8	16.6	18.0
	Partially cured	18.5	19.6	19.2	11.1
	Cured	51.2	54.1	53.1	58.9
	Spontaneous recovery	12.1	10.5	11.1	12.0

A: strategy to reduce the proportion of TB patients who never seek care (Never seeking compartment) by 50%;
B: strategy to reduce patients' delay (i.e. reduce duration in Not seeking care compartment) by 50%;
C: strategy to refer all TB suspect patients from non-DOTS services to DOTS services (from Non-DOTS services to DOTS lab1 compartment).
^a: Simulation using experts estimated parameters
^b: Simulation using adjusted parameters in the alternative health sector, i.e. if 20% of the flow of TB patients to the DOTS and Non-DOTS services compartments now move to the Alternative services compartment (i.e. the proportion of TB patients move from Not seeking care compartment to Alternative, Non-DOTS, and DOTS services compartments are 36%, 24%, and 40% respectively), and patients cannot go directly to the DOTS and Non-DOTS services.

ISSN: 1471-2334