Background: Rapid diagnostic tests (RDTs) are widely used for diagnosing Plasmodium vivax malaria, especially in resource-limited countries. However, the impact of RDTs on P. vivax malaria incidence and national medical costs has not been evaluated. We assessed the impact of RDT implementation on P. vivax malaria incidence and overall medical expenditures in South Korea and performed a cost-benefit analysis from the payer's perspective.
Methods: We developed a dynamic compartmental model for P. vivax malaria transmission in South Korea using delay differential equations. Long latency and seasonality were incorporated into the model, which was calibrated to civilian malaria incidences during 2014-2018. We then estimated averted malaria cases and total medical costs from two diagnostic scenarios: microscopy only and both microscopy and RDTs. Medical costs were extracted based on data from a hospital in an at-risk area for P. vivax malaria and were validated using Health Insurance Review and Assessment Service data. We conducted a cost-benefit analysis of RDTs using the incremental benefit:cost ratio (IBCR) considering only medical costs and performed a probabilistic sensitivity analysis to reflect the uncertainties of model parameters, costs and benefits.
Results: The results showed that 55.3% of new P. vivax malaria cases were averted, and $696 214 in medical costs was saved over 10 years after RDT introduction. The estimated IBCR was 2.5, indicating that RDT implementation was beneficial, compared with microscopy alone. The IBCR was sensitive to the diagnosis time reduction, infectious period and short latency period, and provided beneficial results in a benefit over $10.6 or RDT cost under $39.7.
Conclusions: The model simulation suggested that RDTs could significantly reduce P. vivax malaria incidence and medical costs. Moreover, cost-benefit analysis demonstrated that the introduction of RDTs was beneficial over microscopy alone. These results support the need for widespread adoption of RDTs.
Keywords: epidemiology; malaria; mathematical modelling.
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