OBJECTIVES: This study focuses on the health economical impact of new malaria diagnostic devices on the Malaria control processes in Brazil. Current diagnostic tools have disadvantages which prevent the total coverage of malaria risk regions. As a consequence, there is a high demand for diagnostic devices that can be used in remote settings. The objective of this research is to study the cost-effectiveness of new diagnostic devices. METHODS: Markov modeling and Monte Carlo simulation are used to compare the expected cost-effectiveness of the new devices Magneto-Optic Technology (MOT), Rapid Diagnostic Tests (RDT), and Software Aided Microscopy (SAM), with the golden standard of microscopy. Outcome measures are the diagnostic and treatment costs as well as deaths avoided. Scenario analysis is used to compare different implementation strategies of the devices that are expected to be or become most cost-effective.  RESULTS: Microscopy has the highest cost-effectiveness ratio (1.78), followed by SAM (4.02). The access of Microscopy to remote risk regions is however limited. The implementation scenario with the highest health economic impact is to apply microscopy and to use in addition SAM in remote risk regions. At a total of 80 per cent access to diagnosis, microscopy combined with SAM saves in Brazil up to 36.000 lives (30 % improvement) with a cost-saving of 6 M (26 per cent savings). CONCLUSIONS: The outcomes provide clear guidelines for the investment in new devices. Accordingly, Markov modeling is a valuable tool for medical industry facing decisions concerning technology development and implementation.