Willingness to pay for three hypothetical malaria vaccines in Nigeria

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Clinical Therapeutics/Volume 32, Number 8, 2010

August 2010 1533

Accepted for publication July 8, 2010.doi: 10.1016/j.clinthera.2010.07.0180149-2918/$ - see front matter

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ABSTRACTBackground: Unlike some African countries that have

reported a ~50% reduction in malaria deaths in recent years, Nigeria has shown no evidence of a systematic decline in malaria burden. An important and sustainable reduction in malaria burden cannot be achieved unless an effective and inexpensive malaria vaccine becomes available.

Objectives: The goals of this study were to determine the willingness to pay (WTP) for 3 hypothetical malaria vaccines with different levels of protection (in years), effectiveness, and adverse effects; and to identify factors that influence the price that people are willing to pay in Nigeria.

Methods: With the aid of a questionnaire, a contingent valuation method using payment cards was used to elicit WTP values for 3 hypothetical malaria vaccines. Payment cards contained both a description of the features of the vaccine being evaluated and price options. The 3 hypo-thetical vaccines had the following characteristics: vaccine A was 75% effective, protected for 3 years, and was well tolerated; vaccine B was 85% effective, protected for 6 years, and was less well tolerated than vaccine A; and vaccine C was 95% effective and protected for 12 years, but was the least well tolerated. Participants consisted of a convenience sample of individuals who were at the pharmacy waiting area of the state-owned hospitals located in Benin City and Warri, Nigeria. Every third patient or caregiver who was in the pharmacy to fill a prescription was asked to take part in the study as they waited to see the pharmacist. If consent was not granted, the next person in line was approached to be interviewed. Linear multiple regression analysis and nonparametric Kruskal-Wallis, Mann-Whitney, or χ2 test was applied in inferential analysis, where necessary, to investigate the effects of sociodemographic factors on WTP. Prices on payment cards were expressed in Nigerian naira (NGN 150.00 ≈ US $1.00), but study results were ex-pressed in US dollars.

Results: A total of 359 individuals aged ≥18 years of 500 who were approached agreed to participate in the study, giving a response rate of 71.8%. Most of the participants (216/359; 60.2%) were women, and 48 of them were pregnant. Most respondents (299/359; 83.3%) had at least one malaria attack within the last year, and 27.3% (98/359) were hospitalized for malaria. The mean WTP for vaccine A was $6.77 and that for vaccine B was $6.70. Vaccine C was the least well ac-cepted with a mean WTP of $5.06. Respondents were willing to pay significantly more for vaccine A (95% CI, $5.96–$7.57); thus, the WTP was significantly different for the 3 hypothetical malaria vaccines (P < 0.001; Kruskal-Wallis statistic [kw] = 84.304). Dunn’s multiple comparison test also indicated that the WTP values for vaccines A and B were significantly different from each other (P < 0.05). There was also a significant difference between vaccine A or B versus C (P < 0.001). All workers and those with a higher monthly income were willing to pay significantly more for vaccines A and B, but less for C (P < 0.003). Those who preferred vaccine A (198/359; 55.2%) were willing to back their choice with a higher WTP (P < 0.001).

Conclusions: It appears that although malaria is a serious disease, the Nigerian people in this sample preferred and were willing to pay more for a vaccine that was well tolerated, even if its effectiveness and duration of protection against malaria were lower than those of a product that caused severe adverse effects. Interpretation of this study should be guided by the knowledge that differences exist between the study sample and the general population. (Clin Ther. 2010;32:1533–1543) © 2010 Excerpta Medica Inc.

Willingness to Pay for Three Hypothetical Malaria Vaccines in Nigeria

Waka Anthony Udezi, MPharm; Cyril Odianose Usifoh, PhD; and Omoyeme Oluwatosin Ihimekpen, PharmD

Department of Clinical Pharmacy, Faculty of Pharmacy, University of Benin, Edo, Nigeria

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Clinical Therapeutics

are needed to guide financial strategies to ensure access and affordability for the majority of the population.

The aims of this study were to determine the WTP for 3 hypothetical malaria vaccines with different levels of protection (in years), effectiveness, and adverse ef-fects; and to identify factors that influence the price that people are willing to pay in Nigeria.

MeThodSStudy Sites

This study was conducted in 2 southern Nigerian cities, Benin City and Warri, where malaria transmis-sion occurs throughout the year. Benin City is a civil- servant town where most people work for the govern-ment or a federal university. There are few firms that are not government owned. Warri is an oil-rich city located in the Niger Delta area and has numerous multinational oil companies. Both cities have several private clinics and pharmacies, and each has a hospital owned by the state government. In addition, Benin City has a university teaching hospital and 2 missionary hospitals. The state-owned hospital in each city, which serves as a referral site for residents in the town and surrounding areas, was used as a study site. The study site in Benin City is located in the Oredo local govern-ment area, which has a population of 374,515; the site in Warri is in the Warri-South local government area, which has a population of 311,970. Males and females are equally distributed (1:1) in the 2 locations,13 and ~70.0% of the population is aged ≤29 years. In 2008, data from the Nigerian National Bureau of Statistics showed that 38.2% to 44.5% of citizens had access to untreated bore holes or hand pumps as a source of water for cooking, and 56.0% to 77.7% relied on electricity supplied from the national grid. In 2004, using a self-rating technique, it was reported that 83.1% of those living in Edo and the Delta States, where the study sites are located, were poor.

ParticipantsApproval for this study was obtained from the Min-

istries of Health of both states and the hospital admin-istrations after reviewing the research protocol. Each candidate was informed about the study and he or she provided verbal consent before recruitment; if a potential participant did not understand English, an interpreter who understood the local language was used.

Every third patient or caregiver who was in the pharmacy to fill a prescription was asked to take part in the

Key words: malaria, vaccine, willingness to pay, Nigeria, access, affordability.

INTRoduCTIoNFrom 2001 to 2007, the number of people who died from malaria increased from 4317 to 10,289 for all ages in Nigeria1; therefore, there is no evidence of a systematic decline in malaria burden in this country. In contrast, other African countries such as Rwanda and Eritrea have reported a ~50% reduction in malaria deaths.1,2

Spending for malaria can absorb most or all of the household budget for health, especially among the poor,3 and malaria therefore places a large burden on households that have a sick family member.4–6 The an-nual mean income in Nigeria is ~US $1766.00 (personal communication, Nigerian Ministry of Health, proposed recurrent expenditure, November 2009), and most unskilled workers earn only ~$440.00.7 Artemisinin-based combination therapy (ACT), which may contain lumefantrine and artemether, is the first-line antimalarial treatment recommended in Nigeria. Access and afford-ability are critical for optimal compliance with this strategy. However, ACT is expensive ($3–$8 for a com-plete treatment of one malaria episode) and is unaf- fordable for the lowest-paid, unskilled government workers in Benin City, Nigeria. An important and sustainable reduction in malaria burden cannot be achieved unless an effective and inexpensive vaccine becomes available.8

Development of a malaria vaccine has been difficult, possibly because of the difficulty in pinpointing the immune responses that protect against malaria.9,10 How- ever, there is reason to be optimistic that one or more of the scientific approaches being investigated may al-low a malaria vaccine to become available on a large scale in the near future.11,12

Willingness to pay (WTP) provides a measure of how much individuals value a health technology or interven-tion. To identify scientific investigations of the WTP for malaria vaccines, we conducted a literature search of MEDLINE for English-language articles using search terms such as willingness to pay and malaria vaccine, with no restriction on the dates of publication. Only one study of the WTP for a maternal and childhood malaria vaccine in an African country was identified.8 No information was given on the influence of different levels of tolerability and effectiveness on WTP or de-mand. Studies on WTP for a possible malaria vaccine

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ticipant had malaria, and whether the illness was treated in the hospital. Section B of the instrument consisted of detailed descriptions of 3 hypothetical malaria vac-cines (A, B, and C) with different attributes, including effectiveness, duration of protection against malaria, and possible adverse drug events (Table I). Vaccine A was the best tolerated with the least effectiveness value, whereas vaccine C was the most effective but carried the risk of death as an adverse event. Although a vaccine that causes a 10% risk of death can never be introduced, the justification for including vaccine C in the study was to ensure that participants would make tradeoffs between effectiveness (plus duration of protection) and adverse events. Bearing in mind that in real clinical settings, effective treatments are usually associated with higher costs, it would be valuable to find out whether vaccine C would emerge with the highest WTP value despite the risk of death.

A contingent valuation technique was used to derive the maximum amount of money each respondent was willing to pay for each vaccine. A hypothetical scenario was presented as follows: “Suppose there are now 3 dif-ferent vaccines against malaria; vaccine A can protect you against malaria for 3 years and it is 75% effective. It causes pain at the site of injection and a slight fever for 24 hours. What is the maximum price that you are willing to pay for this vaccine?” Similar scenarios were used to describe the respective characteristics of vaccines B and C.

Different price options (in Nigerian naira [NGN]; NGN 150.00 ≈ US $1.00 at the time of writing the paper) were written on payment cards, which also contained a description of the features of the vaccine being evaluated; prices ranged from NGN 100.00 ($0.67) to NGN 8000.00 ($53.33). The presented prices

study as they waited to see the pharmacist. If consent was not granted, the next person in line was approached to be interviewed.

Study Instrument and data CollectionA questionnaire was used to conduct the interviews.

Because a literature search did not identify more than one scientific article dealing with the subject under investigation, we had no way of identifying important variables that would influence the WTP for a malaria vaccine; therefore, we assembled a panel of local malaria experts. These health care providers each had a minimum of 5 years’ practice experience and included 2 general practice physicians, 2 community pharmacists, and a nurse. The panel and the researchers carefully identified, debated, and selected possible variables that were hy-pothesized to have an influence on WTP for inclusion in our instrument. For example, our expert panel be-lieved that those who have frequent malaria attacks (eg, pregnant women)14 and those who spend more money on malaria treatment are likely to pay more for a malaria vaccine. The logic is that a patient will prefer to purchase a treatment that will reduce the number of malaria ill-nesses to avoid work disruptions due to hospitalization. Pain and suffering of both the patient and family mem-bers (who are usually caregivers) will thus be averted. Therefore, inclusion or exclusion of an item depended on whether it would affect the treatment cost of malaria.

The instrument consisted of 2 sections. Sociodemo-graphic factors such as age, sex, occupation, educational level, and income were included in section A. Other items included the number of malaria episodes experi-enced by the respondent per year, whether the respondent had children and health insurance, how much money was spent on malaria treatment the last time the par-

Table I. Attributes of the 3 hypothetical malaria vaccines.

Attribute Vaccine A Vaccine B Vaccine C

Effectiveness 75% 85% 95%

Duration of protection against malaria

3 Years

6 Years

12 Years

Adverse events Pain at injection site; slight fever for 24 hours

Abscess at injection site; severe headaches, fatigue, and fever that cause a 3-day absence from work

10% Probability of death from leukemia



individuals). This value was plotted on a graph as the y-axis against price or WTP. Equations were then derived that could be used to estimate the demand for any of the vaccines. The χ2 test was used to identify any as-sociation between demand and price.

A linear multiple regression analysis using WTP as the dependent variable and sociodemographic factors as explanatory variables was used to investigate the influence of different factors on WTP. Further analysis of the data to confirm the validity and sensitivity of the study as hypothesized was conducted with GraphPad InStat (version 3.06, GraphPad Software, Inc., La Jolla, California), which reports exact P values.

Kolmogorov-Smirnov normality test confirmed that the data did not have a gaussian distribution; hence nonparametric Kruskal-Wallis or Mann-Whitney test was used for inferential analysis, with the application of Dunn’s multiple comparison test where necessary. Thus, the relationship between WTP and income, choice of vaccine (preferred vaccine), and other variables was investigated. Prices are expressed in US dollars.

ReSulTSA total of 359 individuals aged ≥18 years of 500 who were approached agreed to participate in the study. This represents a response rate of 71.8%.

The sociodemographic characteristics of the respon-dents are shown in Table II. A total of 216 participants (60.2%) were women and 48 of them were pregnant; 278 (77.4%) of the respondents were either currently attending or had completed postsecondary education. In addition, 98 (27.3%) were hospitalized for malaria within the past 12 months, and only 56 (15.6%) of all participants had health insurance. More than half of the respondents (212/359; 59.1%) lived in Benin City and adjoining villages; the rest resided in the Warri area. Most respondents (299/359; 83.3%) had at least one malaria attack within the last year, and the mean (SD) number of malaria episodes was 2.6 (2.0).

Willingness to PayWTP values are shown in Table III. The mean

WTP for vaccine A, which protected for 3 years with 75% effectiveness and was well tolerated, was $6.77. The mean WTP for vaccine B, with moderate effective-ness and tolerability, was $6.70. For the least accepted alternative, vaccine C, which was not well tolerated although it was 95% effective and protected for 12 years, the WTP was $5.06.

were in actual NGN values (unstandardized). Payment cards were presented to the respondent, who was re-quired to select one of the prices from among the 14 options presented on the cards.15–17 The scenarios for vaccines B and C used exactly the same price ranges. To reduce order bias, the WTP questions were rotated such that if the first participant was presented vaccine A first, the second respondent would be presented with vaccine B first, and the third respondent would be shown vaccine C first. Finally, each respondent was asked to indicate which of the vaccines he or she preferred.

Validity and Sensitivity AnalysisTo investigate sensitivity, we hypothesized that if the

most highly valued vaccine met the following criteria, then it was likely that trading (ie, shopping for a bargain) was taking place18,19 and our WTP findings were valid: (1) WTP showed a positive association with income (content validity); (2) WTP was higher for a preferred vaccine than for the other 2 vaccines; and (3) WTP for the 3 presented vaccines was not different for respon-dents who did not prefer any of the vaccines. The main theoretical basis for the above assumptions was that the payment-card method used in contingent valuation of WTP has the advantage of mimicking the purchasing behavior of “shopping around,” by which individuals visit a number of stores that sell the same goods at dif-ferent prices.20

data Analysis and Regression ModelThe aim was to collect data from 300 to 400 respon-

dents, totaling 900 to 1200 responses for the 3 hypothetical malaria vaccines. Because the sample size was not based on any pre hoc power calculations (due to lack of informa-tion in the literature and insufficient funds to conduct a pilot study), this was a sample of convenience.

The collected data were entered into Microsoft Excel (Microsoft Corporation, Redmond, Washington) for sorting and were checked for accuracy. They were then loaded into SPSS (version 17.0.1, SPSS Inc., Chicago, Illinois) for descriptive, internal consistency, and regres-sion analyses.

Values for WTP (as mean [SD] with 95% CI) were calculated directly from the collected data. Those who were not willing to pay for a particular vaccine (zero WTP) were noted. For each given price, we calculated the cumulative percentage of those who indicated that they were willing to pay for a particular vaccine at that price plus all those who gave a higher WTP (ie, tolerant

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Table II. Descriptive statistics of the respondents and their willingness to pay for 3 hypothetical malaria vac-cines* in Nigeria (N = 359). Data are mean (SD), except as indicated.

VariableNo. (%) of

Respondents† Vaccine A Vaccine B Vaccine C

Sex Female 216 (60.2) 5.90 (7.90) 6.06 (9.35) 5.40 (10.66) Male 143 (39.8) 8.07 (7.49) 8.30 (11.25) 6.67 (11.50) P <0.001 0.018 0.138Pregnant (women only) No 168 (77.8) 6.40 (8.14) 6.10 (9.97) 5.83 (11.69) Yes 48 (22.2) 4.18 (6.78) 4.39 (6.66) 3.80 (9.23) P 0.007 0.259 0.537Age, y 18–24 92 (25.6) 6.87 (8.77) 7.00 (10.19) 6.65 (0.31) 25–34 157 (43.7) 5.88 (6.71) 6.35 (9.22) 6.21 (12.38) 35–44 88 (24.5) 8.13 (8.50) 8.49 (12.83) 5.34 (8.87) ≥45 22 (6.1) 6.58 (7.41) 5.18 (5.20) 3.10 (4.22) P 0.241 0.558 0.868Income per month, US $‡

<66.67 122 (34.0) 4.99 (6.00) 5.28 (8.39) 4.52 (9.80) 66.67–266.67 156 (43.5) 7.06 (8.65) 6.62 (9.98) 5.85 (11.74) >266.67 81 (22.6) 8.86 (7.94) 9.00 (12.52) 4.34 (9.80) P <0.001 0.01 0.855Marital status Married 178 (49.6) 6.49 (7.78) 6.80 (10.34) 4.25 (8.13) Single 181 (50.4) 7.03 (7.83) 7.14 (10.30) 7.56 (13.62) P 0.058 0.643 0.120Occupation Student 115 (32.0) 7.43 (8.70) 8.20 (11.50) 8.47 (14.95) Government worker 90 (25.1) 6.10 (6.97) 5.37 (6.46) 4.52 (7.01) Self-employed 75 (20.9) 5.36 (7.18) 6.18 (10.23) 5.13 (10.13) Unemployed 23 (6.4) 5.48 (6.64) 3.42 (4.95) 1.13 (1.20) Private-sector worker 56 (15.6) 8.87 (7.98) 9.48 (13.21) 5.92 (11.25) P 0.001 0.072 0.106Education Less than secondary school 81 (22.6) 3.68 (5.68) 3.55 (4.87) 3.63 (7.37) Postsecondary 278 (77.4) 7.66 (8.10) 7.99 (11.24) 6.60 (12.20) P <0.001 <0.001 0.465Malaria episodes per year 0 60 (16.7) 3.98 (4.09) 4.37 (8.27) 6.19 (11.31) 1 105 (29.2) 7.54 (9.33) 7.98 (11.41) 8.08 (14.28) 2 83 (23.1) 6.65 (6.53) 6.86 (10.17) 4.65 (8.44) 3 49 (13.6) 6.82 (7.62) 6.21 (8.48) 3.09 (7.89) ≥4 62 (17.3) 8.26 (8.85) 8.68 (11.38) 5.70 (10.57) P 0.016 0.020 0.190

(continued)



VariableNo. (%) of

Respondents† Vaccine A Vaccine B Vaccine C

Hospitalization for malaria within last 12 months No 261 (72.7) 955.17 (7.27) 6.12 (9.44) 5.87 (11.50) Yes 98 (27.3) 7.82 (9.00) 9.29 (12.09) 6.03 (10.88) P 0.109 0.006 0.394

Recent treatment cost for malaria, US $‡

0 51 (14.2) 4.95 (5.83) 5.20 (9.68) 7.48 (13.47) <3.33 103 (28.7) 5.97 (8.83) 5.59 (9.68) 4.16 (9.29) 3.33–13.33 140 (39.0) 7.56 (7.83) 7.68 (10.49) 5.92 (11.46) >13.33 65 (18.1) 8.01 (8.04) 9.32 (11.12) 7.58 (12.07) P 0.009 0.001 0.041

Have children No 210 (58.5) 6.78 (7.69) 6.67 (9.62) 6.50 (12.50) Yes 149 (41.5) 6.75 (7.95) 7.41 (11.22) 5.07 (9.38) P 0.298 0.958 0.824

Have health insurance No 303 (84.4) 6.96 (8.02) 7.24 (10.61) 6.04 (11.45) Yes 56 (15.6) 5.69 (6.38) 5.54 (8.37) 5.25 (10.78) P 0.121 0.194 0.706

City of residence Benin City 212 (59.1) 7.00 (7.74) 6.95 (10.31) 5.05 (11.25) Warri 147 (40.9) 6.43 (7.90) 7.01 (10.32) 5.07 (9.85) P 0.201 0.872 0.233

* Vaccine A was 75% effective, protected for 3 years, and was well tolerated; vaccine B was 85% effective, protected for 6 years, and was less well tolerated than vaccine A; and vaccine C was 95% effective and protected for 12 years, but was the least well tolerated.

† Categories may not equal 100% due to rounding. ‡ US $1.00 ≈ Nigerian naira 150.00.

Table II (continued).

Table III. Willingness to pay for 3 hypothetical malaria vaccines* in Nigeria (N = 359). Data are presented in US dollars.

Result Vaccine A Vaccine B Vaccine C P

Mean (SD) 6.77 (7.80) 6.70 (10.19) 5.06 (10.68) <0.00195% CI 5.96–7.57 5.65–7.76 3.95–6.16 –


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WTP values derived from participants) was doubled to $1.33. The difference in demand between vaccine A and B increased when the price became $6.67. However, these differences became smaller when the price was $10.00 or $13.33. The demand for vaccine A became less than that of vaccine B or C at a price of $20.00. At $40.00, the demand for vaccine C became greater than that for A or B. An association was found between price and demand (P < 0.001; χ2 = 94.386).

Nonpregnant women, men, those who had a post-secondary education, and those who paid a higher medical bill for a recent malaria treatment were willing to pay more for all 3 vaccines than were their respective comparison groups (Tables II and IV). Pregnant women, compared with nonpregnant women, would pay a significantly lower amount for vaccine A (P = 0.007). All workers and those with a higher monthly income were willing to pay more for vaccines A and B, but less

Respondents were willing to pay significantly more for vaccine A (95% CI, $5.96–$7.57), which was preferred by 55.2% (198/359); thus, the WTP was significantly different for the 3 hypothetical malaria vaccines (P < 0.001; Kruskal-Wallis statistic [kw] = 84.304). Dunn’s multiple comparison test also indicated that the WTP values for vaccines A and B were significantly different from each other (P < 0.05). There was also a significant difference between vaccine A or B versus C (P < 0.001).

Fourteen participants (3.9%) were unwilling to pay (ie, zero WTP) for vaccine B, whereas 52 (14.5%) would not pay for vaccine C. A total of 167 (46.5%) and 121 (33.7%) of the participants were willing to pay $6.67 or higher for vaccine A and vaccine B, respectively, but only 73 (20.3%) were willing to pay the same amount for vaccine C.

The figure shows the relationship between cumulative demand and price. The difference in demand between vaccine A (or B) and C increased when the price (ie,

20

40

60

80

0

Cum

ulat

ive

Dem

and

(%)

10.006.675.332.671.330.67

Price (US $)

100

20.0013.33 40.0033.33 53.3346.6726.6716.67

Vaccine AVaccine BVaccine C

Figure. Relationship between the presented price (US $) and cumulative demand (ie, the number of respon-dents who are willing to pay more than the price) for 3 hypothetical malaria vaccines in Nigeria. Vaccine A was 75% effective, protected for 3 years, and was well tolerated; vaccine B was 85% effec-tive, protected for 6 years, and was less well tolerated than vaccine A; and vaccine C was 95% effective and protected for 12 years, but was the least well tolerated. The demand for vaccines A and B is given by y = λeαx, where y = cumulative demand; x = price; and λ and α are constants (λ = 288.51 or 215.47 and α = –7.0 × 10–4 or –5.0 × 10–4 for vaccines A and B, respectively). Demand for vaccine C is best explained by y = λx–α, where λ = 127.17 and α = –4.0 × 10–4. All R2 values are >0.95.



tive effect on WTP for vaccine A and a positive effect for vaccine B. In other words, those who had children would pay more for vaccine B but less for vaccine A compared with those who did not have children.

The strongest positive influence on WTP for vaccine A was the amount the respondent was willing to pay for vaccine B (β = 0.670), and the strongest negative effect on WTP for vaccine C was the frequency of ma-laria illnesses per year (β = –0.127) (Table IV).

for C (P < 0.003). Students were willing to pay more for vaccine C compared with all other occupation groups. Income, preferred vaccine, and the amount one was willing to pay for vaccine B significantly influenced the WTP for vaccine A (P < 0.05).

A recent hospitalization for malaria significantly influ-enced the WTP for vaccine B (P < 0.05), and the number of malaria episodes in the past year was significant for vaccine C (P < 0.05; Table IV). Being a parent had a nega-

Table IV. Multiple regression analysis to investigate correlations between willingness to pay (WTP) for 3 hypo-thetical malaria vaccines* and sociodemographic factors in Nigeria.

Vaccine A Vaccine B Vaccine C

Variable B SE β B SE β B SE β

Constant –3.21 3.28 –1.76 3.89 0.32 5.16

Sex 0.04 0.34 0.004 0.38 0.40 0.035 0.18 0.54 0.016

Age 0.32 0.57 0.030 –0.60 0.68 –0.044 –0.01 0.90 0.000

Income 1.13† 0.50 0.107 0.01 0.59 0.000 –0.26 0.79 –0.018

Marital status 1.15 0.95 0.074 –0.81 1.13 –0.040 2.67 1.49 0.125

Occupation 0 0.27 0 0.09 0.31 0.012 –0.43 0.42 –0.056

Education 0.54 0.79 0.029 0.80 0.93 0.033 0.82 1.24 0.032

Malaria episodes per year 0.12 0.24 0.230 0.04 0.28 0.006 –0.90† 0.37 –0.127

Hospitalization for malaria within last 12 months –0.57 0.72 –0.033 1.85† 0.84 0.081 –1.95 1.12 –0.081

Recent treatment cost for malaria 0.50 0.40 0.061 0.02 0.47 0.010 0.83 0.62 0.073

Have children –0.52 1.00 –0.033 0.97 1.18 0.047 1.34 1.57 0.062

Have health insurance 0.17 0.84 0.008 –1.09 0.99 –0.039 0.70 1.32 0.024

WTP vaccine A – – – 0.72‡ 0.05 0.550 –0.07 0.09 –0.050

WTP vaccine B 0.51‡ 0.04 0.670 – – – 0.61‡ 0.06 0.583

WTP vaccine C –0.03 0.03 –0.040 0.35‡ 0.04 0.365 – – –

Vaccine preferred 0.88‡ 0.26 0.136 –0.48 0.31 –0.057 –0.87† 0.41 –0.099

City of residence –0.92 0.64 –0.058 0.57 0.75 0.028 –0.20 1.00 –0.009 No. of respondents 359 359 359 F statistic 23.244‡ 33.314‡ 12.300‡

R2 0.504 . 0.593 0.350

B = coefficient; β = standardized coefficient. * Vaccine A was 75% effective, protected for 3 years, and was well tolerated; vaccine B was 85% effective, protected for

6 years, and was less well tolerated than vaccine A; and vaccine C was 95% effective and protected for 12 years, but was the least well tolerated.

†P < 0.05.‡P ≤ 0.001.

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history of hospitalization for malaria within the last year or had children expressed a higher WTP for vaccine B. This may be due to its longer duration of protection and higher level of effectiveness. These respondents appeared to be willing to sacrifice 3 working days while suffering from fatigue, fever, and severe headaches. The 16.7% who claimed to prefer vaccine B possibly considered the deleterious effects of these adverse drug events to be less serious than those of malaria. Pregnant women had a lower WTP for all 3 hypothetical vaccines, although only that of vaccine A was significantly lower. It is logical to suspect that concerns about the effects of the vaccines on the fetus may have influenced their WTP values. Similarly, although some respondents rejected vaccine C, students and younger participants had a higher WTP for this vaccine than did workers and older persons; this may be an indication of risk-taking behavior in younger people, who are also probably attracted by its 95% ef-fectiveness and 12 years of protection.

Tolerant individuals are defined as those who can tolerate a price higher than the presented price. Toler-ance differs from the demand for the product at that price because even if the price is higher than a person can pay, the individual will still have to bear the burden, especially if the alternative is permanent disability or death, due to the lack of alternatives to many medical services.20 However, when alternative services are avail-able, the number of tolerant individuals may be deemed an accurate approximation of demand. In this study, there were 3 alternatives, and the fact that 20.6% said they did not prefer any of the vaccines seems to imply that they preferred their current methods for managing

Validity and SensitivityOn the basis of income, the WTP for vaccines A and

B was consistently higher in each income group than the WTP for vaccine C (P < 0.001; Tables II and IV). Those with higher incomes had significantly higher WTP for vaccine A (P < 0.001; kw = 17.092) and vac-cine B (P = 0.01; kw = 9.264), but not for vaccine C (P = NS; kw = 0.314).

Table V reveals that those who said that they did not prefer any of the vaccines would not pay a significantly higher amount for any of them (P = NS; kw = 1.104). Those who preferred vaccine A (198/359; 55.2%) or vaccine B (60/359; 16.7%) were willing to back their choice with a higher WTP (both, P < 0.001). However, for those who preferred vaccine C (27/359; 7.5%), the WTP was not significantly different from the amount they were also willing to pay for vaccines A and B (P = NS; kw = 3.505). Of those who preferred vaccine C, 21 (77.8%) were aged ≤34 years.

All of the explanatory variables in Table IV had the expected sign (plus or minus). The 2 independent variables (recent hospitalization for malaria and have children) that had negative signs for vaccine A had an expected positive sign for vaccine B. In other words, respondents who had a recent hospitalization for malaria and those who had children would pay more for vaccine B, which has a longer duration of protection against malaria.

dISCuSSIoNMore than half of the respondents (55.2%) in this study preferred vaccine A, which caused few adverse effects, and were willing to pay more for it. Those who had a

Table V. Relationship between preferred vaccine and willingness to pay for the 3 hypothetical malaria vaccines* in Nigeria (N = 359). Data are mean (SD), except as indicated.

Preferred Vaccine

No. (%) of Respondents Vaccine A Vaccine B Vaccine C P

None 74 (20.6) 3.63 (4.13) 3.75 (4.78) 4.81 (8.86) 0.576

Vaccine A 198 (55.2) 7.13 (4.13) 5.05 (8.00) 3.31 (8.61) <0.001

Vaccine B 60 (16.7) 9.53 (11.27) 14.26 (15.16) 6.69 (11.17) <0.001

Vaccine C 27 (7.5) 6.52 (8.04) 10.12 (13.05) 14.06 (18.61) 0.173




should be strengthened by the fact that the 95% CI of the WTP value for the most preferred vaccine (ie, vac-cine A, which protected for 3 years) is ~16.3% to 20.7% of the monthly salary of the lowest-paid state government worker in Nigeria, who earns ~$36.67 per month. Although this may appear to be fair considering the cost of ACT in the country,7 it does not confirm access or affordability for the larger population who lives in poverty.24

It is important to note that the psychometric proper-ties (validity and reliability) of the questionnaire used in this study were not evaluated before use. It is therefore unknown to what extent the results will be repro-ducible. This should be considered as a study limita- tion, and the results should be viewed against this background.

Studies based on contingent valuation have been criticized for being too hypothetical,26 and a divergence has been demonstrated between the hypothetical WTP and actual purchase behaviors. However, when the commodity is important to the respondents, the dis-crepancy may be small.24 As mentioned earlier, the payment-card method used in contingent valuation of WTP has the advantage of mimicking the practice of “shopping around,” whereby individuals visit several stores that sell the same goods at different prices. The WTP responses are affected by the range of the presented prices (ie, range bias).20 The range of the presented prices in this study was somewhat broad because the WTP values were distributed in the lower prices. In other words, the price options presented on the payment cards were high enough to accommodate all those who were willing to pay much more than others; respondents were not forced to select lower prices as their WTP due to lack of higher options.

There is also a tendency for individuals to provide answers perceived to be the desired response, and the results of WTP studies may be influenced by “strategic bias” as respondents deliberately understate their WTP to influence the price of a new product.20,24 In this study, however, the respondents were clearly informed that the malaria vaccines were hypothetical; therefore, re-spondents would presumably not see any personal benefit in understating their WTP for the 3 hypothetical vaccines investigated.

A high proportion of respondents were pregnant in this study. Further investigation revealed that one of the data-collection days in the Benin City center coincided with an antenatal clinic day. The 2006 national popula-tion census data showed that men and women were

malaria. Therefore, because alternatives existed here, our cumulative demand curve is an approximation of the percentage of tolerant individuals at the given price.

Because of the large societal impact of malaria,1,3–6 it should be of great concern to policy makers and funding agencies that a malaria vaccine be accessible and affordable. WTP can be used as an indicator of whether a sponsoring organization or manufacturer can recover some or all of the costs of introducing a malaria vaccine without experiencing a large financial burden. WTP is normally related to the ability to pay.19 However, WTP may not directly reflect the ability to pay in developing countries because mobilization of resources to pay for health care may require that basic needs such as food and education are sacrificed, with serious consequences for the household.3–6 In this study, respondents with lower incomes had lower WTP, which is consistent with the results of several WTP stud-ies.8,20–22 Most of the Nigerian population lives on less than a dollar a day.23 Therefore, if the cost of malaria vaccine introduction exceeds the ability of the popula-tion to pay, then subsidies will be needed to promote access and affordability.

The internal consistency of the instrument used in this study was considered acceptable. Although the R2 values for the multiple regression results in Table IV were small, indicating that there may be other variables influencing the WTP results that were not accounted for, the F statistics of the multiple regressions were significant, which implies that the variation in WTP explained by the model was not by chance.

WTP was positively associated with higher income and with self-reported preferences for the vaccines. Because the hypothesized criteria determined at the beginning of the study were satisfied by the results obtained, actual trading in a competitive market (ie, the 3 vaccines competing for market share) was successfully captured. Two migraine studies clearly showed that WTP was reduced as pharmaceuticals or treatment attributes offered fewer benefits.24,25 Thus, the increase in adverse drug effects with vaccine C in our study likely explained the reduced WTP for vaccine C compared with vaccines A and B, despite the longer duration of protection and increased level of effectiveness.

As mentioned previously, the annual mean income in Nigeria is ~$1766.00 (personal communication, Nigerian Ministry of Health, proposed recurrent ex-penditure, November 2009), and most unskilled workers earn only ~$440.00.7 Confidence in our study results

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7. Udezi WA, Usifoh CO, Eze UI. Affordability of antimalar-ial drugs in Benin City, Nigeria. Value Health. 2007;10:A447. Abstract.

8. Sauerborn R, Gbangou A, Dong H, et al. Willingness to pay for hypothetical malaria vaccines in rural Burkina Faso. Scand J Public Health. 2005;33:146–150.

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13. National Bureau of Statistics. Social Statistics in Nigeria 2009. http://www.nigerianstat.gov.ng/ext/latest_release/ssd09.pdf. Accessed July 19, 2010.

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evenly distributed in the local government areas where the study sites are located.13 In addition, a larger propor-tion of the study participants had not been hospitalized as a result of malaria, and most of the study participants did not have health insurance. Both statistical and epi-demiologic estimates are hard to obtain in Nigeria. The uneven sex distribution and presence of many pregnant women in the study sample were attributable to the type of study sites used, and the study population cannot be considered to be representative of the general popula-tion; this could have biased the WTP results. Therefore, further community-based studies with larger sample sizes will be required to confirm these results.

CoNCluSIoNSOur results suggest that although malaria is a serious disease, the Nigerians interviewed preferred and were willing to pay more for a vaccine that was well tolerated (ie, vaccine A), even if its effectiveness and duration of protection against malaria were lower than those of a product that caused severe adverse effects. Our findings indicate that the poor will pay less than wealthier people for a well-tolerated malaria vaccine that has an accept-able level of effectiveness and duration of protection. If this amount is smaller than what is economically acceptable to manufacturers, then subsidies may be an option for governments and funding agencies. Interpre-tation of this study should be guided by the knowledge that differences exist between the study sample and the general population.

ACKNoWledGMeNTSAll authors contributed equally toward this study from conception to completion. The authors have indicated that they have no conflicts of interest regarding the content of this article.

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2. Hay SI, Guerra CA, Tatem AJ, et al. Urbanization, malaria transmission and disease burden in Africa. Nat Rev Micro-biol. 2005;3:81–90.

3. Russell S. The economic burden of illness for households in developing countries: A review of studies focusing on malaria, tuberculosis, and human immunodeficiency virus/ acquired immunodeficiency syndrome. Am J Trop Med Hyg. 2004;71(Suppl 2):47–155.



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23. United Nations Development Pro-gramme. Human Development Report 2009. New York, NY: Palgrave Mac-millan; 2009.

24. Lenert LA. Use of willingness to pay study values for pharmacotherapies for migraine headache. Med Care. 2003;41:299–308.

25. Hamelsky SW, Lipton RB, Stewart WF. An assessment of the burden of migraine using the willingness to pay model. Cephalalgia. 2005;25:87–100.

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Address correspondence to: Waka Anthony Udezi, MPharm, Department of Clinical Pharmacy, Faculty of Pharmacy, University of Benin, 300001, Edo, Nigeria. E-mail: [email protected]

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Willingness to pay for three hypothetical malaria vaccines in Nigeria