Decision-making on malaria vaccine introduction: the role of costeffectiveness analyses
Vasee S MoorthyI,*; Raymond HutubessyI; Robert D NewmanII; Joachim HombachI
IInitiative for Vaccine Research, Department of Immunization, Vaccines & Biologicals, World Health Organization, avenue Appia 20, 1211 Geneva 27, Switzerland
IIGlobal Malaria Programme, World Health Organization, Geneva, Switzerland
Status of malaria vaccine development
Policy-makers in countries where malaria is endemic are facing increasingly complex decisions about which vaccines and malaria prevention measures to include in national immunization and malaria control programmes. Several new vaccines and malaria preventive measures are already competing for limited financing in developing countries. African countries with endemic malaria should be ready to make a national policy decision on the introduction of RTS,S/AS01, a first-generation malaria vaccine, by 2015.1 If clinical trials progress according to schedule, that same year the World Health Organization (WHO) will issue a policy recommendation on the public health use of this vaccine based on the findings of the full Phase III efficacy trial in progress, which will be available in late 2014.2 The vaccine's manufacturers are targeting infants in malaria-endemic African countries who undergo routine vaccination through the Expanded Programme on Immunization (EPI) at 6, 10 and 14 weeks of age, with the possibility of a booster dose being needed at 918 months. At present WHO is assessing the evidence base for a policy position on this vaccine. The type of critical data that it will take into account during this process is shown in Box 1.
Costeffectiveness is an important consideration in public health decision-making. This article summarizes critical parameters driving malaria vaccine costeffectiveness predictions and discusses major uncertainties that remain in the costeffectiveness modelling arena. It also highlights the need for ongoing work by modelling groups to further refine costeffectiveness predictions.
The RTS,S/AS01 vaccine is intended for use in conjunction with existing measures for malaria prevention, such as the use of long-lasting insecticide-treated nets (LLINs), which is known to be highly costeffective. A recent systematic review3 of costeffectiveness studies of the use of insecticide-treated nets reported a median cost per disability-adjusted life year (DALY) averted of 27 United States dollars (US$) (range: 8110). LLINs have been associated with reduced all-cause mortality in African children under the age of 5 years4 and are known to greatly reduce malaria transmission.5 So, in countries that have successfully scaled up the use of LLINs, implemented rapid malaria diagnostic testing and facilitated access to effective artemisinin-based combination therapy, how will policy-makers decide whether or not to introduce RTS,S/AS01 as an additional malaria control measure?
Policy-makers are encouraged to use economic evidence from costeffectiveness models, in addition to burden of disease and attainable coverage, to guide their decision-making. During 2010 and 2011, WHO undertook an analysis of model structure, assumptions and key parameters to identify the factors driving uncertainty in malaria vaccine costeffectiveness models. It received independent expert advice from two groups: the Joint Technical Expert Group (JTEG) and the Quantitative Immunization and Vaccines Related Research (QUIVER) Advisory Committee. JTEG is composed of malaria vaccine experts and QUIVER provides technical advice in areas such as vaccine modelling and costeffectiveness tools. In March 2011, a subgroup of JTEG and QUIVER members met with representatives of five modelling groups the Swiss Tropical and Public Health Institute, Imperial College, Intellectual Ventures, GlaxoSmithKline Biologicals and the PATH Malaria Vaccine Initiative.6 So far only one of these groups has published costeffectiveness predictions for the introduction of RTS,S/AS01 into national immunization programmes7 and at least one more is planning to publish a malaria vaccine costeffectiveness model.8 Other malaria vaccine costeffectiveness models and tools are expected to become available over the next few years as Phase III trial results fuel further work.
The meeting between JTEG/QUIVER members and modelling groups resulted in an assessment of the uncertainty underlying model parameters. In the field of malaria epidemiology, major uncertainty still surrounds certain parameters, most notably the incidence of clinical and severe malaria and malaria-related mortality in older children and adults. In addition, major uncertainties remain in connection with the relative effects of age and exposure to malaria parasites on naturally-acquired immunity,9 the interaction between vaccine-induced immunity and naturally-acquired immunity,10 and the potential impact of different types of malaria vaccines on malaria transmission (i.e. herd effects). All of these are important parameters to consider when making costeffectiveness predictions.7 We therefore encourage multiple groups using different modelling designs, structures, tools and plausible assumptions to provide costeffectiveness predictions, as we have done in the course of other vaccine modelling efforts.11 We also support ongoing efforts to fully explore and discuss the uncertainties underlying malaria transmission models; to iteratively improve model parameterization through data fitting, and to carry out further sensitivity analyses to better characterize the parameters driving uncertainty.
Impact and costeffectiveness models
Two published transmission models have so far predicted that RTS,S/AS01 is unlikely to substantially affect transmission if administered at 614 weeks of age through routine EPI programmes.8,12 This needs to be confirmed or proven false through clinical studies, but it highlights the importance of considering RTS,S/AS01 within a framework in which mosquito vector control measures, such as the use of LLINs or indoor residual spraying, have already reduced malaria transmission. Another prediction is that vaccine costeffectiveness will be highest in settings where transmission is low to moderate (i.e. annual entomological inoculation rate (EIR) above 12 but less than 100). The EIR, a measure of transmission intensity, is the number of infectious mosquito bites received per person per unit of time.
A recent probabilistic sensitivity and uncertainty analysis of one model provided useful insights into some of the uncertainties involved in parameterizing malaria transmission models.7 According to this report, the use of RTS,S/AS01 could be highly costeffective in many settings with low to moderate transmission, depending on the price of the vaccine and the duration of the vaccine's protection. In this model costeffectiveness decreases as transmission intensity increases above an annual EIR of 100. If final Phase III trial data shows that the efficacy of RTS,S/AS01 is lower in high-transmission settings, it will be critical to maximize Anopheles vector control to reduce transmission intensity wherever the introduction of RTS,S/AS01 is being considered.
Parameters driving costeffectiveness predictions
What are the key drivers of costeffectiveness predictions? Most groups use similar parameters for initial efficacy, as there are now multiple clinical trial estimates of the initial efficacy of RTS,S/AS01. Initial efficacy estimates from the Phase III trial for infants 614 weeks of age who receive RTS,S/AS01 together with other infant vaccines will be available before the end of 2012. Efficacy estimates for this age group are already available from Phase II trials.
The price per dose of vaccine is a key driver of costeffectiveness. At a cost of US$ 1 or 2 per dose, high costeffectiveness is predicted for most African settings even with the expected four-dose schedule, according to the most extensively published model.7 Since countries are unlikely to introduce RTS,S/AS01 unless they find funding beyond what is needed to support universal access to LLINs or indoor residual spraying, rapid diagnostic tests, and artemisinin-based combination treatment, it becomes apparent that price will be a key factor in public health decision-making surrounding any first-generation malaria vaccine.
The duration of protection is another critical parameter, and this is currently unknown. Although it is difficult to infer efficacy half-life from the clinical trial data currently available, almost all experts concur that this is less than 5 years in the case of RTS,S/AS01. Some predictive models used a less credible half-life of 10 years, although sensitivity analyses were conducted to illustrate the effect of shortening vaccine half-life on predicted costeffectiveness. These analyses suggest that a vaccine half-life of less than 2 to 3 years reduces predicted costeffectiveness substantially.7 We need ongoing research to better characterize the function describing the decay of vaccine efficacy and thus accurately parameterize the costeffectiveness models for this key variable.
The true number of incident malaria infections in a given setting is also an important parameter. Because RTS,S/AS01 acts by reducing incident infections,13 and since all other outcomes follow from this primary biological effect and its interaction with naturally-acquired immunity, it would be helpful to have access to better data on the true incidence of new infections in different settings.
Finally, the mechanism by which the vaccine achieves a given level of efficacy at the group or population level is potentially important for costeffectiveness predictions but remains poorly understood. We know that RTS,S/AS01 reduces the frequency of new malaria infections, but we do not know how much protection varies from person to person. For example, if on average the vaccine reduces the frequency of new infections by 50%, in a vaccinated population does protection vary from 10% among some to 90% among others or does the population uniformly experience a 50% reduction in the rate of infection? This variability is referred to as the "heterogeneity of vaccine mode of action". The sensitivity analyses show that such variability is a substantial driver of model costeffectiveness predictions.7 To date there are few data regarding this potential heterogeneity.
If the malaria vaccine costeffectiveness field progresses with the publication of new model-based costeffectiveness analyses by multiple groups, WHO may facilitate formal comparative assessments of costeffectiveness tools, as it did for vaccines against human papillomavirus, rotavirus and pneumococcus.11
In conclusion, we have conducted an analysis of model structures, assumptions and key parameters driving uncertainty in the field of malaria vaccine costeffectiveness models. The key drivers of predicted costeffectiveness will be price per dose, efficacy, duration of protection and malaria transmission intensity (incidence of new infections per unit of time). Phase III trial data, expected to become available in late 2014, may help address some of the current limitations of model-based costeffectiveness predictions, as outlined above. Additionally, further advances in modelling are expected as multiple groups continue to refine their models. RTS,S/AS01 will be considered for use in conjunction with key preventive measures that exist already, particularly the use of LLINs.
Modelling in Phase IV trials
Current leading malaria transmission models may have a place in the design of Phase IV trials of malaria vaccines. They may be especially useful in determining the immunization strategies that would best reduce malaria transmission in settings with different transmission characteristics. Until such data from Phase IV trials become available, recommendations for malaria vaccine use, expected in 2015, are likely to be restricted to the age groups for which Phase III trial data are available, i.e. children from 6 weeks to 17 months of age. Whether or not a formal costeffectiveness tool assessment is performed, we will continue to critically appraise the results of model-based costeffectiveness evaluations.11
Vaccine introduction decision-making
As highlighted earlier, costeffectiveness is only one criterion among many that influence decision-making in public health. When deciding to implement an intervention, efficiency must always be balanced with other criteria, including implementation capacity, feasibility and impact on poverty and equity.14 In the case of RTS,S/AS01, WHO will provide an updated costeffectiveness assessment in 2015, at the time when decision-making by countries will be necessary. The status of the field of malaria vaccine costeffectiveness does not yet support the use of simple, national-level vaccine impact or costeffectiveness tools by country programmes.
Vasee Moorthy works jointly for the Immunization, Vaccines & Biologicals Department and the WHO Global Malaria Programme.
Competing interests: None declared.
1. Agnandji ST, Lell B, Soulanoudjingar SS, Fernandes JF, Abossolo BP, Conzelmann C et al. First results of phase 3 trial of RTS,S/AS01 malaria vaccine in African children. N Engl J Med 2011;365:186375. doi:10.1056/NEJMoa1102287 PMID:22007715
2. World Health Organization [Internet]. Malaria. Geneva: WHO; 2012. Available from: http://www.who.int/vaccine_research/Malaria/en/index.html [accessed 12 September 2012] .
3. White MT, Conteh L, Cibulskis R, Ghani AC. Costs and cost-effectiveness of malaria control interventions: a systematic review. Malar J 2011;10:337. doi:10.1186/1475-2875-10-337 PMID:22050911
4. Lengeler C. Insecticide-treated bednets and curtains for preventing malaria. Cochrane Database Syst Rev 2004;2:CD000363. PMID:15106149
5. Hawley WA, Phillips-Howard PA, ter Kuile FO, Terlouw DJ, Vulule JM, Ombok M et al. Community-wide effects of permethrin-treated bed nets on child mortality and malaria morbidity in western Kenya. Am J Trop Med Hyg 2003;68(Suppl):1217. PMID:12749495
6. Report on the: WHO Quantitative Immunization and Vaccines Related Research (QUIVER): advisory committee meeting, Geneva, 46 October 2011. Geneva: World Health Organization; 2012. Available from: whqlibdoc.who.int/hq/2012/WHO_IVB_12.03_eng.pdf [accessed 12 September 2012]
7. Maire N, Shillcutt SD, Walker DG, Tediosi F, Smith TA. Cost-effectiveness of the introduction of a pre-erythrocytic malaria vaccine into the expanded program on immunization in sub-Saharan Africa: analysis of uncertainties using a stochastic individual-based simulation model of Plasmodium falciparum malaria. Value Health 2011;14:102838. doi:10.1016/j.jval.2011.06.004 PMID:22152171
8. Griffin JT, Hollingsworth TD, Okell LC, Churcher TS, White M, Hinsley W et al. Reducing Plasmodium falciparum malaria transmission in Africa: a model-based evaluation of intervention strategies. PLoS Med 2010;7:pii: e1000324. doi:10.1371/journal.pmed.1000324 PMID:20711482
9. Doolan DL, Dobano C, Baird JK. Acquired immunity to malaria. Clin Microbiol Rev 2009;22:1336. doi:10.1128/CMR.00025-08 PMID:19136431
10. Marsh K, Kinyanjui S. Immune effector mechanisms in malaria. Parasite Immunol 2006;28:5160. doi:10.1111/j.1365-3024.2006.00808.x PMID:16438676
11. Hutubessy R, Henao AM, Namgyal P, Moorthy V, Hombach J. Results from evaluations of models and cost-effectiveness tools to support introduction decisions for new vaccines need critical appraisal. BMC Med 2011;9:55. doi:10.1186/1741-7015-9-55 PMID:21569407
12. Maire N, Tediosi F, Ross A, Smith T. Predictions of the epidemiologic impact of introducing a pre-erythrocytic vaccine into the expanded program on immunization in sub-Saharan Africa. Am J Trop Med Hyg 2006;75:1118. PMID:16931822
13. Moorthy VS, Ballou WR. Immunological mechanisms underlying protection mediated by RTS,S: a review of the available data. Malar J 2009;8:312. doi:10.1186/1475-2875-8-312 PMID:20042088
14. Walker DG, Hutubessy R, Beutels P. WHO Guide for standardisation of economic evaluations of immunization programmes. Vaccine 2010;28:23569. doi:10.1016/j.vaccine.2009.06.035 PMID:19567247
(Submitted: 16 May 2012 Revised version received: 30 August 2012 Accepted: 3 September 2012 Published online: 19 September 2012 )