Economic costs of vivax malaria episodes: A multi-country comparative analysis using primary trial data

Published: January 1, 2019

Citation

Devine A, Pasaribu AP, Teferi T, Pham HT, Awab GR, Contantia F, Nguyen TN, Ngo VT, Tran H, Hailu A, Gilchrist K, Green JA, Koh GCKW, Thriemer K, Taylor WR, Day NPJ, Price RN, Lubell Y. Economic costs of vivax malaria episodes: A multi-country comparative analysis using primary trial data. WHO Bulletin 2019; 97:828-836.

Abstract

Objective
To determine household and health-care provider costs associated with Plasmodium vivax infection across a range of endemic settings.

Methods
We collected cost data alongside three multicentre clinical trials of P. vivax treatment in Afghanistan, Brazil, Colombia, Ethiopia, Indonesia, Philippines, Peru, Thailand and Viet Nam conducted between April 2014 to December 2017. We derived household costs from trial participant surveys administered at enrolment and again 2 weeks later to determine the costs of treatment and transportation, and the number of days that patients and their household caregivers were unable to undertake their usual activities. We determined costs of routine care by health-care providers by micro-costing the resources used to diagnose and treat P. vivax at the study sites.

Findings
The mean total household costs ranged from 8.7 United States dollars (US$; standard deviation, SD: 4.3) in Afghanistan to US$ 254.7 (SD: 148.4) in Colombia. Across all countries, productivity losses were the largest household cost component, resulting in mean indirect costs ranging from US$ 5.3 (SD: 3.0) to US$ 220.8 (SD: 158.40). The range of health-care provider costs for routine care was US$ 3.6–6.6. The cost of administering a glucose-6-phosphate-dehydrogenase rapid diagnostic test, ranged from US$ 0.9 to 13.5, consistently lower than the costs of the widely-used fluorescent spot test (US$ 6.3 to 17.4).

Conclusion
An episode of P. vivax malaria results in high costs to households. The costs of diagnosing and treating P. vivax are important inputs for future cost–effectiveness analyses to ensure optimal allocation of resources for malaria elimination.