TB is a public health threat despite the availability of advanced diagnostic tools . In order to successfully control the spread of MTB, cases must be detected and treated immediately. GeneXpert is one of the advanced diagnostic tools enabling POC for same-day diagnosis and treatment. This study aimed to evaluate the cost-effectiveness of GeneXpert compared to smear microscopy using an analytic decision model. An ingredient-based costing approach was employed. In this study, the unit cost per test for smear microscopy diagnostic technique was $3.1, while the unit cost per case detected was US$ 55.5.
Moreover, the unit cost per test was high for the GeneXpert-based algorithm compared to the conventional smear microscope technique. This is consistent with studies conducted in Brazil and India [24, 25] and South Africa . This relatively high cost might be due to expensive equipment and cartridge and high maintenance costs required by the GeneXpert algorithm compared to the routine smear microscopy method.
In this study, most drivers of the unit cost of GeneXpert were cartridge and consumable cost (80%). Moreover, the study result indicated that if the cost of cartridge reduced by 10%, the unit cost would reduce by 9.75% below the base case. This estimate was similar to a study conducted in South Africa (47%)  and Uganda  that indicated the most of the costs of GeneXpert were attributed to the high price of the cartridge. This estimate shows that the high cost of cartridges can be the major obstacle to the full implementation of the diagnostic method as a routine test. Therefore, for the full scale-up of this technology, controlling financial sustainability by either increasing TB funding or reductions in cartridge price is needed, as indicated in another study .
In this study, the cost of smear microscopy and GeneXpert in low testing volume health facilities was $4.96 and $13.22. Our scenario analysis result also revealed that the cost of both diagnostic algorithms was reduced from the base case estimate by increasing the volume of tests per day. This cost estimate is in line with finding from sub-Sahara Africa  and Uganda  on the cost and cost-effectiveness of the GeneXpert diagnostic test. The cost of the test method was high in health facilities where their testing volume was low. The most probable reason was the decrease in cost capital equipment as testing volume per day increased.
The control of TB is still the problem of developing countries due to the rise of MDR-TB and poor case detection. This forced countries to raises their concern about using advanced laboratory diagnostic methods . However, advanced technology should have an acceptable cost and cost-effectiveness to be used as a routine diagnostic procedure. Our study result demonstrated that GeneXpert testing among patients with suspected TB is very cost-effective. This cost estimate is in line with a study in China  and the United States  that found incorporating GeneXpert in the TB diagnostic algorithms was highly cost-effective.
Moreover, this study's result was consistent with a study done in South Africa  that found that using a novel diagnostic test (GeneXpert) for TB diagnosis was cost-saving and cost-effective. However, this finding contradicted the study in Uganda that found GeneXpert was not cost-effective . This difference might be due to the algorithm compared with GeneXpert as MODS has almost similar diagnostic accuracy and low cost compared with the GeneXpert diagnostic method.
The GeneXpert technique's cost-effectiveness was indicative of the potential use of this method for the routine diagnosis of TB. However, this advanced technique's cost-effectiveness depends on the prevalence of TB and the diagnostic accuracy of compared algorithms. In one way, sensitivity analysis, the ICER of GeneXpert, was more sensitive to the prevalence of TB: As the prevalence of TB increases, the GeneXpert algorithm becomes the best optimal strategy despite the higher cost. Besides, the ICER of GeneXpert was moderately influenced by the specificity and sensitivity of GeneXpert diagnostic methods. Similarly, studies on the cost-effectiveness of GeneXpert indicated that the most driver of ICER of GeneXpert was the prevalence of TB [35, 36]. On the other hand, other studies result demonstrated that the diagnostic accuracy of GeneXpert was the most influential parameter on the ICER of this test [6, 37]. If the GeneXpert was used at high TB prevalent areas, the probability of GeneXpert to detect more cases might increase, and this algorithm could be an optimal strategy.
Even though this study is the first of its kind measuring the cost-effectiveness of TB diagnostic method in Ethiopia, it has some limitations. First, the use of 1-times or 3-times GDP per capita per DALY averted, as WTP to decide the cost-effectiveness of the strategies may not be directly applicable to our study since we use an intermediate outcome and the ICER was in terms of cost per TB case detected. Another limitation of our study is that the outcome data were collected from secondary sources, and it is impossible to check the accuracy of the test result. Consequently, this can, to some extent, overestimate or underestimate each method's result during diagnosis. However, as our sensitivity analysis shows, the overall ICER's overall effect is likely minimal. Failure of the cost-effectiveness analysis to indicate the affordability of the cost-effective strategy, as we did not conduct budget impact analysis, can also influence the full implementation of results from our study.