Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries

Table 2 Crude total and per-TB detection cost savings and mWRD access expansion by country

	Crude cost savings ($)		Per-TB cost savings ($)		mWRD access expansion
	Incremental	Cumulative	Incremental	Cumulative	Incremental	Cumulative
Bangladesh
Baseline approach
CXR approach	100,669	100,669	27.36	27.36	110.3%	110.3%
Indiscriminate pooling approach	− 1817	98,852	− 0.49	26.87	− 2.0%	106.2%
AI-guided pooling approach	19,240	118,091	5.23	32.10	26.1%	160.0%
Zambia
Baseline approach
CXR approach	3132	3132	11.47	11.47	20.1%	20.1%
Indiscriminate pooling approach	4846	7978	17.75	29.22	45.0%	74.0%
AI-guided pooling approach	1546	9524	5.66	34.89	16.8%	103.2%
Nigeria
Baseline approach
CXR approach	2256	2256	26.53	26.53	38.3%	38.3%
Indiscriminate pooling approach	2224	4479	26.16	52.70	60.8%	122.4%
AI-guided pooling approach	199	4678	2.34	55.04	5.8%	135.3%
Viet Nam
Baseline approach
CXR approach	17,191	17,191	37.78	37.78	73.9%	73.9%
Indiscriminate pooling approach	6432	23,623	14.14	51.92	38.2%	140.5%
AI-guided pooling approach	1235	24,858	2.72	54.63	7.9%	159.5%

CXR Chest X-ray, AI Artificial intelligence, Mwrd Molecular WHO-Recommended Rapid Diagnostic

ISSN: 2731-913X