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. 2020 Oct 2;15(10):e0239829. doi: 10.1371/journal.pone.0239829

Farmers’ willingness to pay for foot and mouth disease vaccine in different cattle production systems in Amhara region of Ethiopia

Wudu T Jemberu 1,*, Wassie Molla 1, Tigabu Dagnew 2, Jonathan Rushton 3, Henk Hogeveen 4
Editor: Simon Clegg5
PMCID: PMC7531826  PMID: 33006982

Abstract

Although foot and mouth disease (FMD) is endemic in Ethiopia, use of vaccines to control the disease has been practiced sparingly. This is due to perceived high cost of good quality FMD vaccine, and consequently limited availability of the vaccine in the market. This study was conducted to assess farmers’ willingness to pay (WTP) for a quality FMD vaccine and identify factors that could potentially influence their WTP in Amhara region of Ethiopia. A total of 398 farmers from four districts that represent the mixed crop-livestock and market oriented production systems were enrolled for the study. The WTP was estimated using contingent valuation method with a double-bound dichotomous choice bid design. Interval regression analysis was used to estimate mean WTP and identify factors that influence it. The results showed that the mean WTP of all farmers was Ethiopian Birr (ETB) 58.23 (95% CI: 56.20–60.26)/annual dose. It was ETB 75.23 (95% CI: 72. 97–74.49) for market oriented farmers and ETB 42.6 (95%CI: 41.24–43.96) for mixed crop livestock farmers. Willingness to pay for the vaccine was significantly higher for farmers in market oriented system than in mixed crop livestock system. It was also significantly higher for farmers whose main livelihood is livestock than those whose main livelihood is other than livestock, and for farmers who keep exotic breed cattle and their crosses than those who keep only local cattle breeds. Willingness to pay significantly increased with increase in FMD impact perception and vaccine knowledge scores of farmers. The high mean WTP estimates showed that farmers are enthusiastic about using the FMD vaccine. Market-oriented farmers with higher willingness to pay may be more likely to pay full cost if official FMD vaccination is planned in the country than mixed crop livestock farmers. Animal health extension about livestock diseases impact and vaccines has a potential to increase farmers’ uptake of vaccines for disease control.

1. Introduction

Foot and mouth disease (FMD) is arguably the most important disease of livestock worldwide due to costs associated with production losses, trade restriction, and prevention and control [1]. The disease is caused by foot and mouth disease virus of the genus Aphthovirus and family Picornaviridae, and primarily affects cattle, swine and small ruminants [2].

Historically two major approaches have been used separately or in combination to control FMD worldwide: intensive surveillance and stamping out as in case of United Kingdom, Scandinavia and North America, and vaccination with or without stamping out as in the case of continental Europe and parts of South America [3]. Currently, the stamping out strategy is used by disease free developed countries to control incursion of outbreaks through rapid detection of disease introduction and slaughtering of infected and in contact herds. Regular mass vaccination is often used to control the disease in endemic developing countries.

For endemic developing countries, prophylactic vaccination remains the main feasible method of controlling the disease [4]. However, FMD vaccination is complex as compared to other similar epidemic livestock diseases such as rinderpest and peste des petitis ruminants, which have effective and affordable vaccines. Conventional FMD vaccines are inactivated vaccines and need frequent application. Vaccine matching is also a serious challenge in FMD vaccination due to existence of multiple serotypes and strains that don’t or poorly cross-protect against each other [5, 6]. Foot and mouth disease vaccines are often made to cover multiple serotypes and strains and these negatively affect the potency and cost of the vaccines as compared to monovalent vaccines [7]. This makes control of FMD using vaccination a difficult undertaking for resource constrained developing countries like Ethiopia.

Although foot and mouth disease is endemic in Ethiopia, control of the disease using vaccination has rarely been practiced. Despite the stated interest and plan of the government to improve the disease situation and boost meat and live animal export trade [8], no official control has been practiced yet. Unlike other transboundary livestock disease such as peste des petitis ruminants, lumpy skin disease, contagious bovine pleuropneumonia, African horse sickness, sheep and goat pox among others, for which the government is providing free vaccination service for farmers, no support have been given for FMD vaccination. Except some market oriented farmers in urban and periurban areas, most farmers are not vaccinating their herds against FMD. The vaccine is not adequately available in the market and the main reason for this could be the perception that FMD vaccines are expensive and farmers may be reluctant to use the vaccine. The present study was conducted to assess farmers’ willingness to pay (WTP) for a quality FMD vaccine and identify the factors that could potentially influence their WTP using contingent valuation method in Amhara region of Ethiopia.

2. Materials and methods

2.1 Ethics statement

The study was ethically reviewed and approved by Institutional Review Board of University of Gondar. Oral informed consent has been obtained from questionnaire respondents.

2.2 The study area and population

The study was conducted in the Gondar-Bahir Dar milk shed in Amhara region of Ethiopia. This area encompasses livestock producers who supply milk to the two major cities of northwestern part of the Amhara regional state namely Bahir Dar and Gondar [9]. Broadly there are two types of production systems practiced in the region: the dominant mixed crop-livestock (MCL) production system, which is a subsistence system that is practiced in the rural areas, and a market oriented (MO) production system which produces commercial milk and is practiced in urban and periurban areas.

2.3 Contingent valuation method

There are many varieties of techniques used for valuation in economics, grouped in two categories: revealed preference and stated preference. Revealed preference techniques are based on actual behavior of individuals in a real market reflecting utility maximization subject to constraints. Stated preference techniques, on the other hand, are based on responses of individuals to hypothetical questions rather than from observations of real-world choices [10]. As the responses are contingent upon the specific conditions laid out in the hypothetical market, this form of stated preference methods are broadly referred to as contingent valuation [10]. Contingent valuation method (CVM) is a widely used nonmarket valuation method in economics to determine WTP for goods or services that are not traded in the market place. This method of measuring value is developed and widely used in environmental economics where it is used to value environmental amenities and services [10, 11]. The other areas in economics where this method is increasingly being applied are health, transportation safety, and cultural economics [11].

In CVM, a survey is designed to create different hypothetical market scenarios for reflecting value of non-marketable goods and survey respondents are asked to state their response to the hypothetical market scenarios. The data collected by such surveys is then analyzed in a similar manner as the choices made by consumers in actual markets [12]. Despite the controversy over the validity of this method of valuation, it is a popular nonmarket valuation method in environmental economics [11].

Willingness to pay studies using contingent valuation methods are also increasingly being used in in animal disease control in recent years [1317]. Brief review of literature on earlier application of contingent valuation method in animal health and associated areas can be found in Bennet and Balcombe [13]. Although animal disease vaccines are marketable and do have market prices, they also have public good nature. Hence, contingent valuation can be used to determine the WTP for these public goods. This could be for a vaccine under development and yet not marketed [13] or for existing vaccines, which are poorly adopted for variety of reasons including price sensitivity [14, 15, 17].

There are different methods of WTP data elicitation (bid design) in CVM. Possible bidding mechanisms include: bidding, payment card, Open-ended question, and Single (Double)-bounded dichotomous choice methods [18]. Dichotomous choice methods are important in that they have less starting bias and simplicity and are therefore commonly used methods in contingent evaluation. While the double dichotomous choice is more complex analytically, it has an advantage in the data efficiency [19] and hence has been a choice of method for the present study.

2.4 The survey

The survey was prepared in line with the recommended contingent evaluation elicitation guideline of the National Oceanic and Atmospheric Administration [18]. It consisted of two major parts. The first part contained the bidding questions directly related to the WTP for a hypothetical vaccine market and the second part contained the questions about the socioeconomic factors that could influence the willingness of the farmer to pay for FMD vaccine (S1 File). The first question of the survey before the two major parts was a question verifying whether the respondents knew the disease. The bidding questions consisted of double-bound dichotomous choice questions. In the double dichotomous choice bidding format, there were questions on two stages. The initial stage questions contain a set of bid amounts to which respondents state their WTP as ‘yes’ or ‘no’ to hypothetical vaccine prices. These initial bid amounts were distributed equally and randomly among respondents during questionnaire administration. The initial stage questions were followed up by second stage questions with bid amount of 50% plus or minus to the initial bid amounts depending on the response to the first bid amount. If the response to the initial bid amount was ‘yes’ the follow up bid amount would increase by 50% and if the response to the initial bid amount was ‘no’ the follow up bid amount would decrease by 50% (Table 1). In both the initial and follow up stage questions an ‘undetermined’ alternative was included for respondents who were not able to decide as ‘yes’ or ‘no’. The hypothetical market scenario was followed by a debriefing question to ensure that the respondents correctly understood the presented scenario before they gave their answers.

Table 1. The double-bound dichotomous choice questionnaire bid structure.

Initial bid (administered randomly one for each respondent) (ETB) Initial bid response Follow up bid amount (ETB)
20 no 10
yes 30
40 no 20
yes 60
60 no 30
yes 90
80 no 40
yes 120

The initial bid set contained prices of Ethiopian Birr (ETB*, One Ethiopia Birr is equivalent to 0.034 USD at the time of the survey.) 20, 40, 60 and 80 per dose. This price set was proposed based on information found from open ended WTP pilot survey on 15 MCL and 15 market oriented farmers with price range of ETB 5-100/annual dose for the same hypothetical vaccine. This price range was roughly similar to the range of USD 0.4–3 (ETB 12–88) for different types of FMD vaccines reported in the literature in different countries in the world [1, 20]. Since, a quality standard FMD vaccine should have a protection level greater than 75% [21], in this study the respondents were made to bid for a hypothetical vaccine with protection effectiveness of 80% which is proposed to be administered twice a year by the public veterinary service in their village.

The second part of the questionnaire contains questions related to sociodemographic features and husbandry practices of the respondents that could potentially affect the respondent’s WTP for FMD vaccine. These include demographic variables (Age, Educational status, Main livelihood), livestock husbandry related variables (number of cattle owned, number of TLU owned, income from cattle sale, income from milk sale, cattle kept for business, breed of cattle kept, main veterinary service used, experience of vaccine for livestock), perception about FMD impact on livestock, and knowledge on the use of vaccine for livestock disease prevention (S1 File). The perception of FMD impact and the knowledge of vaccine variables were measured as composite scores of several questions under each variable. The FMD impact perception score was generated from five questions each of which has a maximum score of three (giving a total maximum impact score of 15). Similarly the knowledge score about livestock vaccine was generated based on four dichotomous vaccine knowledge questions which have score of either one (correct answer) or zero (incorrect answer) giving a maximum knowledge score of four (S1 File).

The survey was administered by means of face to face interviews of respondents in the local language (Amharic) and was done by trained veterinary personnel in each district. The study protocol was ethically reviewed and approved by Institutional Board of University of Gondar. The respondents were asked for their informed consent before the interview.

2.5 Sampling and sample size

The respondents for the WTP survey were farmers from four districts in Bahir Dar–Gondar Milk shed in northwest Ethiopia that represent MO and MCL production systems. The two urban districts (Bahir Dar and Gondar) represent the MO and the other two rural districts (Gondar Zuria and Estie) represent MCL system. These four districts were selected purposefully and conveniently to represent the two types of livestock production systems in the area. While the two urban districts are the major urban centers in the milk shed and had recent FMD history, the two rural districts were selected because of recent history of FMD outbreaks. Districts with a recent history of FMD outbreak were particularly considered for sampling to get more farmers who are familiar with the disease to respond to the survey questions. A total of 400 farmers (farm household heads), 100 from each district who knew the disease, were enrolled for the survey. The farmers were sampled at some haphazard interval in different streets of the urban districts and villages in the rural districts. Strict randomization of the selection was not possible due to lack of sampling frame and in accessibility of some of the villages in the rural districts.

2.6 Data analysis

Interval regression analysis [22] was used to estimate the farmers’ WTP for FMD vaccine from the double-bounded dichotomous contingent valuation data collected with the questionnaire.

The responses to the double-bounded CV questions give four possible discrete outcomes:1) the respondent was not willing to purchase the FMD vaccine both at initial bid amount and at the lower follow up bid amount (‘‘no”, ‘‘no”); 2) the respondent was not willing to purchase the FMD vaccine at the initial bid amount but was willing to buy at the lower follow up bid amount (‘‘no”, ‘‘yes”); 3) the respondent was willing to purchase FMD vaccines at the initial bid amount but not at the higher follow up bid amount (‘‘yes”, ‘‘no”); or (4) the respondent was willing to purchase the FMD vaccine at both the initial bid amount and the higher follow up bid amount (‘‘yes”, ‘‘yes”). This creates four possible intervals where farmers WTP could fall: (0, Bl), (Bl, Bi), (Bi, Bh), (Bh, ∞). Where, Bi the initial bid amount, Bl is the lower follow up bid amount, and Bh is the higher follow up bid amount. This results in three types of censoring: left censored, right censured and interval censored. The WTP was modelled from the interval data created this way and interval regression was used to estimate the mean WTP and potential factors that influence the WTP amount (S1 Dataset). In the model, WTP is estimated as linear function of respondents’ characteristics with normal distribution of random error [23].

The data was first entered into Microsoft excel for editing and cleaning and then taken to Stata software version 14 (Stata Corp. College Station, TX) for analysis. In the interval regression modelling, first the variables considered for the models were checked for multicollinearity using variance inflation factor (VIF). Variance inflation factor value of above 10 was considered as indicator of presence of collinearity [24]. Then the full models containing all non collinear variables were run. Final models were reached through backward elimination of non-significant variables (p-value > 5%) one at a time until only significant variables were left.

3. Results

3.1 Sociodemographic and cattle husbandry characteristics of the survey respondents

A total of 398 respondents participated in the survey. After cleaning, the data from 386 respondents were used for all the analyses. Data of 13 respondents were excluded from the analyses due to incomplete or inconsistent responses for one or more important variables. Data of three respondents were excluded from the WTP analysis because they gave ‘undetermined’ response for WTP questions.

Sociodemographic and cattle husbandry characteristics of the survey respondents are summarized in Table 2. Livestock was the main livelihood for majority (58%) of MO respondents but only very few MCL respondents stated livestock as main livelihood source. The total numbers of different species of livestock kept by respondents were aggregated using tropical livestock units (TLU) and the average TLU holding was about six TLUs being a little bit higher for MCL than MO respondents. Almost all respondents in the MO system keep cattle for business (sale of cattle or milk or other products) whereas only about 28% of MCL respondents keep cattle for business. Majority of the respondents (85%) use modern veterinary service and 88% have experience of using vaccine in their cattle husbandry. Unexpectedly, the MO respondents use traditional veterinary service more and have less experience with livestock vaccine as compared to the MCL respondents (Table 2).

Table 2. Summary of sociodemographic and livestock husbandry characteristics of survey respondents by production system (MCL = 195, MO = 191, Overall = 386).

Variables MCL (mean (SDa)) MO (mean(SD)) Overall (mean (SD))
Sex
Male 0.98 (0.14) 0.91 (0.29) 0.94 (0.23)
Female 0.02 (0.14) 0.08 (0.29) 0.06 (0.23)
Age 47.1 (9.2) 44.0 (10) 45.6 (9.7)
Educational status
Illiterate 0.60 (0.49) 0.22 (0.42) 0.41 (0.50)
Primary 0.36 (0.48) 0.61 (0.49) 0.48 (0.50)
Secondary and above 0.03 (0.17) 0.17 (0.37) 0.10 (0.30)
Main livelihood
Livestock 0.02 (0.12) 0.58 (0.49) 0.30 (0.45)
Other (crop, trade, employment) 0.98 (0.12) 0.42 (0.49) 0.70 (0.45)
Number of cattle owned 6.3 (3.1) 7.4 (5.3) 6.9 (4.4)
Number of TLU 6.6 (3.2) 5.3 (3.7) 6.0 (3.5)
Income from cattle sale for the previous year 5838 (8174) 22632 (26927) 14148 (21498)
Income from milk sale for the previous year 438 (2812) 51425 (62420) 25667 (50777)
Cattle kept for business
yes 0.29 (0.46) 1 (0) 0.64 (0.48)
no 0.71 (0.46) 0 (0) 0.34 (0.48)
Breed of cattle kept
Local 0.65(0.48) 0.08 (0.28) 0.37 (0.48)
Exotic and their cross 0.03 (0.17) 0.31 (0.46) 0.17 (0.38)
Both local, exotic and their cross 0.32 (0.47) 0.60 (0.49) 0.46 (0.50)
Main veterinary service used
Traditional 0 ~0 ~0
modern 0.91 (0.28) 0.79 (0.41) 0.85 (0.36)
Both 0.09(0.28 0.21 (0.41) 0.15 (0. 36)
Ever used vaccine for livestock
Yes 0.98 (0.12) 0.78 (0.42) 0.88 (0.32)
no 0.02 (0.12) 0.22 (0.42) 0.12 (0.32)
Perception of FMD impact (out of 15 score scale) 9.9 (3.1) 10.7 (1.6) 10.3 (1.5)
Knowledge about livestock vaccine (out of 4 score scale) 3 .4 (0.8) 2.7 (0.9) 3 (0.1)

aSD = standard deviation

The average score of the overall FMD impact perception was 10.3 out of a total of 15 points, which was a little bit higher for the urban MO system respondents. Similarly, the average vaccine knowledge score was 3 out of total 4 points, which was higher for MCL respondents (Table 2).

3.2 Willingness to pay for FMD vaccine and factors affecting WTP

The willingness to pay for the hypothetical vaccine presented was observed to decrease with an increase in the bid amount (Table 3). The percentage of WTP (‘yes’ responses) for the initial bids of 20 birr, 40 birr, 60 birr and 80 birr were 84%, 66%, 50% and 33% respectively.

Table 3. Summary of WTP responses in the double dichotomous contingent evaluation survey (N = 393).

Initial bid in ETB Initial bid response Follow up bid amount and response
Response No. of response (%) Follow up bid in ETB No. of ‘no’ responses (%) No. of ‘yes’ responses (%)
20 no 14 (16) 10 2 (14) 12 (86)
yes 82 (84) 30 29 (35) 53 (65)
40 no 32 (34) 20 14 (44) 18 (56)
yes 63 (66) 60 29(46) 34 (54)
60 no 50 (50) 30 25 (50) 25 (50)
yes 50 (50) 90 24(48) 26(52)
80 no 62 (67) 40 29 (47) 33 (53)
yes 30 (33) 120 14 (47) 16 (53)
Overall No 158 (0.41) 70(47) 88(53)
Yes 225 (0.59) 96(43) 129.(57)

Interval regression analysis showed that the mean WTP as determined by the constants of the null models (a model without any explanatory variables) was ETB 57.76 (95% CI: 53.74%-61.78) per dose for all respondents, ETB 42.66 (95%CI: 38.32–46.99) for MCL respondents and ETB 74.56 (95% CI: 67.91–81.24) for MO respondents. These are WTP estimates without taking into account any variables that could potentially affect WTP for the vaccine.

None of the sociodemographic variables considered in the overall interval regression model were significantly associated with WTP (P> 0.05). The variables found to be significantly associated with WTP were those related to livestock husbandry which include livestock production system, type of cattle breeds kept, whether livestock is main livelihood or not, perception of impact of FMD, and knowledge about livestock vaccines (Table 4). For example, the WTP in MO farmers is 18.92 ETB higher than the MCL farmers, and when the vaccine knowledge score of farmers increases by one unit the WTP increases by 6.7 ETB, keeping other variables in the model constant.

Table 4. Livestock husbandry variables significantly associated with WTP for FMD vaccines (N = 383).

Variables Model Coefficients 95% CI of Coefficients P- value
Production system MO 18.92 8.69–29.14 <0.001
MCL reference reference reference
Main livelihood livestock 15.68 5.63–25.76 0.002
Other reference reference reference
Breed of cattle kept
Exotic and their cross 13.56 0.59–26.52 0.040
Both local, exotic and their cross -1.10 -9.82–7.61 0.804
local reference reference reference
Perception of FMD impact 4.58 2.15–7.00 <0.001
Knowledge about livestock vaccine 6.70 2.80–10.60 0.001

Given the socioeconomic and husbandry difference between MCL and MO production systems and also the significant difference in WTP for an FMD vaccine, separate interval regression was run for the two production systems and the results are shown in Table 5.

Table 5. Livestock husbandry variables significantly associated with WTP for respondents in the different production systems (N = 191 for MCL and N = 192 for MO).

Production systems and Variables Model Coefficients 95% CI of Coefficients P- value
CLM system
No of cattle owned 1.61 0.25–2.96 0.020
Perception of FMD impact 4.20 1.15–7.25 0.007
Knowledge about livestock vaccine 6.06 1.18–10.93 0.015
MO system
Main livelihood livestock 14.95 2.92–26,98 0.015
other Reference reference reference
Perception of FMD impact 5.96 2.00–9.92 0.003
Knowledge about livestock vaccine 8.09 1.70–14.47 0.013

For the MCL respondents, the factors that significantly influence the WTP of FMD vaccine were number of cattle owned, perception of FMD impact and Knowledge of livestock vaccine in which increase of the value in all of them increases WTP (Table 5). For the MO respondents, factors that were significantly associated with WTP of FMD vaccine were whether livestock is main livelihood or not, and FMD perception score and livestock vaccine knowledge scores. Having livestock as main livelihood, higher livestock impact perception score and higher livestock vaccine knowledge scores significantly increased WTP.

The mean and median WTP estimates were also derived (Table 6) from the interval regression models described in the preceding paragraphs. The WTP derived from the model are very close to the estimates directly observed from the intercept of the null models described earlier in this section.

Table 6. WTP estimates derived from the best interval linear regression models.

Group Mean Median Standard deviation 95% confidence interval
MCL system 42.60 42.84 9.55 41. 24–43.96
MO system 75.23 73.34 15.91 72. 97–74.49
Overall 58. 23 51 .80 20.24 56.20–60.26

4. Discussion

4.1 Willingness to pay

Despite the availability of an FMD vaccine, the use of such a vaccine in Ethiopia, especially in the dominant subsistence livestock productions (pastoral system and mixed crop livestock system) has been rare. This is presumably due to the low availability and high cost of FMD vaccine. In this study, we tried to estimate how much farmers in two typical Ethiopian livestock production systems in the Bahir Dar-Gondar Milk shed are willing to pay for a quality FMD vaccine and what sociodemographic and livestock husbandry characteristics influence farmers’ WTP for the vaccine. The study revealed that majority of the farmers answered ‘yes’ to both the initial and follow up price bids set for FMD vaccine indicating their enthusiasm for using the vaccine. The proportion of farmers willing to pay decreases monotonically from 82% to 32% when the initial bid values increased from ETB 20 to 80, which is consistent with economic law of demand [25]. This pattern assures the rationality and hence the validity of the responses given by the farmers.

The estimates of the WTP for the vaccine reported from the study were generally high; for example, it is much higher than the ETB 20/annual dose currently available in the government vaccine production institute in the country. This is unexpected in a region where farmers get most of the livestock vaccines with substantially cheaper prices or even free as in the case of vaccines for transboundary animal diseases other than FMD. Although reason for willingness was not asked in the survey, farmers were unpromptingly explaining that if the disease occurs its impact on milk reduction will be very high compared to the stated vaccine prices.

The mean WTP for the vaccine as estimated using the interval regression model parametrized from the double-bound dichotomous questionnaire data was ETB 58.23 (USD1.96) per year. The WTP was significantly different in the different production systems. As expected, it was higher (ETB 75.23 (USD 2.53)) for the MO and lower (ETB 42.6 (USD 1.43)) for mixed crop-livestock system. These WTP estimates are much higher than the ETB 20 (ETB10/dose for a biannual vaccination) currently charged for the trivalent (O, A, SAT2) vaccine produced by the National Veterinary Institute in the country. However, the provision of the vaccine at this price by the institute may not reflect the real market value as the government usually provides vaccines at subsidized prices. Moreover, availability of this vaccine is limited and its effectiveness has also been in question (pres. communication). Therefore, it is difficult to assert that farmers are willing to pay more than market price based on this comparison. The estimates were within the range of USD 0.4 to 3 cost paid per dose for FMD vaccine including vaccine delivery across the world [1]. In Tanzania a roughly similar WTP amount, i.e. USD 1.84 (95% CI: 1.28–2.48) was reported for cattle FMD vaccine [16]. An FMD economic impact study in traditional smallholder production system in Ethiopia indicated the potential economic profitability of FMD vaccination using likely market price of FMD vaccine [26]. The observed farmers’ WTP for the vaccine can, therefore, be considered as economically justifiable. Generally, the average WTP stated by the farmers indicated that they are willing to pay substantial amount, if a quality vaccine is presented and its use promoted. This could be, for example, full cost coverage for the market oriented farmers and the substantial part of the price for the dominantly subsistence MCL system. However, several studies on potential biases associated with WTP determined in contingent evaluation consistently indicated that it tends to overestimate the WTP as compared to actual market behavior [2729]. This has to be taken into consideration when the estimated WTP are interpreted for practical application.

4.2 Factors affecting willingness to pay

A number of sociodemographic and cattle husbandry variables were evaluated for their influence on WTP of the farmers. None of the sociodemographic variables considered such as sex, age, household size, education status and livestock number (proxy for income level) had significant impact on WTP. However, it was observed that MCL farmers who have relatively lower level of education status had more experience of using livestock vaccine than MO farmers who had better education status. Hence, it seems that the main driver for vaccine awareness and uptake is not related to formal education level. Probably the access to livestock extension, which is better in the rural MCL system, might play greater role for better uptake of vaccine in this system.

Livestock husbandry related variables such as livestock production system, type of cattle breeds kept, whether livestock is the main livelihood or not, perception of impact of FMD and knowledge about livestock vaccines were found to be important drivers of WTP for FMD vaccine. Willingness to pay was significantly higher for MO than in the MCL system. Farmers in the urban market oriented system keep more productive but disease susceptible animals for market milk production, hence, would be sensitive to impact of FMD and it is economically rational that they were willing to pay more for the vaccine. In support of this an FMD economic impact study in the same areas indicated much higher loss of USD 459 (USD 26 per animal in the affected herd) due to FMD outbreak in a MO farms as compared to USD 34 (USD 5 per animal in affected herd) in CLM farms [30]. Willingness to pay was also higher for respondents whose main livelihood is livestock raising than respondents whose main livelihood is other than livestock. This is logically consistent, as farmers would like to safeguard their source of livelihood by paying more for vaccination. Respondents who keep exotic breed cattle and their crosses showed higher WTP than those who keep only local cattle breeds. This could be related to the factors discussed in the preceding sentences. Market oriented farmers whose main livelihood is driven from dairy production would keep more exotic cross bred cattle than their counterparts and their higher WTP for FMD can be similarly explained. At this point one might pose question of multicollinearity among these factors i.e. production system, source of livelihood and breed for cattle kept. But their multicollinearity was tested during the model building and no multicollinearity was found between any of the variables large enough to drop from the analysis.

It was also observed that WTP increases significantly with increase in FMD impact perception score. Similarly, farmers with high risk perception for bovine tuberculosis (BTB) in UK were seen to have higher WTP for BTB vaccine [13]. It is economically rational that farmers who perceived significant impact of the disease are willing to pay more to avoid the disease.

Higher livestock vaccine knowledge score was significantly positively associated with WTP. Those who had better knowledge were observed to be willing to pay more. Similar finding of increasing WTP with increase in vaccine knowledge level was reported for other livestock vaccines [17]. This has been also observed in human vaccine where people who have better vaccine related knowledge are willing to pay more [31]. This indicates there is a room for increasing WTP and uptake of vaccine by increasing vaccine awareness related extension to farmers for control and eradication of livestock diseases.

5. Conclusions

The farmers’ mean WTP for FMD vaccine in the study area was generally found high and was greater than the price of the vaccine currently produced and sold by the national veterinary institute in the country. The study findings contested the perception that FMD vaccines are costly and farmers would be reluctant to pay for it. The estimated WTP prices, especially that of the market-oriented farmers can be within the range of FMD vaccine price available in the world market. Based on these WTP estimates it can be assumed that market-oriented farmers with higher willingness to pay may be more likely to pay full cost if official FMD vaccination is planned in the country than mixed crop livestock farmers. Farmers who have high perception of FMD risk and good knowledge of vaccines have greater WTP for FMD vaccine. Hence, animal extension service about the disease impact and importance of vaccines in livestock disease control has potential to increase farmers’ uptake of vaccines for disease control.

Supporting information

S1 File. Willingness to pay questionnaire survey.

(DOCX)

S1 Dataset

(XLSX)

Acknowledgments

Authors would like thank the farmers who were willing to participate as respondents for the survey.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

"This study was funded by University of Gondar (www.uog.edu.et). The grant was awarded to WTJ (the first author of this article) with grant letter number VP/RCS/05/280/2016. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

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Decision Letter 0

Simon Clegg

8 Jul 2020

PONE-D-20-17667

Farmers' willingness to pay for foot and mouth disease vaccine in different cattle production systems in Amhara region of Ethiopia.

PLOS ONE

Dear Dr. Jemberu

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Many thanks for submitting your manuscript to PLOS One

Your manuscript was reviewed by two experts in the field, and they have recommended some modifications be made prior to acceptance

If you could write a response to reviewers, then that will expedite reviews upon resubmission

I wish you the best of luck with your revisions

Hope you are keeping safe and well in these difficult times

Thanks

Simon

==============================

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**********

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Reviewer #1: The study is an important one as it can lead to better control of FMD in Ethiopia. Though the appropriate data has been collected and most of the analyses done, the analysis mentions procedures like checking for multicollinearity but the details of how are missing. It is not clear how WTPs were constructed in the analysis. The resultant coefficients in the regression analysis are not interpreted at all, only the p values (significance).

Specifically:

L24: Replace ‘rarely’ with ‘sparingly’and expensiveness with 'high cost'

L34-37: There are too many variables in this sentence. One is unable to see what is being compared. Split the sentence to make clear what WTP is significantly higher than which with regard to systems, livelihoods, breeds

L40: Report in the affirmative rather than in the negative by turning the sentence around

L42: market-oriented system farmers

L43-44: Be specific on which vaccine, which disease because your study was not on all vaccines, all diseases

L56: Write UK in full; Scandinavia

L65: Do you mean endemic rather than epidemic?

L67: Replace ‘vaccination’ with ‘application’ otherwise it reads like the vaccines are being vaccinated

L68: ‘negatively affect the effectiveness and raise the cost of vaccination’

L75: Sheep and goat

L77: replace etc. with among others

L78: vaccine not vaccines

L149: What does it mean ‘undetermined alternative’

The survey should really be in reverse. You first get the perception and knowledge of the farmers on FMD as you need them as independent variables. Then you need to make all of them understand the disease and its control by the vaccine whose attributes they need to understand before bidding because as per your background information, these farmers may not even know the vaccine. Then you pose the bidding questions. Apparently before bidding you did not explain these aspects to the farmers which makes one wonder whether they knew what they were bidding for.

L217: Change check to checked; It is not clear how multicollinearity was checked

It is rare that a backward elimination of non-significant variables will result in a model with only significant variables

L226: What does ‘inconsistent response’ mean?

L227: Who gave the ‘undetermined response’ for WTP?

L230: The ‘majority’ here is only about half. How were the results of the other half. Explain from the table without repetition

Table 2: In the column, align contents conventionally; text aligned to the left and figures to the right. What is income from cattle and milk sale? Annual, monthly or what?

L255-260: It is not clear how the mean WTPs were calculated

L262: The p should be >0.05 if no significant association

Table 4: Just indicate the reference category within the table by writing ref in the model coefficients column for the respective reference categories instead of having a footnote which is not clear

L261-265 and 272-278: Give the interpretation of the model coefficients, not just of the p value (significance). Considering the regression equation that arises from the results would help

L272-276: Remove unnecessary capitalization of words

Table 6: It is not clear how the WTP estimates were derived

L300: citation/reference?

L311: What is ‘parametrized’?

L321-322: Correct the sentence

L328: What is ‘quality vaccine’ – you did not explain the vaccine to them

L330: What is CLM?

L332: Change ‘tend’ to ‘tends’

L348: Avoid an abbreviation at the beginning of a sentence

L362-365: Sentence is too long and needs rephrasing for clarity

L374: Correct the word knowledge

In the conclusion, WTP alone is not sufficient to make the conclusion that vaccine price can be covered by farmers fully without your knowledge on their ‘ability to pay’. You need to look at their profits or how they perceive profitability from their enterprises. As is, it is possible that WTP may represent valuation of vaccination rather than actual desire to pay the amounts

L441: correct 20.20

Reviewer #2: Reviewer comments:

Excellent study design, data analysis, and overall manuscript. A few suggestions below. Suggest one more read through by a strong English speaker to remove typos. Identified some below, but there are probably more, and they distract from the quality of the paper.

Line 35-36: should read “whose main livelihood is”

36 “livestock than those whose main livelihood is other than livestock,” – Rewrite, confusing

65 – typo – should read peste

63 onwards – May be worthwhile to mention the role of diagnostic testing in FMD vaccination as an additional challenge – alluded to but not directly mentioned

78 – should read “vaccine is…”

120 – contingent valuation is also appropriate in this situation because many people are not vaccinating.

180 – should read “asked for”

198 – should read farmers’

199 – should read double-bounded

347 – should read “is the main”

370 – should read “are willing to pay more”

373 – should read “pay more”

381 – should read farmers’

385 – should read farmers

Gender – noticed the percentage of women respondents is very low. Do you think this is representative of the study population? Seems possible the selection of participants may bias against women if they are more likely to be at home. May be worthwhile to think more about this in the discussion.

**********

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PLoS One. 2020 Oct 2;15(10):e0239829. doi: 10.1371/journal.pone.0239829.r002

Author response to Decision Letter 0


18 Aug 2020

Responses to reviewers’ comments

Note: The line number refer to the Revised Manuscript with Track Changes

Reviewer #1:

Comment: The study is an important one as it can lead to better control of FMD in Ethiopia. Though the appropriate data has been collected and most of the analyses done, the analysis mentions procedures like checking for multicollinearity but the details of how are missing. It is not clear how WTPs were constructed in the analysis. The resultant coefficients in the regression analysis are not interpreted at all, only the p values (significance).

Response:

- Detail of how multicollinearity was assessed for covariates in the model is provided in the revised version (L219-22)

- How the willingness to pay was derived from interval regression model was documented in L 212- 215 of the manuscript. It is explained in more detail below in the responses given for the specific comments on the issue.

- The interpretation of the model coefficients are provided in the revised version (L269-272)

Specifically:

L24: Replace ‘rarely’ with ‘sparingly’ and expensiveness with 'high cost'

Response: modified as suggested (L24)L34-37: There are too many variables in this sentence. One is unable to see what is being compared. Split the sentence to make clear what WTP is significantly higher than which with regard to systems, livelihoods, breeds

Response: The sentence split as suggested for easy reading (L34-37)

L40: Report in the affirmative rather than in the negative by turning the sentence around

Response: the sentence changed as suggested (L40-41)

L42: market-oriented system farmers

Response: modified as suggested (L 44)

L43-44: Be specific on which vaccine, which disease because your study was not on all vaccines, all diseases

Response: The vaccine knowledge was asked for livestock vaccine in general as farmers didn’t vaccinate against FMD and have no experience with FMD vaccine to give FMD vaccine specific information. This was stated in the methodology L177 and the appendix)

L56: Write UK in full; Scandinavia

Response: corrected as suggested (L 57)

L65: Do you mean endemic rather than epidemic?

Response: this was to refer to the epidemic nature of the diseases (FMD, PPR, LSD etc) which always occur in the form of outbreak instead of more or less constant number of cases throughout a year as endemic disease like mastitis or bovine paratuberculosis etc.

L67: Replace ‘vaccination’ with ‘application’ otherwise it reads like the vaccines are being vaccinated

Response: changed as suggested (L68)

L68: ‘negatively affect the effectiveness and raise the cost of vaccination’

Response. This was as compared to monovalent vaccines. When multiple strains are included in the vaccine, the host immune system exhaust and produce less immune response than when antigens are injected separately and hence reduce potency, and at the same time the cost increases because of inclusion of antigen load for each serotype. The sentences is modified to make this clear (L69-70)

L 75: Sheep and goat

Response: Corrected (L77)

L77: replace etc. with among others

Response: modified as suggested (L78)

L78: vaccine not vaccines

Response: corrected (L80)

L149: What does it mean ‘undetermined alternative’

Response: This is an option given to respondents when they could not decide ‘yes’ (agree) or ‘no’ (disagree) with proposed vaccine price. Including this option of “’undetermined or “no answer” is customary in the dichotomous bid design (see reference 5 in the manuscript).

The survey should really be in reverse. You first get the perception and knowledge of the farmers on FMD as you need them as independent variables. Then you need to make all of them understand the disease and its control by the vaccine whose attributes they need to understand before bidding because as per your background information, these farmers may not even know the vaccine. Then you pose the bidding questions. Apparently before bidding you did not explain these aspects to the farmers which makes one wonder whether they knew what they were bidding for.

Response: The first question in the questionnaire was used to verify whether the respondent did know the disease (appendix). It was only if the farmer correctly described the disease that he/she continued for the rest of the survey (this was clearly stated in line 194). Next the questionnaire describes the attributes of the vaccine the farmers are bidding for such as about its effectiveness, how it delivered and its price etc. So the concern that “the bidding questions are posed before the farmers know what they were bidding for” is not practiced. While the reverse order could have been also possible as commented, our intention was first to estimate the amount of the willingness to pay and then identify what factors could affect this willingness.

L217: Change check to check; It is not clear how multicollinearity was checked

It is rare that a backward elimination of non-significant variables will result in a model with only significant variables.

Response: “checked’ corrected (L220)

Multicollinearity was checked using variance inflation factor (VIF) and VIF value above 10 was considered as indicator of presence of multicollinearity (see reference 22). This is made clear in the revised version (L219-222).

The significant variables reported in our manuscript are those which remain significant after back ward elimination. We started with the maximum model (all variables), run the model, identify the variable with least significant p-value and drop this variable and run again, we continued until only significant variables were left in the model.

L226: What does ‘inconsistent response’ mean?

Response. If the answer for the second question cannot logically go with the answer for first question it is said inconsistent. For example. If the respondent answered he/she has no cattle for the first question, he/she should not answer the question about the breed of the cattle asked in the next question.

L227: Who gave the ‘undetermined response’ for WTP?

Response: as choices were “yes”, “no” and “undermined” (see the annexed survey) few respondents answered “undetermined’

L230: The ‘majority’ here is only about half. How were the results of the other half? Explain from the table without repetition

Response: by majority we mean 50 +1. In this question the main interest whether livestock is main source of income or not and whether willingness to pay is strong when the main source of income is livestock. So the other sources of income (crop farming, trade, employment etc.) were categorized simply as others in the analysis. We indicated this in Table 2 of the current version. But we are afraid it will be irrelevant to list the proportion of farmers with each of these income sources

Table 2: In the column, align contents conventionally; text aligned to the left and figures to the right. What is income from cattle and milk sale? Annual, monthly or what?

Response: the table formatted as suggested. The income from milk and cattle sales were asked for the preceding one year. This is indicated in the table as suggested. (Table 2)

L255-260: It is not clear how the mean WTPs were calculated

Response: Here the willingness to pay was determined form a constant only (null) interval regression model. The constant of this model is the mean willingness to pay just as the constant term of a linear regression model is the mean value of the dependent variable except that the constant in interval regression is determined using maximum likelihood estimation instead of simple average of observed values of the dependent variable as in linear regression. This estimate of willingness to pay is without the use of the knowledge of socio-demographic and husbandry characteristics of the respondents. Later in Table 6 the willingness to pay was estimated taking into account socio-demographic and husbandry characteristics of the respondents using the best model built from the potential predictors (see the response for a similar comment below). The detail of the modelling can be found in reference 21 of the manuscript.

L262: The p should be >0.05 if no significant association

Response: The place and sign of the p value is changed for more clarity (L267)

Table 4: Just indicate the reference category within the table by writing ref in the model coefficients column for the respective reference categories instead of having a footnote which is not clear

Response: modified as suggested (Table 4 and 5)

L261-265 and 272-278: Give the interpretation of the model coefficients, not just of the p value (significance). Considering the regression equation that arises from the results would help

Response: example of the interpretation of model coefficients has been given (L270-273). Interpreting all the coefficients would be monotonous as they can be easily seen in the table.

L272-276: Remove unnecessary capitalization of words

Response; The unnecessary capitalizations are corrected (L281-282)

Table 6: It is not clear how the WTP estimates were derived

As explained above for a similar comment. Here willingness to pay estimates were derived form the best interval regression models built (table 4 for all respondents and table 5 for MCL and MO respondents separately). The best models were used to predict the willingness to pay for each respondent. From these individual estimates mean and median willingness to pay were calculated. The estimation using the mode has been described in L 213-216 and detail can be found in reference 21.

L300: citation/reference?

Response: Theory for demand is changed into law of demand and reference has been given (L309)

L311: What is ‘parametrized’?

Response: Fitting the model with data obtained from double bound dichotomous questioner survey

L321-322: Correct the sentence

Response: the sentence is corrected (L330)

L328: What is ‘quality vaccine’ – you did not explain the vaccine to them

Response: the quality of vaccine was described to the farmers (in the appendix, question 2). Its efficacy was stated as 80%. According to OIE a standard potency FMD vaccine with protection percentage of 75% and above is considered as quality FMD vaccine. This has been also described L162-164

L330: What is CLM?

Response: sorry it was to mean MCL; corrected (L328)

L332: Change ‘tend’ to ‘tends’(L341)

Response: corrected

L348: Avoid an abbreviation at the beginning of a sentence

Response: written in full as suggested (L358)

L362-365: Sentence is too long and needs rephrasing for clarity

Response: the sentence is split into two to make it clear (L373-375)

L374: Correct the word knowledge

Response: corrected (L385)

In the conclusion, WTP alone is not sufficient to make the conclusion that vaccine price can be covered by farmers fully without your knowledge on their ‘ability to pay’. You need to look at their profits or how they perceive profitability from their enterprises. As is, it is possible that WTP may represent valuation of vaccination rather than actual desire to pay the amounts

Response: The willingness to pay question was asked whether they are willing to pay for the vaccine at the stated prices. So If they answer yes, it is assumed that they think that it will be worthwhile (profitable) investment to pay that amount (see L 315-317 where farmers implied this rationale) and will pay if they are asked that amount for the prevention of the disease.

L441: correct 20.20

Response: corrected (L452)

Reviewer #2: Reviewer comments:

Excellent study design, data analysis, and overall manuscript. A few suggestions below. Suggest one more read through by a strong English speaker to remove typos. Identified some below, but there are probably more, and they distract from the quality of the paper.

Response: Serious proofreading has been done to minimize the grammar and typographical errors

Line 35-36: should read “whose main livelihood is”

36 “livestock than those whose main livelihood is other than livestock,” – Rewrite, confusing

Response: the sentence is broken down for more clarity (Line 35-37).

65 – typo – should read peste

Response: corrected (Line 66)

63 onwards – May be worthwhile to mention the role of diagnostic testing in FMD vaccination as an additional challenge – alluded to but not directly mentioned

Response: Yes, most of the time vaccination complicates diagnostic testing when the vaccines are not DIVA vaccines. But for FMD there are tests which can differentiate vaccinated and non vaccinated animals such as 3ABC ELISA which are based nonstructural proteins of the virus. So relatively this is not a major problem for FMD as compared to other important disease such as PPR where such tests or DIVA vaccines are yet not developed.

78 – should read “vaccine is…”

Response: corrected (Line 80)

120 – contingent valuation is also appropriate in this situation because many people are not vaccinating.

Response : Yes, this is addressed in Line 124-3 on ‘poor adoption”

180 – should read “asked for”

Response: corrected as suggested (Line 184)

198 – should read farmers’

Response: corrected (Line 201)

199 – should read double-bounded (Line 201)

Response: corrected

347 – should read “is the main”

Response: corrected (Line356)

370 – should read “are willing to pay more”

Response: revised as suggested (Line 380)

373 – should read “pay more”

Response: revised as suggested (Line 384)

381 – should read farmers’

Response. Corrected (Line 392)

Response: corrected

385 – Should read farmers

Response: corrected (Line 396)

Gender – noticed the percentage of women respondents is very low. Do you think this is representative of the study population? Seems possible the selection of participants may bias against women if they are more likely to be at home. May be worthwhile to think more about this in the discussion.

Response: Clarification about this is added under sampling. The respondents were the head of households (Line 194) and in that setting the heads of the households are mainly males.

________________________________________

Attachment

Submitted filename: Response to reviewers comments.docx

Decision Letter 1

Simon Clegg

4 Sep 2020

PONE-D-20-17667R1

Farmers' willingness to pay for foot and mouth disease vaccine in different cattle production systems in Amhara region of Ethiopia.

PLOS ONE

Dear Dr. Jemberu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

=============================

Many thanks for submitting your manuscript to PLOS One

Your manuscript was reviewed by the same two experts in the field as the original submission, and they have suggested some more minor revisions be made to it prior to acceptance.

If you could make these revisions, and write a brief response to reviewers, it will greatly expedite revision upon resubmission

I wish you the best of luck with your revisions

Hope you are keeping safe and well in these difficult times

Thanks

Simon

==============================

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Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #2: No

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6. Review Comments to the Author

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Reviewer #1: (No Response)

Reviewer #2: Reviewer #2 Comments on PONE-D-20-17667_R1

September 3, 2020

23 vaccines

38 Remove “was also seen”

39-43 “perception that farmers would be reluctant to pay for FMD vaccine 41 is unprovable” – Be careful about how you word this. You have measured a distribution of WTP and some farmers may still have reluctance to pay. Review scientific method and do not talk about results suggesting something is unprovable.

“if official FMD vaccination is planned in the country, the vaccine cost can be covered” – Do not confuse WTP with what people will actually pay in a real life scenario. Higher WTP means respondents value the vaccine more but it does not necessarily mean “WTP scenario money” is exactly the same as real life money. Reword to say something like “market-oriented farmers with higher willingness to pay may be more likely to pay full cost if official FMD vaccination is planned in the country than mixed crop livestock farmers”

51 “the most important disease of livestock worldwide” – subjective statement. Reword.

56 Scandanavia

57 the case

63 onwards – I was not referring to DIVA vaccines but that without diagnostic testing, FMD vaccines can be poorly matched to the circulating serotype and therefore less effective. Is this applicable in Ethiopia? Address this as a constraint if so. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067263/

66 replace cheap with affordable

77 pox, among others,

138 – knew – USE SPELL CHECK!! – It is reasonable to exclude farmers who are not familiar with FMD, but this will bias your WTP estimates up. You should then be using even more caution about the statements in lines 39-43. You have systematically removed farmers likely to be reluctant to pay then claimed farmers will cover costs. Be more conservative when wording conclusions.

296 Yes yes can also mean you truncated the distribution of the higher end of the WTP distribution curve.

302 – This suggests vaccines are valued but it does not necessarily mean farmers will pay the amount stated in a hypothetical scenario. Do not misinterpret as such.

364 – List threshold used when testing for multicollinearity

382 – See previous comments. Overstating your results again.

Supporting information – misspelled supplementary

Overall: Do not overstate results – be more careful in how the conclusions are worded. Please check English again and use spell check. Include dataset of WTP bids and relevant variables from the survey referenced in the text.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Oct 2;15(10):e0239829. doi: 10.1371/journal.pone.0239829.r004

Author response to Decision Letter 1


10 Sep 2020

Response to the reviewer comments

NB: the line numbers refer to the revised version of the Manuscript with track changes

23 vaccines

Response: corrected (L23)

38 Remove “was also seen”

Response: modified as suggested (L38)

39-43 “perception that farmers would be reluctant to pay for FMD vaccine 41 is unprovable” – Be careful about how you word this. You have measured a distribution of WTP and some farmers may still have reluctance to pay. Review scientific method and do not talk about results suggesting something is unprovable.

Response: the sentence modified to address the concern (L39-41).

“if official FMD vaccination is planned in the country, the vaccine cost can be covered” – Do not confuse WTP with what people will actually pay in a real life scenario. Higher WTP means respondents value the vaccine more but it does not necessarily mean “WTP scenario money” is exactly the same as real life money. Reword to say something like “market-oriented farmers with higher willingness to pay may be more likely to pay full cost if official FMD vaccination is planned in the country than mixed crop livestock farmers”

Response: the interpretation of the results are revised to address the concern of overstating the results and the conclusions are restated accordingly (L39-44, 391-393). Moreover, in the discussion section, it has been discussed that contingent evaluation tends to overestimate the WTP as compared to actual market behavior and caution should be taken for practical application the results (L332-35).

51 “the most important disease of livestock worldwide” – subjective statement. Reword.

Response: reworded as “ARGUABLY the most important disease of livestock worldwide” (L52)

56 Scandanavia

Response: corrected (L57)

57 the case

Response: corrected (L58)

63 onwards – I was not referring to DIVA vaccines but that without diagnostic testing, FMD vaccines can be poorly matched to the circulating serotype and therefore less effective. Is this applicable in Ethiopia? Address this as a constraint if so. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067263/

Response: Yes. There are multiple serotypes of FMD virus and vaccine matching is an issue in Ethiopia as well. This problem with FMD vaccine has been mentioned in this revision (L68-70).

66 replace cheap with affordable

Response: replaced as suggested (L67)

77 pox, among others,

Response: corrected as suggested (L79)

138 – knew – USE SPELL CHECK!! (Spelling checked as suggested (L 145))

– It is reasonable to exclude farmers who are not familiar with FMD, but this will bias your WTP estimates up. You should then be using even more caution about the statements in lines 39-43. You have systematically removed farmers likely to be reluctant to pay then claimed farmers will cover costs. Be more conservative when wording conclusions.

Response: as stated in the previous comment, the conclusions have been revised to address the concern with the over optimistic interpretation of the results (L39-44, 391-393).

296 Yes yes can also mean you truncated the distribution of the higher end of the WTP distribution curve.

Response: correct. ‘yes’ ‘yes’ mean the upper bound for these respondents is higher than stated bids and shows the farmers are enthusiastic for the vaccine.

302 – This suggests vaccines are valued but it does not necessarily mean farmers will pay the amount stated in a hypothetical scenario. Do not misinterpret as such.

Response: the statement here just compared the stated mean willingness to pay to the actual price and does not necessary imply that they will pay that amount.

364 – List threshold used when testing for multicollinearity

Response: already mentioned in the material and method part i.e. VIF equal or greater than 10 was considered as indicator of multicollinearity (L225-26)

382 – See previous comments. Overstating your results again.

Response: the conclusion revised to avoid the overoptimistic interpretation (L391-393)

Supporting information – misspelled supplementary

Response: modified as supporting information (S1)

Overall: Do not overstate results – be more careful in how the conclusions are worded. Please check English again and use spell check. Include dataset of WTP bids and relevant variables from the survey referenced in the text.

Response: the overoptimistic interpretation of results are revised and the conclusion are restated accordingly (L39-44, 391-393). Spell check has been done to avoid language errors and the data set for the WTP are included as supporting information (see S2)

Attachment

Submitted filename: Response to the reveiwers comments.docx

Decision Letter 2

Simon Clegg

15 Sep 2020

Farmers' willingness to pay for foot and mouth disease vaccine in different cattle production systems in Amhara region of Ethiopia.

PONE-D-20-17667R2

Dear Dr. Jemberu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Simon Clegg, PhD

Academic Editor

PLOS ONE

Additional Editor Comments:

Many thanks for resubmitting your manuscript to PLOS One

As you have addressed all the comments, and the manuscript reads well, I have recommended it for publication

You should hear from the Editorial Office soon

It was a pleasure working with you and I wish you all the best for your future research

Hope you are keeping safe and well in these difficult times

Thanks

Simon

Acceptance letter

Simon Clegg

23 Sep 2020

PONE-D-20-17667R2

Farmers’ willingness to pay for foot and mouth disease vaccine in different cattle production systems in Amhara region of Ethiopia

Dear Dr. Jemberu:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Simon Clegg

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. Willingness to pay questionnaire survey.

    (DOCX)

    S1 Dataset

    (XLSX)

    Attachment

    Submitted filename: Response to reviewers comments.docx

    Attachment

    Submitted filename: Response to the reveiwers comments.docx

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.


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