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ECONOHEALTH: Placing helminth infections of livestock in an economic and social context
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ECONOHEALTH: Placing helminth infections of livestock in an economic and social context Johannes Charlier a,b,∗ , Fiona Vande Velde a,c , Mariska van der Voort d , Jef Van Meensel d , Ludwig Lauwers d,e , Verolien Cauberghe c , Jozef Vercruysse a , Edwin Claerebout a a
Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, Merelbeke 9820, Belgium Avia-GIS, Risschotlei 33, Zoersel 2980, Belgium c Department of Communication Studies, Faculty of Political and Social Sciences, Ghent University, Korte Meer 7–11, Gent 9000, Belgium d Social Sciences Unit, Institute for Agricultural and Fisheries Research (ILVO), Burg. Van Gansberghelaan 115, Merelbeke 9820, Belgium e Department of Agricultural Economics, Faculty of Bio-Engineering, Ghent University, Coupure Links 653, Ghent 9000, Belgium b
a r t i c l e
i n f o
Article history: Received 24 March 2015 Received in revised form 4 June 2015 Accepted 14 June 2015 Keywords: Helminth Livestock Fasciola hepatica Nematodes Farmer behaviour Economics of animal health Social context
a b s t r a c t Livestock farming is central to global food security and to the sustainability of rural communities throughout Europe. Animal health management has a major impact on farming efficiency. Although animal health research has provided effective prevention strategies for the major endemic diseases of livestock, these strategies typically provide solutions for single infectious diseases and they are often not adequately implemented due to farm-specific constraints. We propose a concept termed “ECONOHEALTH” which aims at including the economic and social context in our understanding of the factors that drive animal health. The concept is elaborated on using the example of the major helminthic diseases of cattle in temperate climate regions (gastrointestinal nematodes, liver fluke and lungworm). By considering major diseases simultaneously and placing disease-complexes in an economic and a social context, we believe that insights will be generated upon which more integrated, situation-adapted and thus more effective prevention strategies can be devised. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Livestock farming is central to the sustainability of rural communities around the world, as well as being socially, economically and politically highly significant at national and international levels. Agriculture in general is being asked to intensify production from a shrinking natural resource base to feed another three billion people over the next 50 years (Herrero and Thornton, 2013). It is inevitable that the production of animal products will also have to expand to meet the demands of an increasing and changing world population and that a large part of this expansion will have to come from increases in efficiency. In the meantime, the competitiveness of European livestock farms is challenged by more critical social expectations (e.g. animal welfare, environmental sustainability), increasing competition for raw materials and climate change. The pressure on farm income has increased due to higher production costs and fluctuating output prices (Thornton, 2010).
∗ Corresponding author. Fax: +32 9 264 74 96. E-mail address: [email protected] (J. Charlier).
Animal health issues, have a major impact on farming efficiency. According to the OIE, world production of food animals is reduced by more than 20% due to disease (Vallat, 2009). These diseases can be divided in different groups (e.g. transboundary vs. production diseases) that correspond to different decision makers for control measures. The term “production disease” applies to diseases (infectious or non-infectious) that are caused or enhanced by management or nutritional factors and affect efficient livestock production. In contrast to transboundary or zoonotic diseases where control measures are mostly taken collectively by policy interventions, their control remains the individual responsibility of the farmer. Although the impact of production diseases is often subtle, these diseases can have a large effect on the economic profitability of farms (Van Meensel et al., 2010). Animal health research has provided effective prevention strategies for the major production diseases of livestock, but the uptake of these strategies remains modest and the economic impacts non-deniable. The objective of this paper is to propose the concept termed “ECONOHEALTH” to address the above stated challenges in animal health. It aims to integrate knowledge from the veterinary sciences, agricultural economics and social sciences with the common
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Fig. 1. The traditional determinants of disease. The balance of risk factors and protective factors that determine health status depend on the interaction of the components of the epidemiologic triad: host, agent and environment, all of which are influenced by management practices (from LeBlanc et al., 2006).
shared objective of improving farming resilience by more integrated, economic and accepted animal health advices. We start with reviewing the multifactorial nature and the traditional (known) drivers of animal diseases. Next, we argue that by including socioeconomic sciences in animal health research, major advancements in disease control can be made. Finally, we propose a roadmap how the ECONOHEALTH concept could be elaborated for the concrete case of helminth infections in dairy cattle . 2. The multifactorial nature of animal disease A fundamental advance in the health management of livestock has been the recognition of the multifactorial nature of almost all diseases of importance (LeBlanc et al., 2006). This concept was graphically presented by LeBlanc et al. (2006) in the so-called epidemiologic triad (Fig. 1), illustrating the different determinants of disease. Epidemiology has been extensively used to describe and quantify the multiple risk factors that produce disease. In turn, health management or production medicine is characterized by an integrated, holistic, proactive, databased, and economically framed approach to prevention of disease and enhancement of performance. Health management has been defined as the promotion of health, improvement of productivity, and prevention of disease in animals within the economic framework of the owner and industry, while recognizing animal welfare, food safety, public health, and environmental sustainability (LeBlanc et al., 2006). Veterinarians are traditionally the primary advisor on animal health related issues. To deliver health management and effective disease prevention veterinarians must integrate recommendations of best practices into whole-farm management systems. The profession needs to evolve from task-oriented providers of therapy to adviceoriented consultants. Yet, it continues to struggle with transferring its knowledge, which could be ascribed to the fact that economic and social factors related to animal health decisions are poorly integrated in current advices (Derks et al., 2011; Saddiqi et al., 2012). 3. Traditional drivers of animal helminthic disease: climate, environment and management practices Many animal diseases have a strong climatic and environmental component. As an example, the development and death rates of the free-living stages of helminths and the population dynamics of the snail intermediate hosts are strongly influenced by climate, and this
underpins seasonal patterns of infection in temperate areas (van Dijk et al., 2010). Using geographical information system derived variables such as digital elevation models, land use, land cover and hydrological maps and remote sensing derived variables such as land surface temperature and vegetation indices, researchers have explored risk factors in addition to data on rainfall and temperature by constructing models providing the best fit for estimates of helminth abundance. Significant but region-dependent predictors such as soil pH, the slope of land and irrigation and elevation were identified (Durr et al., 2005; McCann et al., 2010). More recently, it was shown that in addition to the eco-climatic factors describing the parasite’s environment, the inclusion of farm management factors such as the mowing of pastures and the length of the grazing season are vital for the correct prediction of infection risk (Bennema et al., 2011). The remaining problem is that while multiple risk factors and their interactions for the important enzootic diseases of dairy cattle are increasingly described, how certain risk factors act simultaneously on different diseases remains largely unknown. Consequently, prevention strategies for enzootic diseases typically provide solutions for a single disease and it is largely unknown whether a protective measure for a specific pathogen would also protect against other parasitic, bacterial or viral infections, or would rather aggravate these diseases. Positive and negative correlations between different helminth infections or between a helminth infection and specific bacterial infections have been described (Mulcahy et al., 2004). Such common patterns can be caused by interactions at the level of the animal’s immune system (Claridge et al., 2012; Flynn et al., 2007) but also by common risk factors and these have been insufficiently explored (Biggeri et al., 2007).
4. Broadening our perspective on animal health management: including farmer behaviour and farm economics 4.1. Farmer behaviour Animal farming is evolving worldwide: industrialization and increasing international competition have led to a whole new farming approach (Derks et al., 2013). “The farm” as we knew it does no longer exist but it has become an agricultural production business included in the global economy. In turn, livestock enterprises are faced with challenges in maintaining a competitive position and need to restructure their production to meet market demands (Hansson and Ferguson, 2011). The farmer has become an entrepreneur and farm management has taken over old-school farming. As stated above, in the meantime also society as a whole is changing with increasing concerns on environmental impact, (over) usage of chemical drugs, animal welfare and emerging zoonoses (Derks et al., 2012). Farmers are thus being challenged: on one hand to make profit in a competitive market, and on the other hand to meet the increasing societal demands. This makes the decision making of the farmer and his behaviour complex, involving factors like behavioural intention, social environment and attitude (Derks et al., 2012). To understand farmers’ behaviour and decision making in animal disease control, it is thus necessary to create a framework in which those factors and their interrelations are included. From a historical perspective, researchers and veterinarians assumed that a farmer’s decision was based primarily on extrinsic motivations, i.e. rational, technical and economic considerations (Burton, 2004). Livestock farming is a business, thus external factors such as market price and customer demands have an important influence on decision-making processes. However, it is now evident that farmers’ decision-making is also influenced by intrinsic factors like attitude, risk perception, social norms and trust (Jansen
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and Lam, 2012; Jansen et al., 2009). One reason is that farming activities are typically strongly intertwined with lifestyle and family-life, leading to decisions that cannot always be explained by external, economic factors (Garforth et al., 2006; Valeeva et al., 2007). This highlights the need to use socio-psychological models that incorporate the influences of intrinsic motivations on farmers’ decision-making processes, whilst still considering the extrinsic factors (Ellis-Iversen et al., 2010). This area of social epidemiology is widely used in human health policy making but is only recently emerging in animal health research (Ellis-Iversen et al., 2010). Intrinsic factors have been studied in animal health issues such as mastitis management, implementation of zoonotic control programs, the use of antimicrobials in feedlot cattle and the participation in foot-and-mouth disease detection and control (Delgado et al., 2012; Ellis-Iversen et al., 2010; Jansen and Lam, 2012; Mcintosh et al., 2009). However, what is still missing is the development of conceptual models based on theoretic frameworks from human behaviour sciences that identify all the important factors to predict farmer behaviour. The “Theory of Planned Behavior” (TPB) (Ajzen, 1991) is one of the most successful theoretic frameworks in research of human behaviour. Nevertheless, the TPB framework can be expanded and improved through the incorporation of additional variables (Armitage and Conner, 2001) from other socio-psychological and economical theories such as the “Health Belief Model” (Janz and Becker, 1984), the “Risk Information Seeking and Processing model” (Griffin et al., 1999) or the “Temporal self-regulation theory” (Hall and Fong, 2010). 4.2. Farm economics Research addressing the economic impact of helminth infections and other animal diseases has typically studied the effect on technical key performance indicators such as weight gain, milk yield or reproductive measures. Next, observed losses are converted into an economic value (Charlier et al., 2014). As an example in Belgian dairy herds, the annual cost per adult cow ranged between D 4 and113 and between D 0 and 77 for GI nematode and liver fluke infections, respectively (Charlier et al., 2012b). This approach has the advantage that it provides insights into animal performance and is easily explained to farmers. However, these current approaches do not reflect the effect on the whole-farm economic performance (Rushton, 2009). Moreover, they typically use average figures (e.g. average production impact or prices) and thus lack farm-specificity. A novel approach to address these problems has been proposed, based on efficiency analysis (van der Voort et al., 2013). Efficiency analysis aims to identify inefficiency levels by comparing the current performance level of farms with their potential optimal performance level (Farrell, 1957) by analysing the process of converting input(s) into output(s) (Coelli et al., 2005). Efficiency studies have been previously applied in animal health research (Barnes et al., 2011; Lawson et al., 2004). These studies focus on identifying a link between the technical efficiency of farms and indices of disease or certain control strategies. Besides integrality, a major advantage of efficiency analysis, is the possibility to link an animal disease or its diagnosis to input allocation, which is at the core of farmer’s decision making. The economic performance of a farm is not only influenced by technical efficiency, but also by input allocation (i.e. the combination in which inputs are used) (van der Voort et al., 2013). However, the way farmers allocate their inputs may also affect the level or occurrence of disease and the effectiveness of a control strategy. As a simple example, maximal use of grazed pasture is considered an economic way for feed supply of ruminants (White et al., 2002). However, farms relying heavily on pasture may suffer from higher levels of helminth infection impairing productivity and technical efficiency. The issue is thus to find the optimal allocation of pasture,
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Fig. 2. The epidemiologic socio-economic triad. Animal disease, farm economics and social satisfaction are interrelated factors that determine farm sustainability. All of these factors are influenced by human behaviour.
roughage and concentrates in which the economic performance is maximized, given the farm-specific constraints and input prices. This broadening of our perspective on animal health management could be depicted in the so-called epidemiologic socio-economic triad. Animal disease, farm economics and social satisfaction are interrelated factors that determine farm sustainability. All of these factors are influenced by human behaviour (Fig. 2). 5. Applying ECONOHEALTH on the case of parasitic helminth infections in dairy cattle 5.1. Background The EU is the largest producer of milk products in the world and dairy farming is traditionally one of the most profitable sectors in EU agriculture (OECD-FAO, 2013). Of the many infectious diseases that affect dairy cattle, infections with parasitic helminths are among those with the greatest impact on animal productivity (Charlier et al., 2014). All herds with a grass-based production system are infected with these helminths. The disease complex consists mainly of infections with gastrointestinal nematodes (GIN), liver fluke and lungworms. Whereas liver fluke and lungworm infections are commonly caused by a single species, Fasciola hepatica and Dictyocaulus viviparus, respectively; GIN infections comprise > 20 different species but the most prevalent and important species are Ostertagia ostertagi and Cooperia oncophora, which usually occur together. In young cattle, mortalities can be high when no preventive measures are taken. However, the main effect of parasitism is due to sub-clinical infections causing reduced growth, milk yield and reproductive performance. These costs have become increasingly important in the current economic climate with the low profit margins in the livestock sector. In addition, experiments in small ruminants have shown that inadequate preventive measures against GIN, result in an extra 10% emission of CO2 per kg of weight gain and that disease control can contribute to a reduction in greenhouse gas emissions from animal agriculture and help reduce the carbon footprint of livestock farming (Kenyon et al., 2013). We believe that this case, consisting of 3 different infections (GIN, liver fluke and lungworms) can be fertile soil to elaborate the ECONOHEALTH concept, leading to new and integrated prevention strategies. We propose to do this by:
Please cite this article in press as: Charlier, J., et al., ECONOHEALTH: Placing helminth infections of livestock in an economic and social context. Vet. Parasitol. (2015), http://dx.doi.org/10.1016/j.vetpar.2015.06.018
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(1) Revealing the environmental, climatic and management drivers of co-infections with GIN, liver fluke and lungworm; (2) Understanding farmers’ risk attitudes and behaviour in helminth control; (3) Assessing the role of the GIN, liver fluke and lungworm in the whole-farm economic context; (4) Integration of the different drivers of animal health: climate, environment, management, farm economics and human behaviour; (5) Development of decision support tools and communicative advices. 5.2. Environmental, climatic and management drivers of co-infections with GIN, liver fluke and lungworm Risk factors for individual diseases are increasingly described. In contrast, how different risk factors act simultaneously on different diseases remains largely unknown. Helminth infections typically show some level of spatial and spatio-temporal variability. The recent GLOWORM project (www.gloworm.eu) funded under the European Commission’s 7th framework programme, delivered guidelines for standardized and harmonized cross-sectional surveys of helminth parasites in ruminants allowing the development of updated prevalence maps and multiscale spatial models for the European area (Ducheyne et al., 2015; Rinaldi et al., 2015a,b). However, the available spatial and spatio-temporal models have considered each species separately and similarities/dissimilarities in risk distributions remain to be characterized (Bennema et al., 2009). Common spatial patterns of infections can be detected and used as potential markers of common drivers of infection. Multivariate disease mapping can cope with this problem as was recently shown for the case of helminth infections in sheep (Biggeri et al., 2007; Musella et al., 2011). These authors developed multivariate spatial Bayesian hierarchical models to describe common patterns of disease. Second, the underlying factors need to be identified to explain the observed patterns using environmental, climatic and herd management variables, derived from geographical information systems, satellite sensors and questionnaires (Rinaldi et al., 2006). Thus, by developing a multivariate approach that takes into account spatial dependency of helminth infections, common disease patterns of cattle can be discovered and the underlying risk factors of a disease “complex” or co-infections instead of a single disease can be assessed.
The novel framework was tested in the population of Flemish dairy farmers. The results showed that ‘attitude towards diagnostic methods’ and ‘subjective norm’; i.e. the influence of significant others, had the strongest, positive influence on adoption intention of diagnostic methods. ‘Attitude towards the use of anthelmintic drugs’ had a negative effect on adoption intention of the diagnostic methods. This implicates that farmers will be more intended to adopt diagnostics if they have a positive attitude for diagnostics and if they feel some sort of social pressure to adopt these methods. ‘Attitude towards the preventive use of anthelmintic drugs’ had a negative effect on adoption intention of the diagnostic methods. Concretely, the more positive someone perceives the preventive use of anthelminthic drugs, the less motivated they will be to adopt diagnostics. This implicates an effect of their current behaviour (i.e. preventive use of anthelmintics) on future adoption intentions. This raises the question whether farmers’ attitude towards anthelminthics should first be lowered before they can be convinced to adopt diagnostic methods.
5.4. Assessing the role of GIN, liver fluke and lungworm in the whole farm economic context In a study using efficiency analysis, a negative relationship between antibody levels to GIN in bulk tank milk and technical efficiency was observed (van der Voort et al., 2014). GIN infections appeared to mainly constrain the efficient transformation of pasture, health related costs and labour into milk. In addition, the GIN-associated inefficiency was mitigated when higher levels of concentrates and roughage were supplied. Recently, this approach was further elaborated to clarify the relationship between GIN exposure, input allocation, technical efficiency and economic performance of farms (M. van der Voort, unpublished observations). It was concluded that determining the position of farms in an inputoutput efficiency framework could improve the advice regarding GIN control. It provides a way to simultaneously optimize the level of exposure to GIN and the economic performance of a specific farm. The future challenge is to expand this approach by including other pathogens. This challenge is not trivial. Including co-infections will have to deal with correlated infections and inefficiency scores will have to be split in shared and specific effects for each helminth requiring advanced statistical methods.
5.3. Understanding farmers’ risk attitudes and behaviour in helminth control
5.5. Integration of traditional knowledge with novel insights from socio-economic studies
The available literature on livestock farmers’ behaviour in animal health is related to very specific issues. Social research on the control of helminth infections is absent, and a generic understanding is missing. Qualitative research is thus still necessary to fill in the gaps of the literature, and to construct working hypotheses for quantitative studies. This can be addressed by in-depth interviews including the different stakeholders in helminth control: farmers, veterinarians and external experts (covering farmer and animal health organisations, academics and industry). Based on the results of the qualitative research and the scientific literature, theoretical frameworks can be drawn. These should then be validated by the use of large-scale surveys. As an example, we developed a theoretical framework to predict the farmers’ intention to adopt diagnostic methods before implementing anthelmintic drugs in cattle by combining 2 fundamental, cognitive theories in the field of behavioural psychology (“Theory of Planned Behavior”; Ajzen, 1991) and health psychology (“Health Belief Model”; Janz and Becker, 1984) (F. Vande Velde, unpublished observations).
How can the traditional knowledge regarding the epidemiology of helminth infections be combined with the novel insights generated through sociological and economic studies in a single framework where the relative importance of different drivers can be unravelled? Many of the identified drivers will be interrelated and it will be difficult to differentiate direct effects from mediated effects. One approach could be to use structural equation models (SEMs) to deal with such an interrelation of risk factors. SEMs are multivariate or multi-equation regression models in which the response variable in one regression equation may appear as a predictor in another equation (Bollen, 1989). As a result, variables in a SEM may influence each other, either directly or indirectly, i.e., through intermediate variables. SEMs are typically specified in the form of so-called path diagrams. Using path diagrams, we can depict the causal hypotheses of direct and mediating effects of environment, farmer attitude and input use to explain observed herd characteristics that describe level of infection and economic performance (Detilleux et al., 2012).
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5.6. Decision support tools Due to the increased understanding and complexity of disease processes, the success of ECONOHEALTH will depend on the development of successful decision support tools and communicative advices. For instance, during the recent EU FP7 GLOWORM project (www.gloworm.eu), the development of several decision support tools was initiated. These included tools to predict the transmission risk of parasites on pasture (Rose et al., 2015; Verschave et al., 2014), the economic impact at herd level of helminth infections or anthelmintic treatment strategies (Charlier et al., 2012a,b) or anthelmintic efficacy based on faecal egg count reduction (Torgerson et al., 2014). However, there are some critical factors that need to be further looked at in the development of successful decision support tools: perceived usefulness, accessibility, flexibility, credibility, maintenance and adaptability (McCown, 2002). Recently, we organised 2 focus group meetings with veterinarians and farmers in Flanders (Belgium) to identify the user needs for software applications on helminth control in cattle. The meetings revealed that the currently available tools only partially address the user needs. Moreover, there are great differences in the needs for veterinarians versus farmers. Further and closer collaboration between the model-makers and model-users is required and business cases need to be developed so that the tools can be self-sustainable. 5.7. Communicative advices When novel prevention strategies contrast with long established traditions or perceptions, it is known to be difficult to convince farmers of their implementation, even when there is a base of evidence of their comparative advantage (Cabaret et al., 2009). Here, as parasitologists we should collaborate with communication scientists and social marketers in order to convey the novel insights. The insights from sociological studies into farmer’s behaviour regarding helminth control can be applied in communication strategies. As an example, in a recent study, we showed that risk perception of anthelmintic resistance had no effect on the adoption intention of diagnostic methods (F. Vande Velde, unpublished observations). This suggests that in communications promoting sustainable anthelmintic control practices (i.e. with a low selection pressure for anthelmintic resistance), using the threat of anthelmintic resistance is not going to change farmer’s behaviour immediately. Better incentives are likely positive messages to increase the attitude towards diagnostic methods in helminth control and/or lower the attitude towards anthelmintic drugs. The efficacy of these and other incentives should still be experimentally confirmed. 6. Concluding remarks Major advances in animal health management are required in order to address the societal needs to sustainably intensify livestock production from a shrinking natural resource base and ensure food security. Policy makers, chain partners and sector organisations try to influence farmer’s behaviour in order to meet these societal needs. There is considerable focus on production diseases, including helminth infections because efficient management of these diseases is a way to further improve the productivity and welfare of our livestock (Arnold, 2013). In the past, animal health research has provided effective prevention strategies for the major endemic diseases of livestock but these strategies typically provide solutions for single infectious diseases and they are often not implemented because they insufficiently consider the economic and social context of the farm unit. By including the economic and
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social context in our understanding of the factors that drive animal health, and in particular helminth infections of farmed ruminants, more comprehensive prevention strategies can be developed. We believe that this will result in the development of novel concepts and tools for animal health management and will enhance individual entrepreneurship, social satisfaction and thus the resilience of the livestock sector. Acknowledgements JC would like to express his gratitude to Sien Verschave, Brecht Devleesschauwer and Bruno Levecke (Laboratory of Parasitology, Ghent University), Erwin Wauters (Institute of Agriculture and Fisheries Research, ILVO), Guido Van Huylenbroeck (Department of Agricultural Economics, Ghent University), Liselot Hudders (Department of Communication Studies, Ghent University), Henk Hogeveen (Farm Animal Health Department, Utrecht University), Annibale Biggeri (University of Florence) and Guy Hendrickx (AviaGIS) for their support, discussions and motivations which allowed him to develop the ideas presented in the current manuscript. JC would also like to acknowledge the EU FP7 GLOWORM project (Grant agreement no 288,975CP-TP-KBBE.2011.1.3-04), which allowed him to conduct research in the last 3 years. References Ajzen, I., 1991. The theory of planned behavior. Organiz. Behav. Hum. Decis. Process. 50, 179–211. Armitage, C.J., Conner, M., 2001. Efficacy of the theory of planned behaviour: a meta-analytic review. Br. J. Soc. Psychol. 40, 471–499. Arnold, C., 2013. Infectious diseases associated with livestock production: mitigating future risks. Environ. Health Perspect. 121, a256. Barnes, A.P., Rutherford, K.M.D., Langford, F.M., Haskell, M.J., 2011. The effect of lameness prevalence on technical efficiency at the dairy farm level: an adjusted data envelopment analysis approach. J. Dairy Sci. 94, 5449–5457. Bennema, S., Vercruysse, J., Claerebout, E., Schnieder, T., Strube, C., Ducheyne, E., Hendrickx, G., Charlier, J., 2009. The use of bulk-tank milk ELISAs to assess the spatial distribution of Fasciola hepatica, Ostertagia ostertagi and Dictyocaulus viviparus in dairy cattle in Flanders (Belgium). Vet. Parasitol. 165, 51–57. Bennema, S.C., Ducheyne, E., Vercruysse, J., Claerebout, E., Hendrickx, G., Charlier, J., 2011. Relative importance of management, meteorological and environmental factors in the spatial distribution of Fasciola hepatica in dairy cattle in a temperate climate zone. Int. J. Parasitol. 41, 225–233. Biggeri, A., Catelan, D., Dreassi, E., Rinaldi, L., Musella, V., Veneziano, V., Cringoli, G., 2007. Multivariate spatially-structured variability of ovine helminth infections. Geospat. Health 2, 97–104. Bollen, K.A., 1989. Structural Equations with Latent Variables. Wiley, New York. Burton, R.J.F., 2004. Reconceptualising the ‘behavioural approach’ in agricultural studies: a socio-psychological perspective. J. Rural Stud. 20, 359–371. Cabaret, J., Benoit, M., Laignel, G., Nicourt, C., 2009. Current management of farms and internal parasites by conventional and organic meat sheep French farmers and acceptance of targeted selective treatments. Vet. Parasitol. 164, 21–29. Charlier, J., Levecke, B., Devleesschauwer, B., Vercruysse, J., Hogeveen, H., 2012a. The economic effects of whole-herd versus selective anthelmintic treatment strategies in dairy cows. J. Dairy Sci. 95, 2977–2987. Charlier, J., van der Voort, M., Hogeveen, H., Vercruysse, J., 2012b. ParaCalc® - a novel tool to evaluate the economic importance of worm infections on the dairy farm. Vet. Parasitol. 184, 204–211. Charlier, J., van der Voort, M., Kenyon, F., Skuce, P., Vercruysse, J., 2014. Chasing helminths and their economic impact on farmed ruminants. Trends Parasitol. 30, 361–367. Claridge, J., Diggle, P., McCann, C.M., Mulcahy, G., Flynn, R., McNair, J., Strain, S., Welsh, M., Baylis, M., Williams, D.J.L., 2012. Fasciola hepatica is associated with the failure to detect bovine tuberculosis in dairy cattle. Nat. Commun. 3. Coelli, T.J., Rao, D.S.P., O’ Donnell, C.J., Battese, G.E., 2005. An Introduction to Efficiency and Productivity Analysis, 2nd ed. Springer Science and Business Media. Delgado, A.H., Norby, B., Dean, W.R., McIntosh, W.A., Scott, H.M., 2012. Utilizing qualitative methods in survey design: examining Texas cattle producers’ intent to participate in foot-and-mouth disease detection and control. Prev. Vet. Med. 103, 120–135. Derks, M., van Werven, T., Kremer, W.D.J., Hogeveen, H., 2011. Veterinary on-farm counselling on dairy farms: the veterinarians’ vision. Udder Health Commun., 179–185. Derks, M., van de Ven, L.M.A., van Werven, T., Kremer, W.D.J., Hogeveen, H., 2012. The perception of veterinary herd health management by Dutch dairy farmers and its current status in the Netherlands: a survey. Prev. Vet. Med. 104, 207–215.
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ECONOHEALTH: Placing helminth infections of livestock in an economic and social context Johannes Charlier a,b,∗ , Fiona Vande Velde a,c , Mariska van der Voort d , Jef Van Meensel d , Ludwig Lauwers d,e , Verolien Cauberghe c , Jozef Vercruysse a , Edwin Claerebout a a
Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, Merelbeke 9820, Belgium Avia-GIS, Risschotlei 33, Zoersel 2980, Belgium c Department of Communication Studies, Faculty of Political and Social Sciences, Ghent University, Korte Meer 7–11, Gent 9000, Belgium d Social Sciences Unit, Institute for Agricultural and Fisheries Research (ILVO), Burg. Van Gansberghelaan 115, Merelbeke 9820, Belgium e Department of Agricultural Economics, Faculty of Bio-Engineering, Ghent University, Coupure Links 653, Ghent 9000, Belgium b
a r t i c l e
i n f o
Article history: Received 24 March 2015 Received in revised form 4 June 2015 Accepted 14 June 2015 Keywords: Helminth Livestock Fasciola hepatica Nematodes Farmer behaviour Economics of animal health Social context
a b s t r a c t Livestock farming is central to global food security and to the sustainability of rural communities throughout Europe. Animal health management has a major impact on farming efficiency. Although animal health research has provided effective prevention strategies for the major endemic diseases of livestock, these strategies typically provide solutions for single infectious diseases and they are often not adequately implemented due to farm-specific constraints. We propose a concept termed “ECONOHEALTH” which aims at including the economic and social context in our understanding of the factors that drive animal health. The concept is elaborated on using the example of the major helminthic diseases of cattle in temperate climate regions (gastrointestinal nematodes, liver fluke and lungworm). By considering major diseases simultaneously and placing disease-complexes in an economic and a social context, we believe that insights will be generated upon which more integrated, situation-adapted and thus more effective prevention strategies can be devised. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Livestock farming is central to the sustainability of rural communities around the world, as well as being socially, economically and politically highly significant at national and international levels. Agriculture in general is being asked to intensify production from a shrinking natural resource base to feed another three billion people over the next 50 years (Herrero and Thornton, 2013). It is inevitable that the production of animal products will also have to expand to meet the demands of an increasing and changing world population and that a large part of this expansion will have to come from increases in efficiency. In the meantime, the competitiveness of European livestock farms is challenged by more critical social expectations (e.g. animal welfare, environmental sustainability), increasing competition for raw materials and climate change. The pressure on farm income has increased due to higher production costs and fluctuating output prices (Thornton, 2010).
∗ Corresponding author. Fax: +32 9 264 74 96. E-mail address: [email protected] (J. Charlier).
Animal health issues, have a major impact on farming efficiency. According to the OIE, world production of food animals is reduced by more than 20% due to disease (Vallat, 2009). These diseases can be divided in different groups (e.g. transboundary vs. production diseases) that correspond to different decision makers for control measures. The term “production disease” applies to diseases (infectious or non-infectious) that are caused or enhanced by management or nutritional factors and affect efficient livestock production. In contrast to transboundary or zoonotic diseases where control measures are mostly taken collectively by policy interventions, their control remains the individual responsibility of the farmer. Although the impact of production diseases is often subtle, these diseases can have a large effect on the economic profitability of farms (Van Meensel et al., 2010). Animal health research has provided effective prevention strategies for the major production diseases of livestock, but the uptake of these strategies remains modest and the economic impacts non-deniable. The objective of this paper is to propose the concept termed “ECONOHEALTH” to address the above stated challenges in animal health. It aims to integrate knowledge from the veterinary sciences, agricultural economics and social sciences with the common
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Fig. 1. The traditional determinants of disease. The balance of risk factors and protective factors that determine health status depend on the interaction of the components of the epidemiologic triad: host, agent and environment, all of which are influenced by management practices (from LeBlanc et al., 2006).
shared objective of improving farming resilience by more integrated, economic and accepted animal health advices. We start with reviewing the multifactorial nature and the traditional (known) drivers of animal diseases. Next, we argue that by including socioeconomic sciences in animal health research, major advancements in disease control can be made. Finally, we propose a roadmap how the ECONOHEALTH concept could be elaborated for the concrete case of helminth infections in dairy cattle . 2. The multifactorial nature of animal disease A fundamental advance in the health management of livestock has been the recognition of the multifactorial nature of almost all diseases of importance (LeBlanc et al., 2006). This concept was graphically presented by LeBlanc et al. (2006) in the so-called epidemiologic triad (Fig. 1), illustrating the different determinants of disease. Epidemiology has been extensively used to describe and quantify the multiple risk factors that produce disease. In turn, health management or production medicine is characterized by an integrated, holistic, proactive, databased, and economically framed approach to prevention of disease and enhancement of performance. Health management has been defined as the promotion of health, improvement of productivity, and prevention of disease in animals within the economic framework of the owner and industry, while recognizing animal welfare, food safety, public health, and environmental sustainability (LeBlanc et al., 2006). Veterinarians are traditionally the primary advisor on animal health related issues. To deliver health management and effective disease prevention veterinarians must integrate recommendations of best practices into whole-farm management systems. The profession needs to evolve from task-oriented providers of therapy to adviceoriented consultants. Yet, it continues to struggle with transferring its knowledge, which could be ascribed to the fact that economic and social factors related to animal health decisions are poorly integrated in current advices (Derks et al., 2011; Saddiqi et al., 2012). 3. Traditional drivers of animal helminthic disease: climate, environment and management practices Many animal diseases have a strong climatic and environmental component. As an example, the development and death rates of the free-living stages of helminths and the population dynamics of the snail intermediate hosts are strongly influenced by climate, and this
underpins seasonal patterns of infection in temperate areas (van Dijk et al., 2010). Using geographical information system derived variables such as digital elevation models, land use, land cover and hydrological maps and remote sensing derived variables such as land surface temperature and vegetation indices, researchers have explored risk factors in addition to data on rainfall and temperature by constructing models providing the best fit for estimates of helminth abundance. Significant but region-dependent predictors such as soil pH, the slope of land and irrigation and elevation were identified (Durr et al., 2005; McCann et al., 2010). More recently, it was shown that in addition to the eco-climatic factors describing the parasite’s environment, the inclusion of farm management factors such as the mowing of pastures and the length of the grazing season are vital for the correct prediction of infection risk (Bennema et al., 2011). The remaining problem is that while multiple risk factors and their interactions for the important enzootic diseases of dairy cattle are increasingly described, how certain risk factors act simultaneously on different diseases remains largely unknown. Consequently, prevention strategies for enzootic diseases typically provide solutions for a single disease and it is largely unknown whether a protective measure for a specific pathogen would also protect against other parasitic, bacterial or viral infections, or would rather aggravate these diseases. Positive and negative correlations between different helminth infections or between a helminth infection and specific bacterial infections have been described (Mulcahy et al., 2004). Such common patterns can be caused by interactions at the level of the animal’s immune system (Claridge et al., 2012; Flynn et al., 2007) but also by common risk factors and these have been insufficiently explored (Biggeri et al., 2007).
4. Broadening our perspective on animal health management: including farmer behaviour and farm economics 4.1. Farmer behaviour Animal farming is evolving worldwide: industrialization and increasing international competition have led to a whole new farming approach (Derks et al., 2013). “The farm” as we knew it does no longer exist but it has become an agricultural production business included in the global economy. In turn, livestock enterprises are faced with challenges in maintaining a competitive position and need to restructure their production to meet market demands (Hansson and Ferguson, 2011). The farmer has become an entrepreneur and farm management has taken over old-school farming. As stated above, in the meantime also society as a whole is changing with increasing concerns on environmental impact, (over) usage of chemical drugs, animal welfare and emerging zoonoses (Derks et al., 2012). Farmers are thus being challenged: on one hand to make profit in a competitive market, and on the other hand to meet the increasing societal demands. This makes the decision making of the farmer and his behaviour complex, involving factors like behavioural intention, social environment and attitude (Derks et al., 2012). To understand farmers’ behaviour and decision making in animal disease control, it is thus necessary to create a framework in which those factors and their interrelations are included. From a historical perspective, researchers and veterinarians assumed that a farmer’s decision was based primarily on extrinsic motivations, i.e. rational, technical and economic considerations (Burton, 2004). Livestock farming is a business, thus external factors such as market price and customer demands have an important influence on decision-making processes. However, it is now evident that farmers’ decision-making is also influenced by intrinsic factors like attitude, risk perception, social norms and trust (Jansen
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and Lam, 2012; Jansen et al., 2009). One reason is that farming activities are typically strongly intertwined with lifestyle and family-life, leading to decisions that cannot always be explained by external, economic factors (Garforth et al., 2006; Valeeva et al., 2007). This highlights the need to use socio-psychological models that incorporate the influences of intrinsic motivations on farmers’ decision-making processes, whilst still considering the extrinsic factors (Ellis-Iversen et al., 2010). This area of social epidemiology is widely used in human health policy making but is only recently emerging in animal health research (Ellis-Iversen et al., 2010). Intrinsic factors have been studied in animal health issues such as mastitis management, implementation of zoonotic control programs, the use of antimicrobials in feedlot cattle and the participation in foot-and-mouth disease detection and control (Delgado et al., 2012; Ellis-Iversen et al., 2010; Jansen and Lam, 2012; Mcintosh et al., 2009). However, what is still missing is the development of conceptual models based on theoretic frameworks from human behaviour sciences that identify all the important factors to predict farmer behaviour. The “Theory of Planned Behavior” (TPB) (Ajzen, 1991) is one of the most successful theoretic frameworks in research of human behaviour. Nevertheless, the TPB framework can be expanded and improved through the incorporation of additional variables (Armitage and Conner, 2001) from other socio-psychological and economical theories such as the “Health Belief Model” (Janz and Becker, 1984), the “Risk Information Seeking and Processing model” (Griffin et al., 1999) or the “Temporal self-regulation theory” (Hall and Fong, 2010). 4.2. Farm economics Research addressing the economic impact of helminth infections and other animal diseases has typically studied the effect on technical key performance indicators such as weight gain, milk yield or reproductive measures. Next, observed losses are converted into an economic value (Charlier et al., 2014). As an example in Belgian dairy herds, the annual cost per adult cow ranged between D 4 and113 and between D 0 and 77 for GI nematode and liver fluke infections, respectively (Charlier et al., 2012b). This approach has the advantage that it provides insights into animal performance and is easily explained to farmers. However, these current approaches do not reflect the effect on the whole-farm economic performance (Rushton, 2009). Moreover, they typically use average figures (e.g. average production impact or prices) and thus lack farm-specificity. A novel approach to address these problems has been proposed, based on efficiency analysis (van der Voort et al., 2013). Efficiency analysis aims to identify inefficiency levels by comparing the current performance level of farms with their potential optimal performance level (Farrell, 1957) by analysing the process of converting input(s) into output(s) (Coelli et al., 2005). Efficiency studies have been previously applied in animal health research (Barnes et al., 2011; Lawson et al., 2004). These studies focus on identifying a link between the technical efficiency of farms and indices of disease or certain control strategies. Besides integrality, a major advantage of efficiency analysis, is the possibility to link an animal disease or its diagnosis to input allocation, which is at the core of farmer’s decision making. The economic performance of a farm is not only influenced by technical efficiency, but also by input allocation (i.e. the combination in which inputs are used) (van der Voort et al., 2013). However, the way farmers allocate their inputs may also affect the level or occurrence of disease and the effectiveness of a control strategy. As a simple example, maximal use of grazed pasture is considered an economic way for feed supply of ruminants (White et al., 2002). However, farms relying heavily on pasture may suffer from higher levels of helminth infection impairing productivity and technical efficiency. The issue is thus to find the optimal allocation of pasture,
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Fig. 2. The epidemiologic socio-economic triad. Animal disease, farm economics and social satisfaction are interrelated factors that determine farm sustainability. All of these factors are influenced by human behaviour.
roughage and concentrates in which the economic performance is maximized, given the farm-specific constraints and input prices. This broadening of our perspective on animal health management could be depicted in the so-called epidemiologic socio-economic triad. Animal disease, farm economics and social satisfaction are interrelated factors that determine farm sustainability. All of these factors are influenced by human behaviour (Fig. 2). 5. Applying ECONOHEALTH on the case of parasitic helminth infections in dairy cattle 5.1. Background The EU is the largest producer of milk products in the world and dairy farming is traditionally one of the most profitable sectors in EU agriculture (OECD-FAO, 2013). Of the many infectious diseases that affect dairy cattle, infections with parasitic helminths are among those with the greatest impact on animal productivity (Charlier et al., 2014). All herds with a grass-based production system are infected with these helminths. The disease complex consists mainly of infections with gastrointestinal nematodes (GIN), liver fluke and lungworms. Whereas liver fluke and lungworm infections are commonly caused by a single species, Fasciola hepatica and Dictyocaulus viviparus, respectively; GIN infections comprise > 20 different species but the most prevalent and important species are Ostertagia ostertagi and Cooperia oncophora, which usually occur together. In young cattle, mortalities can be high when no preventive measures are taken. However, the main effect of parasitism is due to sub-clinical infections causing reduced growth, milk yield and reproductive performance. These costs have become increasingly important in the current economic climate with the low profit margins in the livestock sector. In addition, experiments in small ruminants have shown that inadequate preventive measures against GIN, result in an extra 10% emission of CO2 per kg of weight gain and that disease control can contribute to a reduction in greenhouse gas emissions from animal agriculture and help reduce the carbon footprint of livestock farming (Kenyon et al., 2013). We believe that this case, consisting of 3 different infections (GIN, liver fluke and lungworms) can be fertile soil to elaborate the ECONOHEALTH concept, leading to new and integrated prevention strategies. We propose to do this by:
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(1) Revealing the environmental, climatic and management drivers of co-infections with GIN, liver fluke and lungworm; (2) Understanding farmers’ risk attitudes and behaviour in helminth control; (3) Assessing the role of the GIN, liver fluke and lungworm in the whole-farm economic context; (4) Integration of the different drivers of animal health: climate, environment, management, farm economics and human behaviour; (5) Development of decision support tools and communicative advices. 5.2. Environmental, climatic and management drivers of co-infections with GIN, liver fluke and lungworm Risk factors for individual diseases are increasingly described. In contrast, how different risk factors act simultaneously on different diseases remains largely unknown. Helminth infections typically show some level of spatial and spatio-temporal variability. The recent GLOWORM project (www.gloworm.eu) funded under the European Commission’s 7th framework programme, delivered guidelines for standardized and harmonized cross-sectional surveys of helminth parasites in ruminants allowing the development of updated prevalence maps and multiscale spatial models for the European area (Ducheyne et al., 2015; Rinaldi et al., 2015a,b). However, the available spatial and spatio-temporal models have considered each species separately and similarities/dissimilarities in risk distributions remain to be characterized (Bennema et al., 2009). Common spatial patterns of infections can be detected and used as potential markers of common drivers of infection. Multivariate disease mapping can cope with this problem as was recently shown for the case of helminth infections in sheep (Biggeri et al., 2007; Musella et al., 2011). These authors developed multivariate spatial Bayesian hierarchical models to describe common patterns of disease. Second, the underlying factors need to be identified to explain the observed patterns using environmental, climatic and herd management variables, derived from geographical information systems, satellite sensors and questionnaires (Rinaldi et al., 2006). Thus, by developing a multivariate approach that takes into account spatial dependency of helminth infections, common disease patterns of cattle can be discovered and the underlying risk factors of a disease “complex” or co-infections instead of a single disease can be assessed.
The novel framework was tested in the population of Flemish dairy farmers. The results showed that ‘attitude towards diagnostic methods’ and ‘subjective norm’; i.e. the influence of significant others, had the strongest, positive influence on adoption intention of diagnostic methods. ‘Attitude towards the use of anthelmintic drugs’ had a negative effect on adoption intention of the diagnostic methods. This implicates that farmers will be more intended to adopt diagnostics if they have a positive attitude for diagnostics and if they feel some sort of social pressure to adopt these methods. ‘Attitude towards the preventive use of anthelmintic drugs’ had a negative effect on adoption intention of the diagnostic methods. Concretely, the more positive someone perceives the preventive use of anthelminthic drugs, the less motivated they will be to adopt diagnostics. This implicates an effect of their current behaviour (i.e. preventive use of anthelmintics) on future adoption intentions. This raises the question whether farmers’ attitude towards anthelminthics should first be lowered before they can be convinced to adopt diagnostic methods.
5.4. Assessing the role of GIN, liver fluke and lungworm in the whole farm economic context In a study using efficiency analysis, a negative relationship between antibody levels to GIN in bulk tank milk and technical efficiency was observed (van der Voort et al., 2014). GIN infections appeared to mainly constrain the efficient transformation of pasture, health related costs and labour into milk. In addition, the GIN-associated inefficiency was mitigated when higher levels of concentrates and roughage were supplied. Recently, this approach was further elaborated to clarify the relationship between GIN exposure, input allocation, technical efficiency and economic performance of farms (M. van der Voort, unpublished observations). It was concluded that determining the position of farms in an inputoutput efficiency framework could improve the advice regarding GIN control. It provides a way to simultaneously optimize the level of exposure to GIN and the economic performance of a specific farm. The future challenge is to expand this approach by including other pathogens. This challenge is not trivial. Including co-infections will have to deal with correlated infections and inefficiency scores will have to be split in shared and specific effects for each helminth requiring advanced statistical methods.
5.3. Understanding farmers’ risk attitudes and behaviour in helminth control
5.5. Integration of traditional knowledge with novel insights from socio-economic studies
The available literature on livestock farmers’ behaviour in animal health is related to very specific issues. Social research on the control of helminth infections is absent, and a generic understanding is missing. Qualitative research is thus still necessary to fill in the gaps of the literature, and to construct working hypotheses for quantitative studies. This can be addressed by in-depth interviews including the different stakeholders in helminth control: farmers, veterinarians and external experts (covering farmer and animal health organisations, academics and industry). Based on the results of the qualitative research and the scientific literature, theoretical frameworks can be drawn. These should then be validated by the use of large-scale surveys. As an example, we developed a theoretical framework to predict the farmers’ intention to adopt diagnostic methods before implementing anthelmintic drugs in cattle by combining 2 fundamental, cognitive theories in the field of behavioural psychology (“Theory of Planned Behavior”; Ajzen, 1991) and health psychology (“Health Belief Model”; Janz and Becker, 1984) (F. Vande Velde, unpublished observations).
How can the traditional knowledge regarding the epidemiology of helminth infections be combined with the novel insights generated through sociological and economic studies in a single framework where the relative importance of different drivers can be unravelled? Many of the identified drivers will be interrelated and it will be difficult to differentiate direct effects from mediated effects. One approach could be to use structural equation models (SEMs) to deal with such an interrelation of risk factors. SEMs are multivariate or multi-equation regression models in which the response variable in one regression equation may appear as a predictor in another equation (Bollen, 1989). As a result, variables in a SEM may influence each other, either directly or indirectly, i.e., through intermediate variables. SEMs are typically specified in the form of so-called path diagrams. Using path diagrams, we can depict the causal hypotheses of direct and mediating effects of environment, farmer attitude and input use to explain observed herd characteristics that describe level of infection and economic performance (Detilleux et al., 2012).
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5.6. Decision support tools Due to the increased understanding and complexity of disease processes, the success of ECONOHEALTH will depend on the development of successful decision support tools and communicative advices. For instance, during the recent EU FP7 GLOWORM project (www.gloworm.eu), the development of several decision support tools was initiated. These included tools to predict the transmission risk of parasites on pasture (Rose et al., 2015; Verschave et al., 2014), the economic impact at herd level of helminth infections or anthelmintic treatment strategies (Charlier et al., 2012a,b) or anthelmintic efficacy based on faecal egg count reduction (Torgerson et al., 2014). However, there are some critical factors that need to be further looked at in the development of successful decision support tools: perceived usefulness, accessibility, flexibility, credibility, maintenance and adaptability (McCown, 2002). Recently, we organised 2 focus group meetings with veterinarians and farmers in Flanders (Belgium) to identify the user needs for software applications on helminth control in cattle. The meetings revealed that the currently available tools only partially address the user needs. Moreover, there are great differences in the needs for veterinarians versus farmers. Further and closer collaboration between the model-makers and model-users is required and business cases need to be developed so that the tools can be self-sustainable. 5.7. Communicative advices When novel prevention strategies contrast with long established traditions or perceptions, it is known to be difficult to convince farmers of their implementation, even when there is a base of evidence of their comparative advantage (Cabaret et al., 2009). Here, as parasitologists we should collaborate with communication scientists and social marketers in order to convey the novel insights. The insights from sociological studies into farmer’s behaviour regarding helminth control can be applied in communication strategies. As an example, in a recent study, we showed that risk perception of anthelmintic resistance had no effect on the adoption intention of diagnostic methods (F. Vande Velde, unpublished observations). This suggests that in communications promoting sustainable anthelmintic control practices (i.e. with a low selection pressure for anthelmintic resistance), using the threat of anthelmintic resistance is not going to change farmer’s behaviour immediately. Better incentives are likely positive messages to increase the attitude towards diagnostic methods in helminth control and/or lower the attitude towards anthelmintic drugs. The efficacy of these and other incentives should still be experimentally confirmed. 6. Concluding remarks Major advances in animal health management are required in order to address the societal needs to sustainably intensify livestock production from a shrinking natural resource base and ensure food security. Policy makers, chain partners and sector organisations try to influence farmer’s behaviour in order to meet these societal needs. There is considerable focus on production diseases, including helminth infections because efficient management of these diseases is a way to further improve the productivity and welfare of our livestock (Arnold, 2013). In the past, animal health research has provided effective prevention strategies for the major endemic diseases of livestock but these strategies typically provide solutions for single infectious diseases and they are often not implemented because they insufficiently consider the economic and social context of the farm unit. By including the economic and
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social context in our understanding of the factors that drive animal health, and in particular helminth infections of farmed ruminants, more comprehensive prevention strategies can be developed. We believe that this will result in the development of novel concepts and tools for animal health management and will enhance individual entrepreneurship, social satisfaction and thus the resilience of the livestock sector. Acknowledgements JC would like to express his gratitude to Sien Verschave, Brecht Devleesschauwer and Bruno Levecke (Laboratory of Parasitology, Ghent University), Erwin Wauters (Institute of Agriculture and Fisheries Research, ILVO), Guido Van Huylenbroeck (Department of Agricultural Economics, Ghent University), Liselot Hudders (Department of Communication Studies, Ghent University), Henk Hogeveen (Farm Animal Health Department, Utrecht University), Annibale Biggeri (University of Florence) and Guy Hendrickx (AviaGIS) for their support, discussions and motivations which allowed him to develop the ideas presented in the current manuscript. JC would also like to acknowledge the EU FP7 GLOWORM project (Grant agreement no 288,975CP-TP-KBBE.2011.1.3-04), which allowed him to conduct research in the last 3 years. References Ajzen, I., 1991. The theory of planned behavior. Organiz. Behav. Hum. Decis. Process. 50, 179–211. Armitage, C.J., Conner, M., 2001. Efficacy of the theory of planned behaviour: a meta-analytic review. Br. J. Soc. Psychol. 40, 471–499. Arnold, C., 2013. Infectious diseases associated with livestock production: mitigating future risks. Environ. Health Perspect. 121, a256. Barnes, A.P., Rutherford, K.M.D., Langford, F.M., Haskell, M.J., 2011. The effect of lameness prevalence on technical efficiency at the dairy farm level: an adjusted data envelopment analysis approach. J. Dairy Sci. 94, 5449–5457. Bennema, S., Vercruysse, J., Claerebout, E., Schnieder, T., Strube, C., Ducheyne, E., Hendrickx, G., Charlier, J., 2009. The use of bulk-tank milk ELISAs to assess the spatial distribution of Fasciola hepatica, Ostertagia ostertagi and Dictyocaulus viviparus in dairy cattle in Flanders (Belgium). Vet. Parasitol. 165, 51–57. Bennema, S.C., Ducheyne, E., Vercruysse, J., Claerebout, E., Hendrickx, G., Charlier, J., 2011. Relative importance of management, meteorological and environmental factors in the spatial distribution of Fasciola hepatica in dairy cattle in a temperate climate zone. Int. J. Parasitol. 41, 225–233. Biggeri, A., Catelan, D., Dreassi, E., Rinaldi, L., Musella, V., Veneziano, V., Cringoli, G., 2007. Multivariate spatially-structured variability of ovine helminth infections. Geospat. Health 2, 97–104. Bollen, K.A., 1989. Structural Equations with Latent Variables. Wiley, New York. Burton, R.J.F., 2004. Reconceptualising the ‘behavioural approach’ in agricultural studies: a socio-psychological perspective. J. Rural Stud. 20, 359–371. Cabaret, J., Benoit, M., Laignel, G., Nicourt, C., 2009. Current management of farms and internal parasites by conventional and organic meat sheep French farmers and acceptance of targeted selective treatments. Vet. Parasitol. 164, 21–29. Charlier, J., Levecke, B., Devleesschauwer, B., Vercruysse, J., Hogeveen, H., 2012a. The economic effects of whole-herd versus selective anthelmintic treatment strategies in dairy cows. J. Dairy Sci. 95, 2977–2987. Charlier, J., van der Voort, M., Hogeveen, H., Vercruysse, J., 2012b. ParaCalc® - a novel tool to evaluate the economic importance of worm infections on the dairy farm. Vet. Parasitol. 184, 204–211. Charlier, J., van der Voort, M., Kenyon, F., Skuce, P., Vercruysse, J., 2014. Chasing helminths and their economic impact on farmed ruminants. Trends Parasitol. 30, 361–367. Claridge, J., Diggle, P., McCann, C.M., Mulcahy, G., Flynn, R., McNair, J., Strain, S., Welsh, M., Baylis, M., Williams, D.J.L., 2012. Fasciola hepatica is associated with the failure to detect bovine tuberculosis in dairy cattle. Nat. Commun. 3. Coelli, T.J., Rao, D.S.P., O’ Donnell, C.J., Battese, G.E., 2005. An Introduction to Efficiency and Productivity Analysis, 2nd ed. Springer Science and Business Media. Delgado, A.H., Norby, B., Dean, W.R., McIntosh, W.A., Scott, H.M., 2012. Utilizing qualitative methods in survey design: examining Texas cattle producers’ intent to participate in foot-and-mouth disease detection and control. Prev. Vet. Med. 103, 120–135. Derks, M., van Werven, T., Kremer, W.D.J., Hogeveen, H., 2011. Veterinary on-farm counselling on dairy farms: the veterinarians’ vision. Udder Health Commun., 179–185. Derks, M., van de Ven, L.M.A., van Werven, T., Kremer, W.D.J., Hogeveen, H., 2012. The perception of veterinary herd health management by Dutch dairy farmers and its current status in the Netherlands: a survey. Prev. Vet. Med. 104, 207–215.
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Please cite this article in press as: Charlier, J., et al., ECONOHEALTH: Placing helminth infections of livestock in an economic and social context. Vet. Parasitol. (2015), http://dx.doi.org/10.1016/j.vetpar.2015.06.018