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    Figure 1.

    Total number of disability-adjusted life years (DALYs) averted after introducing the vaccine (reference case scenario).

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    Figure 2.

    Direct cost structure (vaccine price per dose = US $1).

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    Figure 3.

    Total number of drug treatments under different interventions.

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    Figure 4.

    Relationship between cost-effectiveness ratios and vaccine price over the entire 20-year intervention period. DALY = disability-adjusted life year.

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    Figure 5.

    Cost-effectiveness ratios for different time periods and vaccine prices. DALY =disability-adjusted life year.

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    Figure 6.

    Number of disability-adjusted life years (DALYs) averted due to vaccine introduction in different transmission settings.

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    Figure 7.

    Total number of disability-adjusted life years (DALYs) averted at different levels of vaccine efficacy.

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    Figure 8.

    Total disability-adjusted life years (DALYs) averted at different levels of vaccine efficacy decay (half-life).

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    Figure 9.

    Total disability-adjusted life years (DALYs) averted under different assumptions about heterogeneity in initial efficacy.

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    Figure 10.

    Disability-adjusted life years (DALYs) averted under different assumptions about vaccine coverage.

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PREDICTING THE COST-EFFECTIVENESS OF INTRODUCING A PRE-ERYTHROCYTIC MALARIA VACCINE INTO THE EXPANDED PROGRAM ON IMMUNIZATION IN TANZANIA

FABRIZIO TEDIOSISwiss Tropical Institute, Basel, Switzerland

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GUY HUTTONSwiss Tropical Institute, Basel, Switzerland

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NICOLAS MAIRESwiss Tropical Institute, Basel, Switzerland

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THOMAS A. SMITHSwiss Tropical Institute, Basel, Switzerland

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AMANDA ROSSSwiss Tropical Institute, Basel, Switzerland

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MARCEL TANNERSwiss Tropical Institute, Basel, Switzerland

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We model the cost-effectiveness of the introduction of a pre-erythrocytic malaria vaccine into the Expanded Program on Immunization. We use a dynamic stochastic simulation model of the epidemiology of Plasmodium falciparum in malaria-endemic areas and of case management in Tanzania. We consider a range of vaccine characteristics and a range of transmission settings. At low vaccine prices, the cost-effectiveness of such vaccines may be similar to that of other established preventative and curative interventions against malaria. The cost-effectiveness ratio increases rapidly and approximately linearly with vaccine cost per dose. The approach can be adopted for comparative analyses of the cost effectiveness of different vaccines and other intervention strategies.

INTRODUCTION

The goal of economic evaluation of healthcare interventions in general, and malaria control measures in particular, is to provide policy makers with guidance about how scarce resources can be allocated so that the social and economic benefits are maximized.1,2 Economic evaluation not only shows how efficient it is to spend resources on existing interventions available, but also predicts how efficient new interventions could be if they were to be developed, or if existing interventions had different characteristics. Thus, economic evaluation is an essential part of the appraisal of candidate malaria vaccines. For example, policy makers may wish to know how efficacious a vaccine would need to be to be cost-effective.

Cost-effectiveness analysis (CEA) usually is the method of choice in evaluating alternative health interventions because health decision makers are primarily interested to know what health improvements can be bought with a given budget, and not the overall economic impact per se.1,2 The present paper models the cost-effectiveness of a pre-erythrocytic malaria vaccine, using a dynamic stochastic simulation model of the epidemiology of Plasmodium falciparum in malaria-endemic areas and of case mangement in Tanzania.3,4 Our objective is to assess the potential cost-effectiveness of introducing this malaria vaccine into the Expanded Program on Immunization (EPI) under a range of scenarios, conditions, and assumptions.

We present the vaccine cost-effectiveness for one country, Tanzania. This first stage enables us to specify model inputs without having to consider simultaneously many heterogeneous settings, as would be the case for sub-Saharan Africa. Even one country does not present a single uniform context for ecologic, epidemiologic, socioeconomic, and health system inputs, but there is less heterogeneity than at the multi-country level.

MATERIALS AND METHODS

Perspective and boundary.

The study is a CEA adopting a societal perspective for both costs and effects, and thus considers all relevant resource inputs to the intervention, and resource consequences and health impacts resulting from the intervention. The costs of vaccine delivery4 include all resource inputs irrespective of whether these costs are borne by government, donors, the patient, the wider community, or a mixture of these. Case management costs3 likewise include all resource inputs irrespective of whether these are borne by government, the patient, or both. Vaccine delivery costs and case management costs include both the direct costs of service provision and costs directly associated with the service, which essentially means the costs for the patient(s) accessing the services, covering additional transport and sustenance costs.

A societal perspective in CEA also requires that direct economic impacts of the intervention should be taken into account. In the case of a vaccine that reduces morbidity episodes as well as mortality, there is a clear impact on productive time either leading to higher income (in the case of market work) or higher unsold production (in the case of non-market work). This can either be through a gain in production of the averted malaria case, or where the patient is a child, the production gained of the care giver who would have cared for the averted malaria case. Therefore, the results include these hypothesized economic impacts.

Given the dynamic nature of the epidemiologic model, and the lower transmission rates to other non-vaccinated individuals associated with an effective vaccine, the health effects of the intervention can also include changes in morbidity and mortality of the non-vaccinated population as a result of reduced transmission. However, our epidemiologic analysis implies that these impacts will be minimal in the epidemiologic settings that we have analyzed.5

Model overview.

To predict the cost-effectiveness of the malaria vaccine, we use a stochastic simulation model of the epidemiology of P. falciparum in malaria-endemic areas of Africa.6 This includes a sub-model for the case management of malaria in Tanzania.3 We link these elements with costing of vaccine delivery in the Tanzania setting.4

The epidemiologic model is a stochastic individual-based simulation of malaria infection in disease-endemic areas that uses a five-day time step. It takes as its input the pattern of the entomologic inoculation rate (EIR) in the absence of interventions, with separate values of the EIR specified for each of the 73 five-day periods during the year. We simulate the reference case management scenario in Tanzania3 to provide a baseline with which to compare simulations where a vaccine is introduced.

The simulated population is maintained as a steady state, and includes individuals of all ages, with immune status depending on their simulated exposure. The denominators for calculation of overall health impacts include individuals who were too old to be vaccinated, and 20-year simulation is thus influenced by cohort effects due to gradual increase in the proportion of the population vaccinated, and by dynamic effects of reduction in exposure on acquisition of natural immunity to asexual parasites.

Alternatives being compared.

We compare health outcomes, direct costs, and productivity gains of a combined strategy of a new malaria vaccine delivered through EPI in combination with the reference case management scenario for Tanzania with only the reference case management scenario.3 The EPI was chosen as the channel for vaccine delivery because in most African countries EPI is well established and achieves reasonably high levels of coverage amongst the target population group. Therefore, it is the only reliable mechanism to deliver a vaccine to a high proportion of infants less than one year of age.79

The vaccine modeled is a pre-erythrocytic stage vaccine requiring three doses to fully immunize a child. These doses are administered when infants are one, two, and three months of age, at the same time as the hepatitis B vaccine. Many of the inputs for the CEA are based on data from the case management model3 and epidemiologic scenarios.10

The cost-effectiveness model simulates the health system typical for a rural area of Tanzania.3 A set of different scenarios were constructed to reflect different malaria transmission intensities representing the stable, annually recurring pattern of malaria transmission. In all simulations, the seasonal pattern of transmission was assumed to be that recorded in the village of Namawala, Tanzania during 1989–1991 where exceptionally precise estimates of dry season transmission were made.11 The annual EIR for this site was 329 infectious bites per year. For the reference scenario, we use a seasonal pattern of transmission for a mesoendemic site, which was obtained by dividing the EIR from Namawala for each five-day period by 16. Direct measurement of dry-season transmission in mesoendemic areas is impracticable because of low mosquito densities. To simulate a high-transmission area, we use an EIR four times that of the reference scenario. This is probably more typical of high-transmission sites in Africa than the extremely high transmission in Namawala. This gives an overall annual EIR of 21 infectious bites per year, which is typical for a mesoendemic area in sub-Saharan Africa.12 The simulations were first run for a warm-up period of 90 years of exposure to define the baseline immune status of the simulated populations, which is highly age dependent. For the present analyses, the simulations are run in populations of 100,000 individuals, with an approximately stationary age distribution matching that of the demographic surveillance site in Ifakara.13

Measuring health gains.

To estimate the number of disability-adjusted life years (DALYs), years of life lived with disability are calculated on the basis of the duration of disability and respective disability weights.3,14 Weights for different malaria attributable disease conditions have been obtained from the global burden of disease (GBD) study,15 and age-weighting is applied as in the GBD method. However, to assess how sensitive results are to the life table used, DALYs are also computed assuming a zero age weighting. The disability associated with anemia is assigned to the same time period as the malaria infections causing it.

Years of life lost (YLLs) and DALYs are calculated assuming age-specific life expectancies based on the life table from Butajira, Ethiopia, with an average life expectancy of 46.6 years at birth.16 This life table represents that of an east African setting with low malaria transmission and is very similar to that for Hai District, a high altitude and low malaria prevalence site in Tanzania.13 We thus compute YLLs for each simulated death under the assumption that this life table would apply in the absence of malaria.

Assumptions on vaccine efficacy.

In the reference scenario, the efficacy of this hypothetical pre-erythrocytic malaria vaccine is assumed to be 52% reduction in infections in naive individuals,10 decaying exponentially with a half-life of 10 years. Since it is likely that the degree of protection provided varies between individuals, in the reference scenario, a value for the initial efficacy is drawn from a beta distribution with parameter b =10 and assigned to each vaccinated individual.5

Coverage.

In the reference scenario, it is assumed that the coverage rate is the same as that reported in Tanzania for three doses of diphtheria tetanus pertussis–hepatitis B virus (DTP-HBV) vaccine in the year 2003, which stood at 89%. Given that the coverage for the first dose of DTP-HBV vaccine was 95%, the dropout rate from the first to the third dose is 6%.4

Case management.

The case management model, including both formal and informal treatment, is described elsewhere.3 It has implications for health outcomes, both in terms of the potential to reduce rates of severe disease, sequelae and death, but also in the impact on transmission intensity and therefore the potential for new infections in the entire population. The rate of treatment seeking among uncomplicated malaria episodes was assumed to be 5%, which although apparently low, is justified due to the very sensitive definition of clinical episodes used. The clinical episodes simulated thus include very mild fevers that would be unlikely to elicit attendance at a health facility. The model assumes in the reference case a cure rate of 93% for the first-line drug sulfadoxine-pyrimethamine (SP) for uncomplicated malaria.5

Costs presented.

We considered both marginal and average costs. The marginal cost reflects most closely the additional financial costs that would be incurred when introducing a new intervention. The average cost includes all those costs involved in delivering a health intervention, including the use of spare capacity or slack in the system, those health care resources diverted from other uses, and existing health sector resources that are shared with other health programs. All cost data are expressed in US$ 2004.

Vaccine delivery costs.

The costs of introducing a malaria vaccine into the EPI in Tanzania include those related to an assumed range of vaccine purchase costs, and data collected from Tanzania on likely distribution and cold chain storage costs, management costs, vaccine delivery costs at health facility level, training costs, and social mobilization costs. A detailed description of the methodology used to estimate vaccine delivery costs can be found in an accompanying paper.4

The CEA is run under various vaccine price hypotheses ranging from US $1.0 to US $20 per dose. The vaccine delivery cost estimates according to the different price hypotheses are shown in Table 1.

Case management costs.

The costs of treating those seeking health care for malaria episodes are calculated under the two scenarios being modeled: case management alone and vaccine with case management, which allow us to calculate expected cost savings associated with the introduction of an efficacious malaria vaccine.

The direct costs of care seeking for an uncomplicated malaria episode at official facilities include the cost of an outpatient visit (US $1.02 dispensary; US $1.27 health center), a diagnostic test in a proportion of outpatient cases (US $0.30), the cost of a course of SP treatment (varying from US $0.012 to US $0.071 depending on age and weight), the cost of a course of amodiaquine treatment (varying from US $0.018 to US $0.114 depending on age and weight), and other costs incurred by patients when visiting an official health facility (US $0.30).

The direct costs of a severe malaria patient include inpatient hotel costs per day (US $7.80), drug treatment cost during hospitalization (varying from US $0.56 to US $3.74 depending on age and weight), average length of stay (4.5 days with full recovery), and the costs that patients incur when visiting an official inpatient facility (US $1.29 for the average length of stay). The case management cost inputs are presented in detail elsewhere.3

Measuring productivity gains.

The productivity costs of malaria relate to the productive time lost due to illness, whether it is the patient or the patient care giver (especially if a child or elderly patient). In this analysis, productivity costs included are those related to time spent by adults seeking official care for their children, time spent by adults caring for children at home, and the time forgone by sick adults due to malaria episodes. Given that inclusion of productivity gains in CEA remains controversial, the reference case results do not include these hypothetical productivity gains.

To measure the value of productive time lost, we use the wage rate method that involves multiplying the time lost per episode (for adults only) by the average daily wage in Tanzania. These estimates are adjusted downwards by an estimate of the unemployment rate in Tanzania, thus taking into account that not all those sick or those caring for the sick would have been working.

The time lost per malaria episode is expected to be highly variable. For example, a recent review of the literature available found that for a sick adult the time off work ranges from one to five days, depending most importantly on severity of disease.17 For this study, uncomplicated adult malaria cases are assumed to lose two working days, while a care taker of a sick child loses one working day. Adults with a severe malaria episode are assumed to lose 4.5 days if not hospitalized, or if hospitalized, 1 day more than their length of stay in hospital. A care giver of a child with severe malaria is assumed not to be able to work during the hospitalization period.

For uncomplicated episodes, productivity costs are computed under two scenarios. In the first scenario, a productivity cost is attached to only those uncomplicated episodes that get treated, presumed to correspond in general to the more severe episodes. In the second scenario, a productivity cost is attached to all malaria episodes. These two scenarios represent the likely upper and lower bounds on the true productivity costs avertable through the introduction of an efficacious vaccine. The formulae for calculating productivity costs are presented below, and the data inputs are provided in Table 2.

Icu=Tcuw(1U)
Ics=Tcsw(1U)
Iau=Tauw(1U)
Ias=Tasw(1U)

where Icu and Ics are the productivity costs of the care taker for uncomplicated and severe malaria, respectively; Iau and Ias are the productivity costs of sick adults with uncomplicated and severe malaria, respectively; Tcu and Tcs are the time lost in days per episode by care taker of sick child for uncomplicated and severe malaria, respectively; Tau and Tas are the time lost in days for sick adults for uncomplicated and severe malaria, respectively; w is the minimum gross daily wage in Tanzania (US $3); and U is the assumed unemployment rate in Tanzania (40%).

Net cost calculations.

The net costs associated with current case management and adding the vaccine to case management is computed over time as follows:

NC=i=1n[ DC(cmv+v)tDC(cmnv)t(1+r)t ]

where NC is net costs including only direct costs; DC ( cmv + v) is the direct costs in the case of the vaccine plus case management; DC (cmnv) is the direct costs of current case management under a no vaccine scenario; n is the time period of intervention (20 years); and r is the annual discount rate for future costs and health effects.

Reference scenario.

In the reference case, results are presented to show cost-effectiveness at four different five-year time periods during the 20-year follow-up period (1–5 years, 6–10 years, 11–15 years, and 16–20 years) to reflect the possible fact that cost-effectiveness changes depending on time after vaccine introduction. The cost-effectiveness ratios (CERs) are presented under seven vaccine price assumptions (in US$): 1, 2, 4, 6, 8, 10, and 20. Incremental CERs are presented using two different definitions of cost: marginal cost to reflect the likely short-term financial impact of the intervention, and average cost to reflect the long-term and full opportunity cost associated with the intervention. In the reference case, only direct costs are included.

Incremental CERs are calculated under four health outcomes relevant for decision making: cost per episode averted, cost per DALY averted, cost per YLL, and cost per death averted. Future costs and benefits are presented both undiscounted and at a discount rate of 3% to reflect time preference.18

Sensitivity analysis.

In addition to the reference case data assumptions and scenarios, the sensitivity analysis runs these same simulations under different assumptions. The rationales for these scenarios and the epidemiologic patterns associated with them are described in the accompanying paper.5

The different transmission intensity patterns used are low stable transmission (Namawala/64, equivalent to 5.2 infectious bites per year and high transmission (Namawala/4, equivalent to 83 infectious bites per year). The reference case is an EIR of 21 infectious bites per year, corresponding to Namawala/16. The different levels of vaccine efficacy are 30%, 80%, and 100%. The reference case is 52% entered in the model. Different decay rates for the efficacy are half-lives of 6 months, 1 year, 2 years, 5 years, and 10,000 years. The reference case is 10 years. Different distributions of vaccine effect in the population are b equals 0.01 and 100,000. The reference case is 10. Different vaccine coverage rates are a low coverage rate, with 70% of the infants receiving their first dose, and 50% receiving their third dose and complete coverage, with 100% of the infants receiving three doses. The reference cases were 89% for the third dose and 95% for the first dose. Inclusion of productivity cost savings were low productivity costs, where those with uncomplicated episodes who do not seek care are assumed not to lose productive time and high productivity costs, where all those predicted by the model to have a malaria episode are assumed to lose productive time.

RESULTS

Reference case presentation.

Health effects.

Over 20 years, the number of uncomplicated episodes averted due to the introduction of the vaccine, in the simulated reference population of 100,000 people, is close to 192,485, which corresponds to a rate of 0.1 per capita per year, while the total number of severe episodes averted is 1,697, or 0.0008 per capita per year.5 These health effects represent only a small fraction of the total burden of disease because vaccinated children represent only a small proportion of the total population in the early years of the simulation. Since the reference scenario also assumes waning of vaccine-induced immunity, the protected proportion of the population is never very high and increases only gradually. Furthermore, vaccination with a pre-erythrocytic vaccine effectively postpones many illness episodes because it reduces acquisition of asexual stage immunity.

The number of deaths prevented over 20 years is 942. The number of undiscounted DALYs averted over 20 years is 58,579, which corresponds to a rate of 0.029 per capita per year. When DALYs are discounted at 3%, the number of DALY averted is 26,892, or 0.013 per capita per year. The number of undiscounted DALYs with no age weighting applied is 48,299 DALYs averted, or 0.024 per capita per year. Since most of these DALYs are due to the mortality effects, the number of YLL is very close to that of DALYs. Figure 1 presents the distribution of DALYs averted over the 20-year model period, indicating that the health effects of introducing the vaccine vary over time.

Table 3 shows that the number of uncomplicated episodes averted is higher in the second and third five-year time periods and lower in the first and fourth five-year time periods since the start of vaccination. Most of the severe episodes averted occur in the first 10 years of the intervention, with a sharp decrease in the third five-year period, even registering a higher number of severe episodes under vaccination scenario in the fourth five-year period. Also, a higher proportion of deaths prevented are concentrated in the first 10 years after vaccine introduction. When health outcomes are discounted, this effect is stronger.

Net costs.

The net cost of vaccine introduction for the 20-year period and at a vaccine price of US $1 per dose is US $447,391 or US $0.22 per capita per year (direct, undiscounted average costs). In the marginal cost analysis, these costs are 3% less at US $433,890. The reference case results are shown in Table 4 for discounted and undiscounted costs and at different vaccine price assumptions.

Figure 2 shows that the contribution of different cost components remains stable over the 20-year time period after introduction of the vaccine, comprising inpatient costs, out-patient costs, drug costs and patient costs. Before introduction of the vaccine, approximately 30% of direct costs are due to outpatient visits, approximately 10% to drugs, 40% to hospital care, and 20% to patient costs. After the introduction of the vaccine, more than 50% of total direct costs, at a vaccine price of US $ 1 per dose, would be due to the vaccine delivery costs. This proportion increases significantly as the vaccine price increases.

The number of first-, second-, and third-line drug treatments over time is lower after the introduction of the vaccine (Figure 3). The number of first-line drug treatments averted by the vaccine reaches a maximum in the second five-year interval, then decreases. The number of second- and third-line treatments averted is high in the first five-year period, after which it decreases to close to zero after 15 years. In the last five-year period, the number of first-, second-, and third-line drug treatment is higher when the vaccine is introduced. This is because in the last five-year period the vaccine does not prevent any severe episodes. There is also a shift in uncomplicated episodes to older ages, where higher drug costs are incurred due to the requirement for a greater dose.

Cost-effectiveness.

Cost-effectiveness ratios using undiscounted average cost are presented for the vaccine in Table 5 over the entire 20-year intervention period and by vaccine price. The cost per death averted by introducing the vaccine is US $475, under a vaccine price assumption of US $1 per dose, increasing to US $7,158 per death averted at a vaccine dose price of US $20. The CERs using the marginal cost are generally between 97% and 99% of the CERs at average cost. Furthermore, discounting costs and health effects makes only a marginal difference to the CER, as shown in Table 5.

The undiscounted cost per DALY averted by introducing the vaccine is US $8 under a vaccine price assumption of US $1 per dose, increasing to US $115 per death averted at a vaccine dose price of US $20. The effect of discounting increases the cost per DALY averted by approximately 50% to US $12 per DALY averted at a vaccine price of US $1 per dose. The effect of taking out the age weighting in the DALY calculation reduces the cost per DALY averted back towards undiscounted levels. Figure 4 shows the relationship between CERs (for deaths averted and DALYs averted) and vaccine price.

However, the presentation of CERs over the entire 20-year intervention period hides some important variations across five-year time intervals. Furthermore, variations in cost-effectiveness between the four different periods do not show a similar pattern across health outcome measures. Table 6 shows CERs for selected health outcomes over the four time intervals, and at different vaccine price assumptions.

The CERs for cost per death averted are similar in the first two five-year intervals, but considerably higher in the second two five-year intervals. At a vaccine price of US $1 per dose, the cost per death averted ranges between US $364 and US $601 over the four time intervals (Figure 5). The cost per death increases almost linearly with the vaccine price and at US $20 per dose it ranges between US $6,028 and US $9,332 per death averted at different time periods.

The undiscounted cost per DALY averted follows the same pattern over time as the cost per death averted, with a substantial difference between the first two five-year periods and the second two five-year periods (Figure 5). At vaccine price of US $1, the cost per DALY averted varied between US $6 and US $11 over time, but it increases with the vaccine price up to a range of US $92 to US $149 at US $ 20 per dose.

The discounted cost per DALY averted is higher, ranging between US $11 and US $16 at US $1 per dose (Figure 5). When DALYs are computed undiscounted and assuming zero age weighting, the average direct cost per DALY averted over the four time intervals ranges between US $7 and US $12 at this vaccine price. The cost per DALY averted by the vaccination program is thus lower in the first two five-year time periods than in the latter. The CER is much higher if both costs and DALYs are discounted at 3%, and excluding the age weighting from the DALY calculation leads to a cost effectiveness ratio that is somewhere in between.

Cost-effectiveness ratios for cost per episode averted demonstrate another pattern. Since most uncomplicated episodes are prevented a few years after vaccine introduction and before the end of the third five-year interval, the cost per uncomplicated episode averted is higher in the first and last five years (US $3 at a vaccine price of US $1 per dose) and lower in the second and third five-year periods (US $2 at a vaccine price of US $1 per dose). This finding is even stronger for the severe episodes since most are averted in the first 10 years, and in the last 5 years the number of severe episodes is higher in the vaccination scenario than under no vaccination. The cost per severe episode averted is US $106 in the first five-year period, US $123 in the second five-year period, and US $1209 in the third five-year period. In the fourth five-year period, the health effect is negative, thus giving a negative CER.

Effect of transmission intensity.

The number of deaths and DALYs averted in the first 10 years of the simulation is lower in a low-transmission setting (5.2 infectious bites per year) than in the reference scenario, while in a high-transmission setting (83 infectious bites per year) is close to the number reported in the reference scenario (Figure 6). However, in a high-transmission setting, almost all deaths prevented (approximately 90%) and DALYs averted (approximately 93%) occur in the first 10 years.

The cost per death averted and per DALY averted in a high-transmission setting is thus equal to that in the reference scenario in the first five-year period, but it is almost twice the cost per death averted in the second five-year period, and the CER then increases dramatically in the subsequent years (Table 7). In a low-transmission setting, the cost per death prevented and per DALY (both undiscounted and discounted) averted are twice as high as those in the reference scenario in the first five years, and lower in the subsequent years (Table 7).

Effects of different vaccine efficacy.

The cost-effectiveness simulations in the reference scenario assume that vaccination reduces the force of infection by 52%. Figure 7 shows the number of deaths averted over the 20-year period at different levels of vaccine efficacy. The effect on DALYs averted shows a similar pattern.

Table 7 shows the cost-effectiveness results under different efficacy assumptions. If the efficacy of the vaccine is 30% instead of 52%, the direct costs per death prevented and per DALY averted would be considerably higher, with the highest difference being in the second and third five-year periods where it is more than 200%. Increasing the efficacy to 80% would reduce the CERs by approximately 50% to between US $3 and US $6 per DALY averted and to between US $200 and US $400 per death averted. The cost-effectiveness of a completely efficacious vaccine would result in a considerable further improvement in the CER to US $1.4–$3.2 per DALY averted.

Effects of decay of efficacy.

The reference scenario assumes a half-life of protection against infection of 10 years. The cost-effectiveness simulations are run assuming different duration of vaccine protection from 6 months up to 10,000 years, approximating a non-decaying efficacy. The impact on DALYs averted is shown in Figure 8.

As expected, the longer the duration of efficacy the lower the CERs (Table 7). However, the improvements in cost effectiveness ratios are not linear. Improving the half-life from six months to five years leads to substantial improvements in the CER, but the differences in cost-effectiveness between 5 and 10 years efficacy duration are slightly smaller.

Effects of variation in vaccine efficacy between individuals.

The distribution of vaccine efficacy among the vaccinated infants has a moderate effect on the number of deaths and DALYs that can be averted introducing the vaccine. The two alternative scenarios modeled, assuming either an all-or-nothing response or complete heterogeneity, show that the more the efficacy is concentrated in a few vaccinated subjects, the more deaths and DALYs can be prevented. This finding is also reflected in the CERs that are more favorable than the reference case if b = 0.01 (i.e., efficacy concentrated among fewer individuals), and less favorable if the effect was completely dispersed (Figure 9).

Effects of the coverage rate.

The reference scenario assumes a fairly high vaccine coverage rate (89%) as reported in Tanzania for DTP-HBV vaccine in year 2003.4 We also simulate a coverage rate of 50%, which is likely to be closer to that in many malaria-endemic countries, and coverage of 100%, which allows us to analyze which effects are due to incomplete coverage. The cost-effectiveness simulations are thus run assuming a low coverage rate (50%) and complete coverage (100%). A lower coverage rate leads to significant reduction in the number of deaths and of DALYs averted over the 20-year simulation (Figure 10).

The cost per death prevented and per DALY averted assuming a coverage rate of 50% is between 20% and 50% higher than in the reference scenario in the central 10 years of simulation, and is slightly lower in the first and last five years (Table 7). A complete coverage would increase slightly the number of deaths prevented and more significantly the number of DALY averted compared to the reference scenario, while the cost per deaths and DALY averted would be slightly lower.

Inclusion of productivity costs.

The economic implications of reducing the burden of malaria go beyond the direct costs due to health care treatment. In the sensitivity analysis, we model the cost-effectiveness results including the productivity costs of productive time lost due to the disease. Results are presented for two assumptions of the proportion of malaria episodes where there is a productivity cost associated with the disease: the high productivity cost case where productivity costs are incurred by all episodes predicted by the epidemiologic model, and the low productivity cost case where there are no productivity costs associated with uncomplicated episodes unless the patient seeks treatment.

Over the entire 20-year follow-up period, introducing the vaccine would lead to savings in productivity costs of approximately US $263,634 in the high productivity cost scenario and US $28,443 in the low productivity cost scenario. However, since effects of the vaccine vary over time, the savings in productivity costs also vary over time (Table 8). Under the high productivity cost scenario, the savings in productivity costs reduce the total net cost of introducing the vaccine by between 49% and 90% in different time periods at a vaccine price of US $1 per dose. The savings are significantly reduced to an impact on total net cost of 3–4% when the vaccine price increases to US $20 per dose.

Under the low productivity cost scenario, the reductions in the net cost of introducing the vaccine are significantly lower than under the high productivity cost scenario. Total net cost reductions would occur only in the first three five-year periods, giving reductions of 5% to 7% and 5% at US $1 per dose and less than 1% at US $20 per dose. In the fourth five-year period, productivity costs would be higher with the vaccine. This leads to an increase in the net cost of introducing the vaccine in the last 10 years of follow-up.

As a consequence, the cost per DALY averted (discounted) is lower when productivity costs are included, as shown in Table 9. Under the high productivity cost scenario, the total cost per DALY averted would be between US $1.7 and US $8.1 at a vaccine price of US $1 per dose. These figures represent a reduction in cost per DALY averted of between 63% and 89% when compared to the CER containing only direct costs. However, since the vaccine price increases, the cost per DALY becomes closer to the reference case analysis CER. For example, at US $20 per dose, the cost per DALY averted would be between US $148 and US $227 in different time periods, which is similar to that including only direct costs.

DISCUSSION

We have used a stochastic simulation of P. falciparum epidemiology combined with a case management model for a Tanzanian setting3 to explore the potential cost-effectiveness of a pre-erythrocytic malaria vaccine. To our knowledge, this is the first time that dynamic models of malaria transmission and disease have been used to evaluate the cost-effectiveness of malaria vaccines. We have used vaccines with different characteristics introduced by the EPI in Tanzania to illustrate the approach. The models can readily be extended to other types of vaccine and to different epidemiologic and socioeconomic settings.

Over the vaccine price range of US $1.0 to US $20 per dose, the CER is almost proportional to the price per dose, ranging (in the reference analyses) between US $12 and US $190 per (discounted) DALY averted. In the sub-Saharan African context, CERs towards the lower end of this range would be very attractive for health ministries.18,19 Up to a vaccine price per dose of almost US $10, the cost per discounted DALY averted remains less than US $100. When productivity costs due to morbidity are included, our CERs are even lower than those estimated including only direct costs. However, this difference decreases with the increase of vaccine price. There is little difference between marginal and average costs, which means that substantial savings cannot be achieved by taking up spare capacity in the health system; thus, the cost of the vaccine is the major determinant of costs.

These results should be interpreted in the context of CEA of other malaria control strategies. At vaccine price towards the lower end of the range used, our cost-effectiveness estimates of vaccination compare favorably with those of several other malaria control interventions estimated for the Global Forum for Health Research (GFHR),20 but these comparisons are problematical because of differences in the methodology. Although the GFHR study used DALY calculations based on an African life table with similar life expectancies to those that we use, our models differ by including dynamic effects that result in age and time shifts in the burden of disease.

The indirect economic impact of malaria is clearly important and we aimed to capture these effects by including productivity costs in some analyses. However, there are many pitfalls in measuring potential or actual economic impact in the context of rural Africa where most of the population is subsistence farmers, child care is often performed by older siblings, work is seasonal, and work inputs may be shifted over time and between household members. We had no empirical studies available for our estimates of time use or on the impact of malaria episodes on productive capacity. Concerns about equity effects, inadequate data, or methods for estimating economic benefits mean that indirect costs are often excluded from CEA.2,17 Indirect costs were not included in the GFHR study,20 or in any other cost-effectiveness studies to date of malaria interventions, and were not included in the analyses underpinning World Health Organization guidelines for CER thresholds for considering health interventions as attractive or very attractive.18 Our analyses that include productivity costs are thus even less comparable with those of other studies.

A major impact of malaria on productivity is likely to be by the effects on premature mortality, but it is inappropriate to include in a CEA the costs of mortality, as available from estimates of life-time earnings forgone or willingness to pay studies, since this would result in double counting of the benefits of averting deaths.1,2,21 Among the microeconomic studies on the economic consequences of malaria published, only one22 has included productivity costs due to premature mortality. That study estimated the economic burden of malaria and not the cost-effectiveness of interventions.

A malaria vaccine may also have positive impacts on social and economic development that are not captured by the productivity cost savings. Endemic malaria is associated with substantially lower indices of economic development at the national level,23,24 and reducing the burden of malaria might have macroeconomic benefits that are not captured in microeconomic analyses. However the epidemiologic analyses5 clearly indicate that on their own vaccine programs with profiles like those we investigated will avert a proportion of illness events that is much lower than the primary vaccine efficacy, and will have little or no effect on malaria endemicity. In this context, it would be surprising if they had substantial effects on economic development.

We obtain only modest estimates of the wider economic benefits of a vaccination program if we apply the recently suggested approach25 of estimating these benefits by multiplying the number of DALYs averted by the average GDP per capita. Using our prediction that a pre-erythrocytic malaria vaccine would avert between 0.013 and 0.029 DALYs per capita per year and the GDP per capita of Tanzania (US $322 in 2005), the annual per capita economic benefits would be between US $4.2 and US $9.3 (according to whether DALYs are discounted and aged weighted).

These conclusions reflect the reference case, but the CER is highly sensitive to assumptions about the epidemiologic setting and vaccine characteristics including the transmission intensity, the efficacy, and duration of protection (Table 7). The CER varied with the time since the start of the vaccination program because the epidemiologic model does not reach equilibrium within the time scale of the simulation.5 In general, the cost per DALY averted is lower in the first phase of the vaccination program than later, with the highest cost per DALY in the third five-year time period after the start of the program. Extending the duration of protection increases the CERs in the third and fourth five-year time periods. A vaccine boost at some specified time point may have a similar effect, although this would involve additional costs that would be included in calculation of the CER. We have not addressed the emerging problem of drug resistance, which could be included in the case management model and would presumably increase the cost per DALY averted.

Our simulations considered only a limited set of sources of heterogeneity. In particular, we assumed that each person in the simulation was exposed to the same entomologic challenge, and that the chances of being vaccinated were independent of individual susceptibility to disease. We also assumed homogeneous probabilities of accessing health care. Over a period of 20 years, the introduction of a new malaria vaccine would have an impact on the health system and on the case management of malaria. It would be possible to simulate more realistic patterns of heterogeneity but the field data on which to base such models are very limited.

Some counter-intuitive behavior in CERs corresponds to health effects in the model. When episodes are delayed rather than averted, they occur in older individuals who may require larger drug dosages. Thus, the health benefit of delaying illness may be partially offset by increased costs. Since the epidemiologic model also corresponds with field data that suggests a maximum incidence of clinical episodes (though not mortality) at intermediate transmission intensities,2629 it is possible for reductions in malaria transmission to lead to increased case loads.

The proportion of clinical episodes averted varies by transmission intensity,5 as do the numbers of DALYs averted. The numbers of clinical episodes continues to decrease after 10 years of the vaccine introduction only in low-transmission scenarios. This is explained by the fact that in high-transmission settings there is an increase in severe malaria incidence in children more than five years of age due to reduced accrual of immunity to asexual blood stage parasites during early childhood. In addition, the pyrogenic threshold, which determines the parasite density that leads to acute illness, depends on the recent exposure to parasite and can be lower in vaccinated individuals.10 In the model, the lower level of acquired immunity in vaccinated individuals and the resulting inability to effectively control parasite densities also leads to higher proportion of the acute episodes being severe.

An extension to the current work will be to carry out a full probabilistic sensitivity analysis. This will enable us to present acceptability curves in addition to the presentation of CERs in this report. However, the present analyses already indicate that a pre-erythrocytic malaria vaccine, even one with moderate efficacy and minimal effectiveness in reducing transmission to the vector, could be a cost-effective intervention in reducing the intolerable burden of malaria in sub-Saharan Africa.

Table 1

Incremental delivery cost per fully immunized child (FIC) for the vaccine

Vaccine delivery cost per FIC in US$
Vaccine price (US$ per dose) Average cost Marginal cost
1 4.43 4.24
2 7.43 7.24
4 13.43 13.24
6 19.43 19.24
8 25.43 25.24
10 31.43 31.24
20 61.43 61.24
Table 2

Data inputs for calculation of productivity costs*

Item Value (US$ 2004)
* UM = uncomplicated malaria; SM = severe malaria.
Caretaker UM 1.8
Caretaker SM if patient dies 3.6
Caretaker SM if patient fully recovers 8.1
Caretaker SM if patient recovers with sequelae 18.0
Sick adult UM 3.6
Sick adult SM if patient dies 5.4
Sick adult SM if patient fully recovers 9.9
Sick adult SM if patient recovers with sequelae 18.0
Table 3

Comparison of discounted and undiscounted health outcomes over the four five-year time periods after the vaccine introduction*

Time period (years)
1–5 6–10 11–15 16–20
* YLL = years of life lost; DALYs = disability-adjusted life years.
Uncomplicated episodes averted 31,289 65,810 59,187 36,199
Severe episodes averted 979 867 96 −245
Deaths averted 275 292 193 182
Deaths averted (discounted) 256 236 134 110
YLL averted 16,731 18,454 12,035 11,655
DALYs averted (undiscounted) 17,083 18,426 11,699 11,370
DALYs averted (discounted) 8,507 8,741 5,036 4,608
DALYs averted (unweighted, undiscounted 13,657 14,953 9,933 9,755
Table 4

Net costs in thousand US$, reference case (year 2004)*

Period
Years 1–5 Years 6–10 Years 11–15 Years 16–20
Vaccine price per dose Discounting AC MC AC MC AC MC AC MC
* AC = average cost; MC = marginal cost; Neg = negative. Each figure is the predicted cost for a total population of 100,000 people over the five-year period.
1 Undiscounted 104 104 211 210 327 320 447 434
Discounted 97 48 183 182 263 259 336 327
2 Undiscounted 186 182 Neg 366 575 734 779 749
Discounted 173 121 Neg 318 464 593 586 565
4 Undiscounted 350 337 706 680 1,072 1,028 1,441 1,378
Discounted 326 265 612 590 866 832 1,088 1,041
6 Undiscounted 513 492 1,035 993 1,568 1,500 2,104 2,008
Discounted 478 410 899 862 1,268 1,214 1,589 1,518
8 Undiscounted 677 648 1,365 1,307 2,065 1,971 2,767 2,637
Discounted 630 555 1,185 1,134 1,670 1,595 2,091 1,994
10 Undiscounted 840 803 1,695 1,620 2,561 2,443 3,429 3,267
Discounted 783 700 1,471 1,406 2,072 1,977 2,592 2,471
20 Undiscounted 1,658 1,580 3,345 3,187 5,044 4,802 6,742 6,414
Discounted 1,545 1,423 2,903 2,766 4,083 3,887 5,100 4,853
Table 5

Cost-effectiveness (average cost) of the vaccine over 20-year intervention period, by vaccine price*

Vaccine price per dose, in US$ (year 2004)
Outcome 1 2 4 6 8 10 20
* DALY = disability-adjusted life year.
Cost per death averted
    Undiscounted 475 827 1,530 2,234 2,937 3,640 7,158
    Discounted 456 796 1,477 2,158 2,840 3,521 6,926
Cost per DALY averted
Undiscounted 8 13 25 36 47 59 115
    Discounted 12 22 40 59 78 96 190
    Undiscounted, unweighted 9 16 30 44 57 71 140
Table 6

Cost-effectiveness ratios for selected health outcomes disaggregated by five-year time intervals and vaccine price*

Cost-effectiveness ratios (direct cost) for different health outcomes
Uncomplicated episodes averted Severe episodes averted Deaths prevented DALYs averted (undiscounted) DALYs averted (discounted) DALYs averted (undiscounted, unweighted)
Vaccine price per dose (US$) Time interval (years) AC MC AC MC AC MC AC MC AC MC AC MC
* DALYs = disability-adjusted life years; AC = average cost; MC = marginal cost; Neg = negative.
1 1–5 3 3 106 106 379 378 6 6 11 11 8 8
6–10 2 2 123 122 364 362 6 6 10 10 7 7
11–15 2 2 1,209 1,152 601 573 10 9 16 15 12 11
16–20 3 3 Neg Neg 663 625 11 10 16 15 12 12
2 1–5 6 6 190 186 676 661 11 11 20 20 14 13
6–10 3 3 219 213 649 632 10 10 17 17 13 12
11–15 3 3 2,077 1,977 1,033 983 17 16 27 26 20 19
16–20 6 5 Neg Neg 1,119 1,058 18 17 26 25 21 20
4 1–5 11 11 357 344 1,271 1,226 20 20 38 37 26 25
6–10 5 5 411 395 1,219 1,174 19 19 33 32 24 23
11–15 6 6 3,813 3,626 1,897 1,803 31 30 50 48 37 35
16–20 10 10 Neg Neg 2,032 1,925 33 31 48 46 38 36
6 1–5 16 16 524 503 1,866 1,790 30 29 56 54 38 36
6–10 8 8 603 578 1,789 1,715 28 27 48 46 35 33
11–15 9 9 5,549 5,275 2,760 2,624 46 43 73 70 54 51
16–20 15 14 Neg Neg 2,944 2,792 47 45 70 66 55 52
8 1–5 22 21 691 662 2,460 2,355 40 38 74 71 50 47
6–10 10 10 794 760 2,359 2,256 37 36 63 61 46 44
11–15 12 11 7,285 6,924 3,623 3,444 60 57 96 92 70 67
16–20 19 18 Neg Neg 3,857 3,659 62 59 91 87 72 68
10 1–5 27 26 858 820 3,055 2,920 49 47 92 88 62 59
6–10 13 12 986 942 2,928 2,798 46 44 79 75 57 55
11–15 15 14 9,020 8,573 4,487 4,264 74 70 119 113 87 83
16–20 24 23 Neg Neg 4,769 4,526 76 72 113 107 89 84
20 1–5 53 50 1,693 1,614 6,028 5,745 97 92 182 173 121 116
6–10 26 24 1,946 1,854 5,777 5,504 92 87 155 148 113 107
11–15 29 27 17,700 16,818 8,804 8,366 145 138 234 223 171 163
16–20 47 45 Neg Neg 9,332 8,860 149 142 221 210 174 165
Table 7

Cost-effectiveness ratios under different scenarios in the sensitivity analysis (US$, year 2004, using average costs, vaccine price US$1 per dose)*

Price = 1 Cost per DALY averted Cost per death prevented
Scenario/time period 1–5 6–10 11–15 16–20 1–5 6–10 11–15 16–20
* DALY = disability-adjusted life year; Neg = a negative cost-effectiveness ratio.
† b is the parameter of the beta distribution used to model variation between individuals in the efficacy of the vaccine.
Reference case Undiscounted 6.1 5.8 9.9 10.6 378.9 364.5 601.4 663.1
Discounted 11.4 9.8 16.0 15.7 379.6 362.4 599.7 657.4
Undiscounted 7.6 7.1 11.7 12.4
Low transmission Undiscounted 13.0 4.7 8.8 7.4 845.4 293.7 579.9 512.1
Discounted 25.3 7.4 13.3 9.8 421.8 122.7 104.4 74.7
Undiscounted 16.2 5.9 10.6 9.0
High transmission Undiscounted 5.5 9.5 309.7 68.1 339.4 559.4 4,965.7 3,281.7
Discounted 10.6 16.2 Neg 725.7 234.7 171.3 146.9 97.7
Undiscounted 6.8 11.4 128.3 59.4
Half-life 6 months Undiscounted 12.6 13.5 Neg 17.8 744.8 795.9 9,798.5 1,067.5
Discounted 23.5 23.0 Neg 21.3 729.1 779.5 8,568.5 1,079.5
Undiscounted 15.8 16.5 827.8 22.3
Half life 1 year Undiscounted 9.9 22.4 37.9 13.9 618.6 1,332.0 2,080.8 909.2
Discounted 18.5 41.5 62.5 19.4 607.5 1,299.3 2,212.6 938.3
Undiscounted 12.3 26.4 42.8 16.7
Half-life 2 years Undiscounted 6.4 9.2 19.3 9.3 401.4 552.9 1,201.0 554.8
Discounted 12.0 15.6 31.7 12.4 391.9 548.0 1,212.3 555.7
Undiscounted 8.1 11.2 22.8 11.2
Half-life 5 years Undiscounted 5.5 8.2 13.1 11.8 336.7 517.3 804.0 761.3
Discounted 10.3 14.0 21.3 16.8 336.1 514.1 801.5 766.2
Undiscounted 6.9 10.0 15.3 13.9
Half-life 10,000 years Undiscounted 5.2 4.5 11.2 6.2 323.0 287.3 673.8 406.0
Discounted 9.9 7.5 18.1 8.6 321.6 285.7 671.4 403.8
Undiscounted 6.5 5.6 5.6 5.6
Efficacy 30% Undiscounted 9.7 14.1 26.8 15.7 625.9 917.9 1,706.5 1,080.6
Discounted 18.2 23.7 45.1 23.6 622.1 921.1 1,768.3 1,092.1
Undiscounted 12.1 17.5 30.9 18.7
Efficacy 80% Undiscounted 3.5 3.0 5.0 6.2 219.9 187.3 318.9 407.2
Discounted 6.7 5.0 7.9 9.5 222.4 184.8 315.2 408.5
Undiscounted 4.3 3.7 3.7 3.7
Efficacy 100% Undiscounted 1.9 1.4 2.8 3.2 120.2 89.8 175.4 205.4
Discounted 3.7 2.3 4.3 4.5 121.5 89.3 173.8 204.7
Undiscounted 2.4 1.8 3.3 3.7
Coverage 50% Undiscounted 5.1 6.8 15.6 8.2 325.0 437.8 916.2 529.1
Discounted 9.7 11.7 27.3 11.8 326.6 441.3 934.5 535.8
Undiscounted 6.4 8.3 17.3 9.8
Coverage 100% Undiscounted 5.7 5.0 11.6 8.0 355.0 316.3 698.8 517.0
Discounted 10.7 8.3 18.4 11.2 354.6 310.7 689.7 512.8
Undiscounted 7.1 6.2 13.7 9.6
b = 0.01† Undiscounted 4.0 4.3 5.7 7.6 253.1 272.1 354.6 503.3
Discounted 7.5 7.2 8.6 10.9 254.4 269.6 350.2 506.1
Undiscounted 4.6 4.8 6.6 8.6
b = 100,000† Undiscounted 5.4 6.8 17.9 15.3 348.1 430.5 1056.4 980.9
Discounted 10.2 11.7 31.3 27.5 324.9 345.5 733.5 587.5
Undiscounted 6.7 8.4 8.4 8.4
Table 8

Hypothetical value of production time gained due to less time spent ill after vaccine introduction (US$, year 2004)

High productivity cost scenario Low productivity cost scenario
Time period (years) Undiscounted Discounted Undiscounted Discounted
1–5 63,478 57,173 15,260 14,074
6–10 124,743 98,807 18,603 15,114
11–15 105,779 72,440 6,238 4,407
16–20 59,366 35,214 −8,771 −5,153
Table 9

Cost per DALY averted including direct and productivity costs (US$, year 2004)*

Cost per discounted DALY averted
Vaccine price per dose Time period (years) High productivity cost scenario Low productivity cost scenario
* DALY = disability-adjusted life year; Neg = cost saving and a health benefit.
1 1–5 3.98 9.76
6–10 Neg 8.07
11–15 1.66 15.12
16–20 8.12 16.80
2 1–5 13.50 18.72
6–10 6.15 15.73
11–15 13.88 26.61
16–20 19.60 27.59
4 1–5 32.55 36.63
6–10 22.44 31.05
11–15 38.31 49.59
16–20 42.56 49.18
6 1–5 51.60 54.54
6–10 38.73 46.37
11–15 62.75 72.56
16–20 65.51 70.77
8 1–5 70.65 72.46
6–10 55.02 61.69
11–15 87.18 95.54
16–20 88.47 92.36
10 1–5 89.70 90.37
6–10 71.32 77.01
11–15 111.61 118.52
16–20 111.43 113.95
20 1–5 180.41 179.93
6–10 148.91 153.62
11–15 227.97 233.40
16–20 220.77 221.91
Figure 1.
Figure 1.

Total number of disability-adjusted life years (DALYs) averted after introducing the vaccine (reference case scenario).

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 2.
Figure 2.

Direct cost structure (vaccine price per dose = US $1).

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 3.
Figure 3.

Total number of drug treatments under different interventions.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 4.
Figure 4.

Relationship between cost-effectiveness ratios and vaccine price over the entire 20-year intervention period. DALY = disability-adjusted life year.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 5.
Figure 5.

Cost-effectiveness ratios for different time periods and vaccine prices. DALY =disability-adjusted life year.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 6.
Figure 6.

Number of disability-adjusted life years (DALYs) averted due to vaccine introduction in different transmission settings.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 7.
Figure 7.

Total number of disability-adjusted life years (DALYs) averted at different levels of vaccine efficacy.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 8.
Figure 8.

Total disability-adjusted life years (DALYs) averted at different levels of vaccine efficacy decay (half-life).

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 9.
Figure 9.

Total disability-adjusted life years (DALYs) averted under different assumptions about heterogeneity in initial efficacy.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

Figure 10.
Figure 10.

Disability-adjusted life years (DALYs) averted under different assumptions about vaccine coverage.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 2_suppl; 10.4269/ajtmh.2006.75.131

*

Address correspondence to Thomas A. Smith, Swiss Tropical Institute, Socinstrasse 57, Postfach, CH-4002 Basel, Switzerland. E-mail: Thomas-A.Smith@unibas.ch

Authors’ address: Fabrizio Tediosi, Guy Hutton, Nicolas Maire, Thomas A. Smith, Amanda Ross, and Marcel Tanner, Swiss Tropical Institute, Socinstrasse 57, Postfach, CH-4002 Basel, Switzerland, Telephone: 41-284-8273, Fax: 41-284-8105, E-mails: fabrizio.tediosi@unibas.ch, nicolas.maire@unibas.ch, Thomas-A.Smith@unibas.ch, amanda.ross@unibas.ch, guy.hutton@unibas.ch, and marcel.tanner@unibas.ch.

Acknowledgements: We thank the members of the Technical Advisory Group (Michael Alpers, Paul Coleman, David Evans, Brian Greenwood, Carol Levin, Kevin Marsh, F. Ellis McKenzie, Mark Miller, and Brian Sharp), the Project Management Team at the Program for Appropriate Technology in Health (PATH) Malaria Vaccine Initiative, and GlaxoSmithKline Biologicals S.A. for supporting this study.

Financial support: The mathematical modeling study was supported by the PATH Malaria Vaccine Initiative and GlaxoSmithKline Biologicals S.A.

Disclaimer: This publication and the contents hereof do not necessarily reflect the endorsement, opinion, or viewpoints of the PATH Malaria Vaccine Initiative or GlaxoSmithKline Biologicals S.A.

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Author Notes

Reprint requests: Thomas A. Smith, Swiss Tropical Institute, Socinstrasse 57, Postfach, CH 4002 Basel, Switzerland.
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