Assessment of farmer's attitude towards the risk of tick borne diseases in Tanga, Tanzania under alternate management practices - the use of conjoint analysis

E S Swai and J Leslie*

Veterinary Investigation Centre, P O Box 1068, Arusha, Tanzania
emasw@yahoo.co.uk
* VEERU, Department of Agriculture, University of Reading, UK

Abstract

Using conjoint analysis, farmer's attitudes towards tick borne diseases (TBDs) risk under alternative husbandry practices were assessed and evaluated. Various potential management factors: Source of feeds, disease challenge, type of animals, forms of preventive methodology and regime of tick control both under different scale scenario were investigated using general linear models.

Feed, disease challenge and the method of intervention were all significant  whereas type of animals kept (F1, F2 or indigenous cattle) and form of preventive measures (spray, vaccination and pour on) were not significantly associated with deaths as perceived by farmers. Financial implication, deduced from decision tree, revealed that, under correct use of intervention, cattle kept under grazing regime in the area of study could be cost effective.

Key words: attitude, conjoint, decision tree, modeling, risk, Tanga, tick borne diseases

Introduction

Self- sufficiency in beef and milk yield has not yet been attained in Tanzania despite the country possessing over 17 million cattle (Anonymous 2004). The foundation of smallholder dairy development was laid over two decades (Anonymous 1984). During this period, crossbreeding schemes of cattle in ranches and commercial dairy farms were established in various parts of the country to improve the local cattle. Performance studies in some locations indicated encouraging trends especially with F1 cows (Mchau 1991; Msanga 1997).

Vector and vector-borne diseases, particularly (TBDs) are a major constraint of livestock production in the Tropics (Norval et al 1992; Ogden et al 2005). Quantitative economic losses caused by East coast fever (ECF) in eastern and central Africa have recently been estimated at US$ 168 million each year (Mukhebi et al 1992). In Tanzania, it is estimated that TBDs cause loss of US$ 64 million annually (Anonymous 2005). Out of this ECF alone cause a loss of US$ 35 million (Anonymous 2005). From livestock deaths reported in Tanzania for 12 years (1981-1993) it has been estimated that 72% of all mortalities were due to TBDs, with 43.7% due to theileriosis/ECF, 16.6% due to Anaplasmosis, 6.5% due to Cowdriosis (Heartwater) and 5.2% due to Babesiosis (Anonymous 2005). Of the TBDs, East Coast fever (ECF) is perceived by farmers to be the most important disease (Leslie et al 1999).

One alternative strategy to control cattle from being exposed to ticks is the use or adoption of zero grazing system. Zero grazing involves cut and carry of fodder to cattle unit for a big part of the year and requires substantial labour provision and therefore denying farmers from doing other farm activities (Swai et al 2005).

Despite of being ranked first, farmer's attitude towards TBDs risk under alternative management and husbandry practices seems to be overlapping and poorly understood. Studies aiming at assessment of attitude and identification of alternate management and husbandry practices in both small and large-scale livestock production are unavailable or scarce.

We report the revealed perceptions of husbandry and management practices and their effect on the number of animals affected by ECF in Pongwe area, Tanga district, an area recognised with ECF problem.

Materials and Methods

Study site

Tanga region is situated on the North Eastern part of Tanzania lying between Longitude 36' and 38'E and latitude 4' and 6'S. The region has heterogeneous physical and climatic features varying from hot humid coastal lowland in the East to cool Usambara Mountains in the North and semi-arid plain in the South West. Administratively, the region is divided into seven districts. The current study was conducted in Tanga district. The district is located along the Northeast coast of Tanga region. Its land area comprises of 2% of Tanga region and harbours 12% of the regions human population (Anonymous 1988). Administratively, the district comprises of four divisions (sub-counties) namely Chumbageni, Ngamiani Kaskazini, Ngamiani Kusini and Pongwe. This study was conducted in Pongwe division, an area that is considered to have high challenge of TBDs and Trypanosomosis.

Climate of the Pongwe Division

The climate is humid and hot with an average rainfall of 1356 mm/year and minimum and maximum temperature range between 23- 28 ^°C along the coast belt and slightly more towards the hinterland. Rainfall is bimodal, occurring between March and May (long rains) and between September to November (short rains).

Livestock husbandry practices in Pongwe Division

The inhabitants of Pongwe area practice both crop and livestock farming. Other important occupations include fishing and petty trading. Of the livestock farmers, majority keep traditional cattle (Tanzania Shorthorn Zebu (TSHZ), Boran) and the rest keep graded cattle mainly crosses of Taurine breeds (Friesian, Ayrshire, Jersey, Simmental) with Bos indicus breeds (TSHZ, Boran) at varying levels of exotic blood, often ranging from 50 to 85%. Graded stocks are zero grazed while traditional stocks are left to graze through-out the year.

Questionnaire design and data collection

Farmers were asked in the questionnaire survey what they did to control disease (ECF) and identify how they perceived the frequency of the disease in their area. To this end, a visual or picture based (semi-structured) questionnaire was developed and executed during the period November 1998. The questionnaire was designed based on 5 attributes (disease challenge status, method of control, frequency / regime of control, type of animals and form of feeding) each with 3 levels (ie:  good control, poor control, no control). The studied attributes and their levels were as follows (Disease challenge: levels; high, medium and low; Method of control: spray, vaccination, pour on; Frequency and regime of tick control: Correct, intermittent, in-correct; Type of animals: F1, F2, local breed; Source of feeds: cut and carry from home established pasture plot, cut and carry from communal land, grazing). Farmers were asked a series of questions involving different levels of each attribute and asked how they think would affect a proportion of animals (out of 10) affected by ECF. A group of farmers (n =30) of mixed dairy and local cattle experience and mixed periods of animal ownership convened for the exercise. Self introduction, experience with cattle farming, type of animals owned, grazing and preventive measures used for TBDs control were explained by each farmer. The questionnaire objective was then explained including unfamiliar concepts like differences between F1, F2, F3 and indigenous animals. No instruction or information was given at this stage on factors influencing ECF infection. Farmers' understanding of the questions was tested by filling in the number of animals (out of 10) that they thought would be affected in each of 27 questions given the different mix of five attributes (circumstances / husbandry practices) presented. Farmers took between 5 and 20 minutes to complete filling the form. Collected data were entered, edited and analysed using both General Linear Model (GLM) procedure of the Statistical Analysis System (SAS 1999) and Genstat (Payne et al 1993).

Statistical analysis and modelling

Using stepwise regression, a generalised linear model, with a logit link was used to explain the variation in the dependent variables, the number of 10 cattle that would be affected by East Coast fever under different management practices. Explanatory variables investigated in the best-fit model included: Disease Challenges(C), Feeding practices (F), Tick control regimes (use of intervention) (T) and individual identifier (ID).

Affected animals = Constant + C + F + T + ID

Significant differences in variables reported relate to differences between level 2 or 3 with respect to level 1 (reference variables).

Results

The results of the regression models are shown in Table 1. The variables found to be significant were challenge (high, medium, low), use ofintervention (correct, intermittent, incorrect application) and feed (cut and carry from home plot, cut and carry from communal land, grazing). In general terms: challenge levels 2 and 3 were seen as significantly different from level 1 although if all factors were held constant, there was no real difference between challenge level 2 and 3.

With feeding, there was a significant difference between level 3 (grazing) and level 1 (cut and carry from home plot) although no difference was noted between cut and carry from communal land practices (levels 1 and 2)

Variables such as cattle type (F1, F2 and local) and form of preventive treatment (spray, vaccination, spray or pour on) were not significant and excluded from the model.

A decision tree for individual farmer basing on the findings from the above were developed (Figure 1). A decision tree was considered as a framework to look at financial costs related to single farmer's decision given his /her subjective belief.

Implication out of each branch of the tree were associated with costs of each practice next to the costs of  affected animals (Table 2)

Attributed costs are shown in Table 3. The overall addition or reduction in costs compared with farmers practice (i.e. lowest risk practice) is estimated in Table 3 (sect. F). Subjective assessment and cost based on individual farmer (x) basing on the above figures (Table 2) suggest that farmer (x) could improve his/her margin by using the correct application of preventive treatment and grazing his/her animals. This would result in a 0.039 increase in the probability that an animal is affected causing a loss of $ 5.15, which could be offset against a saving in forage costs of $ 185 and net increase in margin of $ 180 per year.

Discussion

Discussions held with farmers revealed the majority seemingly only able to identify between local and dairy cattle. Indeed, it was surprising, in view of some farmers' perceptions, that the form of or type of preventive treatment did not appear to be significant in the analysis. This may be because the majority could only distinguish between acaricide and non-acaricide preventive methods while a few producers had sufficient knowledge on more than one of the methods. Broadly, two groups of farmer responses were evident. Those who feel that the probability of infection is very low if the correct preventive control is applied and those that, although thinking that correct usage is important still feel there is considerable probability that animals will be affected.

Indeed, these assessments are highly subjective. However, limitations of this work includes:

(a) Loose definition of treatment and associated costs: Incorrect (50% of treatment cost) and intermittent (75% treatment cost).

(b) Disease probability being subjective: it would be interesting to know which management practices are actually followed i.e. does the farmers appear to be acting rationally subject to his /her stated disease risk.

(c) Whether the farmer is actually aware of current practices, correct dosage or the dilutions/ applications correctly measured.

(d) Whether all additional costs associated with an animal being affected and dying are correctly incorporated. The analysis assumes that a living or dead cow has no salvage value. Some additional costs, which may need to be quantified, include i.e. loss of milk, interest on replacement animal, changing calving interval.

(f) It would be of use to know which of the 10 farmers selected and surveyed actually used acaricide in the correct way - not only if they believe they do but if they actually do. This may explain some of the variation in the individual findings.

(g) Perhaps, the use of 10 animals rather than average of 2-4 animals per farmer would influence the response from farmers. 90% of the surveyed farmers had less than five animals.

Despite the above limitations, some observations might be of value from the findings of this study. The information gathered may serve as a first step towards improved decision- making on disease management (i.e. tick control) avoidance and formulation of rational cattle keeping, and feeding management practices on smallholder dairy farms in this coastal region of Tanzania.

Acknowledgements

We thank participating farmers in Pongwe area for being cooperative. Statistical advice from University of Reading (Statistical dept) is gratefully appreciated. Thanks are also due to various keen experts for proof reading the manuscript and for their valuable comments. Permission to publish this work was granted by the Director of Veterinary Services- Ministry of Water and Livestock development. Financial assistance from DFID- Animal Health Research programme is gratefully acknowledged.

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