MALDI-TOF MS for malaria vector surveillance: A cost-comparison analysis using a decision-tree approach.

Abstract

The use of MALDI-TOF MS for mosquito identification and surveillance is routinely used in developed countries as an affordable alternative to molecular methods. However, in low- and middle-income countries (LMIC) where mosquito-borne diseases carry the greatest burden, the method is not commonly employed. Using the Kenyan national malaria program (NMCP) as a case study, we compared the costs of current methods used for malaria vector surveillance to those that would be incurred if MALDI-TOF MS were used instead. A deterministic decision tree analytic model was developed to systematically calculate the costs associated with materials and labour, and time-to-results for two workflows, i.e., current molecular methods versus MALDI-TOF MS. The analysis assumed an annual sample size of 15,000 mosquitoes (representing the average number of mosquitoes analysed annually by the Kenyan NMCP) processed at a local laboratory in Kenya. We estimate that if the Kenyan national entomological surveillance program shifted sample processing completely to MALDI-TOF MS, it would result in 74.48% net time saving, up to 84% on material costs and 77% on labour costs, resulting in an overall direct cost savings of 83%. Adoption of MALDI-TOF MS for malaria vector surveillance can result in substantial time and cost savings. The ease of performance, the rapid turn-around time, and the modest cost per sample may bring a paradigm shift in routine entomological surveillance in Africa.