Volume 71, Issue 2_suppl
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645


Artemisinin-based combination therapies (ACTs) are generally regarded as vital in addressing the growing problem posed by the development of antimalarial resistance across sub-Saharan Africa. However, the costs of the new ACTs are likely to be significantly higher than current therapies. Therefore, it is important to examine formally the cost-effectiveness of the more effective yet more expensive ACTs before advocating a switch in policy. Importantly, any such economic evaluation must consider the temporal dynamics of drug resistance, and not just focus on the static question of whether switching today would be cost-effective at current levels of resistance, particularly since the development of new antimalarials in the future is so uncertain. However, predicting the future changes in drug resistance is a major difficulty in accurately quantifying the relative costs and health outcomes associated with different drug therapies over time. Here, we use a simple decision tree model to estimate the incremental cost-effectiveness of using ACTs, compared with persisting with current therapies, over 5-, 10-, and 15-year periods. We describe the dynamics of drug resistance using a general logistic growth function, in which the starting frequency of resistance and maximum growth may be altered. However, rather than make assumptions about the absolute rate at which resistance to ACTs will progress, we allow the ratio of the growth rate of resistance to ACTs relative to that of current therapies to vary. Defining the growth rate of ACT resistance in this manner allows us to calculate the threshold ratio at which ACTs would no longer appear cost-effective, for any starting conditions of resistance to current therapies and ACTs, and over any time period. The influence of uncertainty in other decision tree parameters on the threshold ratio values is also quantified, using Monte Carlo simulation techniques. This analysis shows that ACTs are more than 95% likely to be cost-effective under most conditions, other than very low levels of initial resistance to sulfadoxine/pyrimethamine and a five-year time frame. These predictions are conservative in that 95% certainty is a stringent decision rule favoring the rejection of new policies. The importance of other variables not included in the analysis for the robustness of the findings are discussed (e.g., consideration of the entire population at risk for malaria, the affordability of ACTs in specific settings, and the growth of resistance modeled according to population genetic parameters).


Article metrics loading...

Loading full text...

Full text loading...



  1. Nosten F, van Vugt M, Price R, Luxemburger C, Thway KL, Brockman A, McGready R, ter Kuile F, Looareesuwan S, White NJ, 1999. Viewpoint: averting a malaria disaster. Lancet 353 : 1965–1967.
  2. Bloland PB, Kazembe PN, Oloo AJ, Himonga B, Barat LM, Ruebush TK, 1998. Chloroquine in Africa: critical assessment and recommendations for monitoring and evaluating chloroquine therapy efficacy in sub-Saharan Africa. Trop Med Int Health 3 : 543–552.
  3. Bloland PB, Ettling M, Meek S, 2000. Combination therapy for African malaria: hype or hope? Bull World Health Organ 78 : 1378–1388.
  4. McIntosh HM, Olliaro P, 2002. Artemisinin derivatives for treating uncomplicated malaria. Cochrane Database Systematic Review.
  5. White NJ, 1999. Delaying antimalarial drug resistance with combination chemotherapy. Parassitologia 41 : 301–308.
  6. Hastings IM, Watkins WM, White NJ, 2002. The evolution of drug-resistant malaria: the role of drug elimination half-life. Philos Trans R Soc Lond B Biol Sci 357 : 505–519.
  7. Kindermans JM, Pécoul B, Perez-Casas C, Den Boer M, Berman D, Cox I, 2002. Changing National Malaria Treatment Protocols in Africa: What Is the Cost and Who Will Pay? Médicins sans Frontières Campaign for Access to Essential Medicines. Background Paper for the Roll Back Malaria Partnership Meeting on Improving Access to Antimalarial Treatment. Geneva: World Health Organization. September 30 to October 2.
  8. Bloland PB, 2001. Drug Resistance in Malaria. Geneva: World Health Organization.
  9. Goodman CA, Coleman PG, Mills A, 2001. Changing the first line drug for malaria treatment - cost-effectiveness with highly uncertain inter-temporal trade-offs. Health Econ 10 : 731–749.
  10. WHO/CTD, 1996. Assessment of Therapeutic Efficacy of Antimalarial Drugs for Uncomplicated Falciparum Malaria with Intense Transmission. Geneva: World Health Organization. WHO/MAL/96.1077
  11. Goodman CA, Coleman PG, Mills A, 1999. Cost-effectiveness of malaria control in sub-Saharan Africa. Lancet 354 : 378–385.
  12. Murray CJL, Lopez AD, 1996. The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020. Cambridge, MA: Harvard University Press.
  13. Goodman CA, Coleman PG, Mills A, 2000. Economic Analysis of Malaria Control in Sub-Saharan Africa. Geneva: World Health Organization. Global Forum for Health Research.
  14. Roper C, Pearce R, Bredenkamp B, Gumede J, Drakeley C, Mosha F, Chandramohan D, Sharp B, 2003. Antifolate anti-malarial resistance in southeast Africa: a population-based analysis. Lancet 361 : 1174–1181.
  15. WHO, 1996. Investing in Health Research and Development: Report of the Ad Hoc Committee in Health Research Relating to Future Intervention Options. Geneva: World Health Organization. TDR/Gen/96.1.
  16. Curtis CF, Otoo LN, 1986. A simple model of the build-up of resistance to mixtures of anti-malarial drugs. Trans R Soc Trop Med Hyg 80 : 889–892.
  17. Hastings IM, D’Alessandro U, 2000. Modelling a predictable disaster: the rise and spread of drug-resistant malaria. Parasitol Today 16 : 340–347.
  18. Phillips M, Phillips-Howard PA, 1996. Economic implications of resistance to antimalarial drugs. Pharmacoeconomics 10 : 225–238.
  19. Sudre P, Breman JG, McFarland D, Koplan JP, 1992. Treatment of chloroquine-resistant malaria in African children: a cost-effectiveness analysis. Int J Epidemiol 21 : 146–154.
  20. Claxton K, 1999. The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies. J Health Econ 18 : 341–364.
  21. Kindermans JM, 2002. ACTs: Availability and Prices. Geneva: World Health Organization. Presentation at Roll Back Malaria Partners Meeting, October 1.

Data & Media loading...

  • Received : 21 Aug 2003
  • Accepted : 08 Dec 2003

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error