It is anticipated that improved control of tick-borne diseases and
trypanosomiasis will be made possible through the development of
recombinant antigen vaccines, enhanced genetic resistance and other
technologies, the application of which will need to be responsive to the
varying demands for disease control in different regions and production
systems of Africa. The demand for control of tick-borne diseases and
trypanosomiasis
varies considerably in the continent depending on their distribution, the level of losses caused by them and on the economic outputs of the livestock production systems in which they occur. Given these variations, and the impracticality of gathering data representative of all possible conditions, the use of models offers a strategic method of quantifying the productivity effects of disease, permitting socioeconomic impact evaluations of disease control measures to be performed.
The level of losses caused by tick-borne diseases is affected by numerous factors, particularly host susceptibility, the dose of infection (dependent partly on tick infestation levels) and the age at which infection occurs.
Thus in cattle production systems with indigenous East Africa zebu in the Lake Victoria Basin, where at least two generations of the vector Rhipicephalus appendiculatus occur each year, where all instars may occur on livestock at the same time, where the majority of animals are carriers of Theileria parva at low levels of parasitaemia, and where virtually all animals are infected as calves and become immune before reaching three months of age, little or no clinical East Coast fever (ECF) occurs as a result of T. parva infection.
In contrast, in areas where R. appendiculatus infestations are strictly seasonal and only one generation occurs each year, where clinical cases (with higher piroplasm parasitaemias) occur, and where all animals are not infected as calves, even indigenous cattle may experience outbreaks of clinical theileriosis. In both areas, the introduction of Taurine cattle and their crosses increases the incidence of clinical disease.
The situation in which little or no losses occur due to clinical disease, termed endemic stability, only exists for T. parva infections in a few areas of eastern Africa, but for babesiosis and anaplasmosis it is much more widespread in the continent.
The situation for heartwater is not well documented, but widespread endemic stability is suspected in many areas. The artificial induction of endemic stability through the use of vaccines will provide the most effective and sustainable option for tick-borne disease control in the future. The determination and quantification of the variables contributing to endemic stability and instability are therefore crucial in identifying target populations for tick-borne disease control programs, and assessing their impact.
The most important quantitative indicators of the presence of endemic stability and instability to tick-borne diseases are incidence of infection, incidence of disease, case-morbidity and case-fatality rates in young cattle. Stability is characterized by a high incidence of infection in this age group, but low levels of disease.
Instability is generally characterized by a low and variable incidence of infection, and high incidence of disease. Regrettably, disease incidence, case-morbidity and case-fatality rates are rarely measured accurately under field conditions, and estimates of disease occurrence generally rely on antibody prevalence rates as a surrogate for incidence of infection (and for prevalence of immunity).
Thus, it is important to determine whether it is possible to quantify the relationship between antibody prevalence and these indicators under different conditions and with different tick-borne disease combinations, and to determine the relationship between these indicators and productivity effects (in terms of milk, meat, traction and manure).
An important component of this process is to determine the relationship between antibody prevalence, as measured by current and developing serological tests, and population immunity in the sampled cohort to the spectrum of tick-borne disease antigens they are likely to encounter.
A first step in modelling this dynamic process has been made for T. parva by Medley, Perry and Young (described earlier in the workshop), who simulated endemic stability and tested the effect of tick abundance and carrier state prevalence on its maintenance. However, in order to assess the validity of such models on a broader scale, they require testing in other endemically stable and unstable states.
Regrettably, due to the intensive nature and high cost of prospective studies needed to validate such models, few data sets exist.
Eventually, it is hoped that such studies will lead to the development of user-friendly models that assess the efficacy of tick-borne disease control options for given herds, districts or regions, determine their effects on livestock productivity and assess their economic impact.
With tsetse-transmitted trypanosomiasis, similar models are required, but due to differences in the immune mechanisms involved, it may not be possible to base them on the concepts of stability and instability. Furthermore, it is anticipated that the mechanisms involved are more complex and less predictable.
These effects, which may be better understood and projected through modelling, can include changes in livestock and human population densities, changes in patterns of land use accompanied by environmental changes, increased conflict over resources, disruptions of local social patterns, and increases in income and wealth disparities within the population. Moreover, other constraints within the overall livestock management system may serve to suppress potential benefits resulting from improved livestock disease control.
These can include the existence of other diseases, poor animal nutrition, labour scarcity and lack of access to supporting services such as animal health delivery system, artificial insemination or credit for improvement of livestock.
Modelling can help in identifying such constraints, or in evaluating their effects on potential impacts of alternative control strategies. Ex-ante assessment and prediction of the impacts of disease control through modelling can also help in avoiding possible deleterious effects in the application of new control technologies.
It also provides useful information to farmers, governments and donors in order to assist them in planning better (strategic and systematic) disease control programs. In addition, such information can help in prioritizing the allocation of resources to disease research.
There are not always sufficient data, in content or quality, for assessing and predicting socioeconomic and environmental impacts of disease control. In many instances, the gathering of such data by field studies is unrealistic and costly, particularly given the large and varying geographic areas involved. A more cost-effective approach is to develop models using available field and secondary data that are supplemented by expert opinion, and then use such models for desk-top experimentation and extrapolation in ex-ante analyses.
An additional advantage of models is that once developed and verified they provide a standardized method of data analysis which can be extended to users in different areas and countries, particularly if the models are developed and packaged in user-friendly computer software.
ILRAD has developed and applied spreadsheet models for assessing annual economic losses due to East Coast fever and the financial and economic impacts of its control by immunization at farm and above farm level. These models are being adapted and improved, in collaboration with the AP Consultants of the UK, for the analysis of trypanosomiasis control.
In collaboration with Texas A & M University, a whole farm simulation model has been developed and applied for assessing and projecting farm level financial and nutritional impacts of ECF immunization under small-holder dairy production systems; a similar simulation analysis approach can be extended to trypanosomiasis control in sedentary livestock production systems. ILRAD's current modelling efforts, however, tend to emphasize microfinancial/economic aspects of livestock disease control effects.
Macro-economic sectoral, trade and policy issues are not fully incorporated. In addition, linkages of financial/economic relationships to physical (ecological), biological (epidemiological) and socio-cultural (welfare) factors of livestock production systems are weak.
Future modelling needs will require integration of micro- and macro-economic factors involved in livestock disease control with ecological, epidemiological and socio-cultural factors for more comprehensive assessments of the impacts of alternative control strategies.
Such integrated model(s) will, however, be complex, and technical, data procurement problems and modelling mechanisms required are issues that must be addressed.
The model(s) developed would ideally be suitable for application to different livestock production systems in different environments.
Traditionally these have been classified into host, agent and environment factors, but I would argue that this is in some respects too static a view of the initiation of disease, and that we should look for a more dynamic way of viewing the interactions.
Computer modelling is one way of representing epidemiological interaction realistically and dynamically. While some risk factors are common to many different infectious diseases, others are very specific to a single disease, and it is unwise to extrapolate from knowledge of relevant risk factors for one disease to conclude that the same factors are necessarily important in other superficially similar diseases.
Many diseases exert their effect on productivity most strongly in the early subclinical stages of infection, when there may not necessarily be any evidence of disease, while in others the effects grow as the clinical severity rises.
Overall, the scale of effects of disease on productive capacity of animals is surprisingly large, much greater than would occur by depriving the animal of an apparently similar quantity of nutrients. While it is not completely clear why particular diseases have the effect they do on animal productivity, a reasonable overview of why disease so adversely affects productivity has emerged in recent years, and this is presented in this paper.
The main effect of disease appears to be on protein metabolism. In addition, some diseases reduce efficiency of utilization of various micronutrients, such as Cu or P.
The primary metabolic effects of disease then produce a cascade of secondary effects which can be measured in economic terms. In developing a model of a disease process as a basis for decision-making, consideration must be given to accurately representing these various effects for the particular disease.
While some risk factors are common to many different infectious diseases, others are very specific to a single disease, and it is unwise to extrapolate from knowledge of relevant risk factors for one disease to conclude that the same factors are necessarily important in other superficially similar diseases. Risk factors can be identified and the scale of their impact (measured variously as relative risk and attributable risk) assessed through appropriate epidemiological study designs using observational data.
Such studies do not always discriminate between infection and disease, including animals as 'cases of disease' only if they show recognizable clinical signs. However for the types of diseases we are currently seeking to control, it is increasingly necessary to look separately at the process of initial infection, at the process of conversion from infection to disease, and at the ways in which animal productivity is affected at each stage. Similarly for non-infectious diseases, there will tend to be a process of lesion production and a subsequent process of development of clinical disease.
Figure 1 shows one such example of a system diagram developed in order to represent the causal processes and the way in which they are believed to interact to produce a particular disease. The example chosen is one form of lameness in dairy cattle, known as white line disease. This can cause lameness directly but can also lead on to sole abscess which causes even more severe lameness. The figure is based upon research at both herd and individual animal level, and draws together factors which can operate at each of these levels to influence whether or not an individual animal develops a subclinical lesion or becomes clinically lame, and whether the herd has a high or low incidence of clinical lameness. This particular disease is non-infectious, but such representations are even easier to formulate for infectious diseases where the interactions tend to follow more standard patterns.
Such a system diagram is helpful in presenting an understanding of how factors influence disease processes, but it is still static, in that it does not provide any way of analysing and understanding the dynamics of the disease process over time or its spatial spread for diseases which show spatial patterns of occurrence. Computer modelling takes the process a major step further forward and is the most effective way of representing epidemiological interactions realistically and dynamically. Typically nowadays a computer model is designed by first formulating a system diagram, plus sub-diagrams exploring in more detail each specific facet of the disease processes and then programing a computer to mimic the processes and progress the total system forward through time.
In other papers presented at this workshop, techniques of modelling are considered for different types of disease. However if modelling of parasitic diseases is to include representing their economic effects, then it is necessary to formulate an adequate representation of this part of the disease process to complement the epidemiological part of the total model. This paper therefore concentrates on how disease agents affect productivity of animals and how this should be included in a computer model.
The purpose of Figure 2 is to summarize all the possible direct and indirect mechanisms through which a disease can influence the productive efficiency of livestock. Not all diseases will have all of the effects, but in representing economic effects in a model it is necessary to consider all possibilities and select for inclusion those which appear to be relevant. Each of the mechanisms will be discussed individually and then consideration will be given to how they should be combined to evaluate the effect of disease on profitability.
It is intriguing that feed intake should be commonly depressed by disease when other evidence shows clearly that feed requirements are increased by many of the same diseases, since productivity falls under the influence of the disease. From the limited studies which have been conducted to resolve this apparent paradox, it would appear that it results from disturbances in body homeostatic mechanisms of the host. Symons and Hennessy (1981) have found that choleocytokinin levels rise as appetite falls in Trichostrongylus colubriformis infestations, and return to normal in line with appetite when the infestation is terminated. In the same disease, corticosteroid levels rise and thyroxine levels fall in response to the parasite, while insulin levels fall apparently in response to reduced intake rasher then directly due to the parasite (Prichard et al., 1974; Hennessy and Prichard, 1981). The disease agent may also in some cases produce a toxic substance which depresses intake directly (Seebeck et al., 1971). It is important to differentiate between diseases which merely depress feed intake and those which lower the efficiency of feed conversion - with or without any effect on feed intake. Seebeck et al. (1971) called the effect on intake the anorectic effect and that on feed conversion efficiency the specific effect. The specific effect is the more serious of the two, since lower production is achieved from the same feed intake and efficiency of the production process is adversely affected, whereas the anorectic effect reduces both intake and output without altering the efficiency of production. This differentiation is an important consideration in studies of animals which consume purchased feed, such as pigs. It is less important in grazing ruminants, for which feed production is closer to being a fixed cost.
It nevertheless seems likely that, at least in ruminants, adverse effects of disease on productivity which cannot be explained by reduction in feed intake can reasonably be attributed to lower feed conversion efficiency; although as Symons (1969) points out, digestibility trials are a crude method of assessing changes in digestive function. It is also clear that the nature and extent of pathological changes in the body cannot be used as any direct guide to the severity of effects of a disease on productivity.
Steel (1974) and Symons and Steel (1978) have reviewed the metabolic consequences of gastrointestinal parasitism, with particular reference to sheep. They conclude that helminth disease causes a series of metabolic changes to occur in the animal, the primary impact of which is on protein metabolism. The effects, however, carry through to the metabolism of other nutrients. The result is to produce a syndrome analogous to undernutrition.
In gastrointestinal nematode infestations, plasma is lost into the digestive tract at the attachment sites of the parasites, and haemoglobin is also removed by blood-sucking parasites. Much of this protein is digested and reabsorbed lower in the tract, but the host uses energy and protein to replenish the mucosa and plasma proteins which have been depleted. This places demands on the liver and increases its nutrient utilization. There is increased excretion of nitrogen as urea in urine, demonstrating that recycling of the nutrients is not completely efficient in maintaining nitrogen balance, even though considerable energy costs are incurred by the host for increased protein synthesis.
Animals tend under these circumstances to run down their pool of plasma proteins because production in the liver cannot keep pace with the loss, even though the synthesis rate is unusually high. Adjustments are made to other nitrogen-using processes of lower priority, notably synthesis of wool protein and muscle protein. In sheep, sulphur-containing proteins are put in especially short supply by Trichostrongylus colubriformis infestation, demand cannot be met, and wool production shows an exceptionally large fall.
If feed intake is reduced either due to the parasite or to a low plane of nutrition, protein intake may fall below the level required to maintain an adequate serum protein pool. Bown et al. (1986) have shown that direct post-ruminal infusion of casein in sheep receiving daily doses of larvae of Trichostrongylus colubriformis increased nitrogen retention five-fold, and supported the argument as outlined above that the primary defect is one of protein loss and an anabolic cost of tissue regeneration. Infusion of glucose in amounts isocaloric with the casein only doubled nitrogen retention, showing that energy supplementation was not as beneficial as protein replacement.
A contrasting example to Trichostrongylus colubriformis is the cattle tick Boophilus microplus, which sucks blood much like some internal parasites, but differs in that the animal cannot recover any of the nutrient content of the blood in this case. The effects of ticks on host metabolism have been studied by Seebeck et al. (1971), O'Kelly et al. (1971) and Springell et al. (1971). Haemoglobin and plasma albumin fell, whereas globulin rose. Thus the animal was able to synthesize increased supplies of globulins, but could not maintain levels of the other two blood constituents. This was attributed in part to a disturbance of protein metabolism, but the injection of a toxin by the tick was also hypothesized. To further emphasize the tenuous link between the pathology of a disease and its effects on productive processes, O'Kelly and Kennedy (1981) found that ticks adversely affected function in the gastrointestinal tract and reduced organic matter digestibility. It is difficult to explain why this should be so when such effects are not common for parasites directly affecting the tract.
Although these are the two most fully studied diseases, evidence for other diseases in a variety of species confirms the central importance of the derangement of protein metabolism in the disease process. There is also impairment of energy metabolism, but this appears to be largely secondary to the alterations in protein metabolism, and is a result primarily of the energy costs of tissue regeneration.
Mineral and micronutrient metabolic flows are also altered by parasitic diseases, which are the only ones to have been studied. There is reduced retention of ingested calcium and phosphorus in growing sheep infested with Trichostrongylus colubriformis or Ostertagia circumcincta (Symons and Steel, 1978). Consequently, bone growth and skeletal development are impaired, and this can reduce mature body size and capacity to accumulate muscle (Sykes et al., 1977). Cobalt, copper and vitamin status of animals have all been reported to be affected by parasitism (Downey, 1965, 1966a, 1966b) as well.
Since lung disease can adversely affect productivity, another mechanism by which disease might impair physiological function is a reduction in respiratory function. It seems more likely, however, that it is the regenerative process following lung disease which cause the production deficit.
Premature Death
This effect is the easiest of all the consequences of disease to measure, and therefore tends to be considerable over-emphasized in comparison with other effects. In economic studies, death losses should be measured as the difference between the potential market value of the animal and its value when dead (which may not be zero), less the costs which would have been incurred in obtaining the market value (such as extra feed and care to market age, marketing costs, etc.).
Changed Value of Animals and Products From Slaughtered Animals
Diseased animals may have lower market value either due to visible lesions or due to indirect changes in appearance or body conformation which make them less attractive to buyers. True market value of final products may be altered due to changes in the ratio of meat to fat or to bone (Springell et al., 1971; Sykes et al., 1980), or reduced protein content. The value of offals may also be reduced due to pathological changes caused by agents such as Fasciola hepatica or Echinococcus granulosus. Presence of lesions of a zoonotic disease may render the animal totally unfit for consumption.
Some diseases (such as caseous lymphadenitis in sheep) may render products less attractive to the consumer for aesthetic reasons, and hence may reduce meat consumption. Diseases which affect the skin, such as warble fly infestation or even sheep lice (Britt et al., 1986), may reduce the market value of hides or their value to the user.
Reduced Liveweight Gain
There have been well in excess of 50 published studies on the effect of diseases on weight gain in animals and in general they find that diseased animals gain weight more slowly than equivalent disease-free animals. Notable as an exception is lice infestation in cattle. It has been among the most intensively studied but the evidence shows that differences in weight gain between infested and free animals are modest or negligible, and certainly not enough to yield an economic benefit from treatment. Therefore caution is required in assuming an effect on weight gain of a disease without experimental data to support it.
Reduced Yield and Quality of Products From Live Animals
Yield of products such as milk, wool and eggs may also be reduced by disease, and there have been numerous papers showing the effect of various diseases on wool growth or milk-yield. Quality of the products may also be reduced, as in the case of the changes in milk composition which result from bovine mastitis, and these may or may not be detectable by the consumer. In the first case price will fall and the livestock producer will suffer; in the second case, the consumer will suffer the loss. For example, parasitic disease can reduce the market value of wool per kg, as well as the quantity produced (Morris et al., 1977); but the structural characteristics of the wool may also be altered in ways which reduce its value to the manufacturer but cannot be detected in the normal marketing process (Johnstone et al., 1976). It has also been shown that parasitic disease can affect the taste of meat (Garriz et al., 1987).
Reduced Capacity for Work
Worldwide, the single most important use of animals is as a source of traction. The second largest (after dung) productive energy output of animals in developing countries is for work, and products considered as of central importance in developed countries are seen as bi-products under those conditions (Odend'hal, 1972). There have been no published reports directly measuring the effects of diseases on capacity for work, but field evidence is that diseases can severely curtail rice paddy preparation and other tasks for which animals are essential, so this effect can be very important and should be considered in developing countries.
Altered Production of Dung for Fuel and Fertilizer
In Asia and Africa cattle dung is a vital source of cooking fuel and in much of the developing world it is an important fertilizer. Diseases which cause high death rates in cattle will also indirectly influence human nutrition by reducing dung supplies.
Altered Feed Conversion Efficiency
As discussed earlier, it appears that disease primarily affects animal productivity by altering the metabolic processes for protein and other nutrients, thereby reducing the feed conversion efficiency of affected animals and producing a number of ramifications which reduce herd productivity. Feed intake may also be reduced, but this is not usually the primary effect.
Feed conversion efficiency is the ultimate measure of the influence of disease on the production process, but its measurement requires accurate measurement of feed intake, and that is only possible under controlled feeding conditions. In grazing systems it is usually reasonable to take changes in productivity as an adequate indication of changes in feed conversion efficiency when comparing diseased and disease-free animals kept under identical conditions.
Intuitively, it seems likely that the rate of decline in productivity would increase as the disease becomes more severe and body functions become more deranged. However, the limited evidence available favours the alternative view that the most dramatic changes occur at low or subclinical levels of disease, and that each additional parasite, for example, has less effect than the one before it (Hawkins and Morris, 1978). This emphasizes the importance of the health management approach in which the focus is on optimizing productive efficiency rather than the clinical approach in which a disease must be detectable to be considered important.
Reduced Productive Life of Animals
Apart from animals which die, all remaining herd members are culled when the manager considers them less potentially productive than the animal which would replace them. This issue has been investigated in detail by Renkema and his co-workers (Renkema and Stelwagen, 1979; Korver and Renkema, 1979; Dijkhuizen et al., 1985a, 1985b). They showed that in general a substantial economic benefit could be achieved by taking action to extend the herd life of the average dairy cow, principally by reducing the amount of involuntary culling due to health-related causes. This is not limited to disposal specifically because of disease, but also includes culling for low yield or other causes, where the underlying cause is lowered productivity due to disease, but the manager is unaware of this fact.
Less Accurate Genetic Selection
If a disease alters any of the components of productivity which are the subject of genetic selection pressure in the herd (such as milk or wool yield), it will affect the efficiency with which animals of superior genetic merit are identified, especially if the probability of an animal being affected by the disease is unrelated to yield level. Provided susceptibility to the disease and yield level are not correlated, the presence of the disease will confound the genetic selection effort. For example, Johnstone et al. (1976) showed that internal parasitism can affect wool production by sheep in ways which distort selection by objective measurement of wool characteristics. Since resistance to internal parasitism cannot be regarded as a heritable trait for practical purposes, genetic selection will be more efficient if effective parasite control is being carried out in the herd.
Less obviously, diseases which adversely affect body metabolism (but do not directly affect the reproductive tract) can also affect the number of progeny born. The mechanisms have not been fully explored, but may well operate through an effect on liveweight and condition, or through indirect means such as the induction of pyrexia at critical stages in the reproductive process. For example, both gastrointestinal parasites (Murray et al., 1971) and liver fluke (Hope Cawdery, 1976) have been shown to affect reproductive performance in ewes. In cattle, bovine leucosis (Schmied et al., 1979; Parchinski, 1979) and ephemeral fever (Theodoris et al., 1973) have been reported to affect reproduction. If reproductive performance is too poor, it may even become impossible to maintain herd size through home-bred replacements, necessitating the purchase of breeding animals with all the additional risks which that entails.
This has not been studied for very many diseases, but some examples exist. For instance, bovine mastitis appears to be a disease for which complete regeneration occurs in most animals over the dry period following elimination of an infection (Morris, 1973), although yield remains depressed for the rest of the lactation in which a cure is achieved. Conversely, when infestations with Fasciola hepatica are eliminated in growing animals, sheep do not regain their former productivity or feed conversion efficiency, even when the infestation had existed for as little as eight weeks (Hawkins and Morris, 1978). In a study of a nematode parasite, wool growth and liveweight gain responded quite differently to anthelmintic treatment (Coop et al., 1984).
Therefore each disease type must at least in the first instance be considered separately, since the nature and extent of recovery following elimination of a disease is not predictable from general principles. The selection of an economically optimal control strategy will be strongly influenced by this consideration.
The major direct effect of animal disease on human well-being is through reducing the supply of high quality protein, such as diseases which reduce the supply of milk for young children. Animal products are also important sources of other nutrients, notably minerals and vitamins, and diseases can both reduce the total supply of animal products and modify the composition of animal products in ways which reduce their nutritional value (Huss-Ashmore and Curry, 1992).
Effects on Community Development
As well as the effects on human nutrition, animal diseases can affect other aspects of community welfare, especially in developing countries. As discussed earlier, the two most important services provided by animals in such circumstances are traction and dung production, and disease may reduce the supply of both of these. Animals are also important sources of products (wool, hair, hides, feathers, fur, etc.) used for clothing, decoration and for manufacture of utensils and other products. A further effect of those animal diseases which are zoonotic is to cause disease in the human as well as the animal population, thus amplifying their impact.
Cultural Significance of Animals
In most communities animals serve functions far beyond the utilitarian roles which are the focus of this paper. While these are not strictly economic in nature, they are vital functions which should be included in any consideration of the significance of animal disease.
Provided that the relevant items from Figure 2 are included into the total simulation model by linking them to the appropriate ecological and epidemiological indices within the overall system model, then estimation of the benefits of disease control strategies within the simulation model becomes straightforward, and depends only on the availability of suitable field data on the effects of the disease on various yield measures. If such data are unavailable when the model is formulated, guesstimates can be used initially and sensitivity analysis applied to determine which of the productivity indicators most urgently need field refinement.
Estimation of costs at farm level can usually be done quite simply from information on the unit costs of control measures, since a partial budgeting approach to such economic analyses is almost always adopted at this level.
In regional evaluations it may be necessary to build a complete model of a regional disease control program. However in many cases it is sufficient to run the model for various types of farms and sets of conditions and then to combine these through an electronic spreadsheet in which the regional total effects are calculated, taking into account costs above the farm level and possible supply/demand consequences of disease control programs.
varies considerably in the continent depending on their distribution, the level of losses caused by them and on the economic outputs of the livestock production systems in which they occur. Given these variations, and the impracticality of gathering data representative of all possible conditions, the use of models offers a strategic method of quantifying the productivity effects of disease, permitting socioeconomic impact evaluations of disease control measures to be performed.
The level of losses caused by tick-borne diseases is affected by numerous factors, particularly host susceptibility, the dose of infection (dependent partly on tick infestation levels) and the age at which infection occurs.
Thus in cattle production systems with indigenous East Africa zebu in the Lake Victoria Basin, where at least two generations of the vector Rhipicephalus appendiculatus occur each year, where all instars may occur on livestock at the same time, where the majority of animals are carriers of Theileria parva at low levels of parasitaemia, and where virtually all animals are infected as calves and become immune before reaching three months of age, little or no clinical East Coast fever (ECF) occurs as a result of T. parva infection.
In contrast, in areas where R. appendiculatus infestations are strictly seasonal and only one generation occurs each year, where clinical cases (with higher piroplasm parasitaemias) occur, and where all animals are not infected as calves, even indigenous cattle may experience outbreaks of clinical theileriosis. In both areas, the introduction of Taurine cattle and their crosses increases the incidence of clinical disease.
The situation in which little or no losses occur due to clinical disease, termed endemic stability, only exists for T. parva infections in a few areas of eastern Africa, but for babesiosis and anaplasmosis it is much more widespread in the continent.
The situation for heartwater is not well documented, but widespread endemic stability is suspected in many areas. The artificial induction of endemic stability through the use of vaccines will provide the most effective and sustainable option for tick-borne disease control in the future. The determination and quantification of the variables contributing to endemic stability and instability are therefore crucial in identifying target populations for tick-borne disease control programs, and assessing their impact.
The most important quantitative indicators of the presence of endemic stability and instability to tick-borne diseases are incidence of infection, incidence of disease, case-morbidity and case-fatality rates in young cattle. Stability is characterized by a high incidence of infection in this age group, but low levels of disease.
Instability is generally characterized by a low and variable incidence of infection, and high incidence of disease. Regrettably, disease incidence, case-morbidity and case-fatality rates are rarely measured accurately under field conditions, and estimates of disease occurrence generally rely on antibody prevalence rates as a surrogate for incidence of infection (and for prevalence of immunity).
Thus, it is important to determine whether it is possible to quantify the relationship between antibody prevalence and these indicators under different conditions and with different tick-borne disease combinations, and to determine the relationship between these indicators and productivity effects (in terms of milk, meat, traction and manure).
An important component of this process is to determine the relationship between antibody prevalence, as measured by current and developing serological tests, and population immunity in the sampled cohort to the spectrum of tick-borne disease antigens they are likely to encounter.
A first step in modelling this dynamic process has been made for T. parva by Medley, Perry and Young (described earlier in the workshop), who simulated endemic stability and tested the effect of tick abundance and carrier state prevalence on its maintenance. However, in order to assess the validity of such models on a broader scale, they require testing in other endemically stable and unstable states.
Regrettably, due to the intensive nature and high cost of prospective studies needed to validate such models, few data sets exist.
Eventually, it is hoped that such studies will lead to the development of user-friendly models that assess the efficacy of tick-borne disease control options for given herds, districts or regions, determine their effects on livestock productivity and assess their economic impact.
With tsetse-transmitted trypanosomiasis, similar models are required, but due to differences in the immune mechanisms involved, it may not be possible to base them on the concepts of stability and instability. Furthermore, it is anticipated that the mechanisms involved are more complex and less predictable.
Needs for modelling socioeconomic and environmental impacts of livestock disease control
One of the research areas of ILRAD requiring modelling is the assessment and prediction of the probable economic, socio-cultural and environmental impacts of alternative control technologies for trypanosomiasis and tick-borne diseases in different production systems and agro-ecological zones in Africa and elsewhere. The application of new technologies to control these and other diseases may cause unforeseen economic, social and environmental consequences for segments of the human population.These effects, which may be better understood and projected through modelling, can include changes in livestock and human population densities, changes in patterns of land use accompanied by environmental changes, increased conflict over resources, disruptions of local social patterns, and increases in income and wealth disparities within the population. Moreover, other constraints within the overall livestock management system may serve to suppress potential benefits resulting from improved livestock disease control.
These can include the existence of other diseases, poor animal nutrition, labour scarcity and lack of access to supporting services such as animal health delivery system, artificial insemination or credit for improvement of livestock.
Modelling can help in identifying such constraints, or in evaluating their effects on potential impacts of alternative control strategies. Ex-ante assessment and prediction of the impacts of disease control through modelling can also help in avoiding possible deleterious effects in the application of new control technologies.
It also provides useful information to farmers, governments and donors in order to assist them in planning better (strategic and systematic) disease control programs. In addition, such information can help in prioritizing the allocation of resources to disease research.
There are not always sufficient data, in content or quality, for assessing and predicting socioeconomic and environmental impacts of disease control. In many instances, the gathering of such data by field studies is unrealistic and costly, particularly given the large and varying geographic areas involved. A more cost-effective approach is to develop models using available field and secondary data that are supplemented by expert opinion, and then use such models for desk-top experimentation and extrapolation in ex-ante analyses.
An additional advantage of models is that once developed and verified they provide a standardized method of data analysis which can be extended to users in different areas and countries, particularly if the models are developed and packaged in user-friendly computer software.
ILRAD has developed and applied spreadsheet models for assessing annual economic losses due to East Coast fever and the financial and economic impacts of its control by immunization at farm and above farm level. These models are being adapted and improved, in collaboration with the AP Consultants of the UK, for the analysis of trypanosomiasis control.
In collaboration with Texas A & M University, a whole farm simulation model has been developed and applied for assessing and projecting farm level financial and nutritional impacts of ECF immunization under small-holder dairy production systems; a similar simulation analysis approach can be extended to trypanosomiasis control in sedentary livestock production systems. ILRAD's current modelling efforts, however, tend to emphasize microfinancial/economic aspects of livestock disease control effects.
Macro-economic sectoral, trade and policy issues are not fully incorporated. In addition, linkages of financial/economic relationships to physical (ecological), biological (epidemiological) and socio-cultural (welfare) factors of livestock production systems are weak.
Future modelling needs will require integration of micro- and macro-economic factors involved in livestock disease control with ecological, epidemiological and socio-cultural factors for more comprehensive assessments of the impacts of alternative control strategies.
Such integrated model(s) will, however, be complex, and technical, data procurement problems and modelling mechanisms required are issues that must be addressed.
The model(s) developed would ideally be suitable for application to different livestock production systems in different environments.
The relationship between infections, diseases and their economic effect
For very few disease agents does infection automatically mean that clinical disease will be expressed. In epidemiological terms, for most diseases there are various risk factors which influence whether an animal which is exposed to an agent becomes infected and generates a host response, and a second (frequently overlapping) set of risk factors which determine whether the infection proceeds sooner or later to clinical disease. Risk factors vary widely in their nature, ranging from the genotype of both host and agent, through the nutritional state of the host at the time, to short-term weather conditions at the location where the animals are kept.
Traditionally these have been classified into host, agent and environment factors, but I would argue that this is in some respects too static a view of the initiation of disease, and that we should look for a more dynamic way of viewing the interactions.
Computer modelling is one way of representing epidemiological interaction realistically and dynamically. While some risk factors are common to many different infectious diseases, others are very specific to a single disease, and it is unwise to extrapolate from knowledge of relevant risk factors for one disease to conclude that the same factors are necessarily important in other superficially similar diseases.
Many diseases exert their effect on productivity most strongly in the early subclinical stages of infection, when there may not necessarily be any evidence of disease, while in others the effects grow as the clinical severity rises.
Overall, the scale of effects of disease on productive capacity of animals is surprisingly large, much greater than would occur by depriving the animal of an apparently similar quantity of nutrients. While it is not completely clear why particular diseases have the effect they do on animal productivity, a reasonable overview of why disease so adversely affects productivity has emerged in recent years, and this is presented in this paper.
The main effect of disease appears to be on protein metabolism. In addition, some diseases reduce efficiency of utilization of various micronutrients, such as Cu or P.
The primary metabolic effects of disease then produce a cascade of secondary effects which can be measured in economic terms. In developing a model of a disease process as a basis for decision-making, consideration must be given to accurately representing these various effects for the particular disease.
The relationship between infection and disease
For very few disease agents does infection automatically mean that clinical disease will be expressed. In epidemiological terms, for most diseases there are various risk factors which influence whether an animal which is exposed to an agent becomes infected and generates a host response, and a second (frequently overlapping) set of risk factors which determine whether the infection proceeds sooner or later to clinical disease. Risk factors vary widely in their nature, ranging from the genotype of both host and agent, through the nutritional state of the host at the time, to short-term weather conditions at the location where the animals are kept.While some risk factors are common to many different infectious diseases, others are very specific to a single disease, and it is unwise to extrapolate from knowledge of relevant risk factors for one disease to conclude that the same factors are necessarily important in other superficially similar diseases. Risk factors can be identified and the scale of their impact (measured variously as relative risk and attributable risk) assessed through appropriate epidemiological study designs using observational data.
Such studies do not always discriminate between infection and disease, including animals as 'cases of disease' only if they show recognizable clinical signs. However for the types of diseases we are currently seeking to control, it is increasingly necessary to look separately at the process of initial infection, at the process of conversion from infection to disease, and at the ways in which animal productivity is affected at each stage. Similarly for non-infectious diseases, there will tend to be a process of lesion production and a subsequent process of development of clinical disease.
A systems view of interactions among factors to produce disease
Traditionally the influences on disease occurrence have been classified into host, agent and environment factors, but we would argue that this is in some respects too static a view of the initiation of disease, and that we should look for a more dynamic way of viewing the interactions. System diagrams aim to represent through boxes and arrows the pathways by which components of a total biological system interact to create the various processes which drive the system through time, and generate whatever 'outcome' variables are decided by the observer to be of interest. In the case of diseases, the outcome variable may be the prevalence or incidence of the disease as determined by the underlying transmission processes, or it may be the (altered) productivity of the animals when affected by the disease. Through the system diagram approach, not only can host, agent and environment be treated as multifactorial influences in themselves (for example breaking environment into multiple climate variables, shelter, nutrient availability etc.), but the nature of the interactions within and among the various factors can be represented precisely, using arrows only between those factors for which an interaction is thought to occur.Figure 1 shows one such example of a system diagram developed in order to represent the causal processes and the way in which they are believed to interact to produce a particular disease. The example chosen is one form of lameness in dairy cattle, known as white line disease. This can cause lameness directly but can also lead on to sole abscess which causes even more severe lameness. The figure is based upon research at both herd and individual animal level, and draws together factors which can operate at each of these levels to influence whether or not an individual animal develops a subclinical lesion or becomes clinically lame, and whether the herd has a high or low incidence of clinical lameness. This particular disease is non-infectious, but such representations are even easier to formulate for infectious diseases where the interactions tend to follow more standard patterns.
Such a system diagram is helpful in presenting an understanding of how factors influence disease processes, but it is still static, in that it does not provide any way of analysing and understanding the dynamics of the disease process over time or its spatial spread for diseases which show spatial patterns of occurrence. Computer modelling takes the process a major step further forward and is the most effective way of representing epidemiological interactions realistically and dynamically. Typically nowadays a computer model is designed by first formulating a system diagram, plus sub-diagrams exploring in more detail each specific facet of the disease processes and then programing a computer to mimic the processes and progress the total system forward through time.
In other papers presented at this workshop, techniques of modelling are considered for different types of disease. However if modelling of parasitic diseases is to include representing their economic effects, then it is necessary to formulate an adequate representation of this part of the disease process to complement the epidemiological part of the total model. This paper therefore concentrates on how disease agents affect productivity of animals and how this should be included in a computer model.
Mechanisms by which disease may alter animal productivity
Figure 2 summarizes the various pathways through which disease can adversely affect the productivity of a livestock herd. In the case of infectious and parasitic diseases the underlying principle is that a disease agent is in constant competition with its host for access to nutrient supplies. The agent is successful if it can divert for its own use and reproduction, nutrients which the animal would otherwise have used for growth and production. The agent must therefore have some adverse effects on the host if it is to survive and multiply. Non-infectious diseases cannot be understood in the same simple way, but do frequently represent a change in ecological balance, in which the flow of nutrients and toxins (copper deficiency, facial eczema, etc.) or of controlling signals (hypocalcaemia, ketosis, etc.) through the agricultural ecosystem is distorted by human or environmental interventions of some type. Some of the same principles therefore apply.The purpose of Figure 2 is to summarize all the possible direct and indirect mechanisms through which a disease can influence the productive efficiency of livestock. Not all diseases will have all of the effects, but in representing economic effects in a model it is necessary to consider all possibilities and select for inclusion those which appear to be relevant. Each of the mechanisms will be discussed individually and then consideration will be given to how they should be combined to evaluate the effect of disease on profitability.
Effects on ingestion
Many diseases alter feed intake in affected animals. In almost all cases intake is reduced (Hawkins and Morris, 1978), but rarely it may be increased (Dargie, 1973). Diseases which cause pain during prehension (contagious ecthyma of sheep) or mechanical difficulty (actinobacillosis of the tongue in cattle) will reduce intake temporarily. Diseases which affect locomotor ability or reduce appetite due to a fever or similar discomfort will also lower intake. However many diseases appear to reduce intake in subtle ways which may not be recognized unless careful measurements are made. These effects have been documented most carefully for parasitic diseases (Larbier et al., 1974), although in some cases intake has been reduced only in more severe forms of the disease (Hawkins and Morris, 1978). Depression of feed intake can also occur in non-infectious diseases such as nutritional deficiencies (Scott et al., 1980).It is intriguing that feed intake should be commonly depressed by disease when other evidence shows clearly that feed requirements are increased by many of the same diseases, since productivity falls under the influence of the disease. From the limited studies which have been conducted to resolve this apparent paradox, it would appear that it results from disturbances in body homeostatic mechanisms of the host. Symons and Hennessy (1981) have found that choleocytokinin levels rise as appetite falls in Trichostrongylus colubriformis infestations, and return to normal in line with appetite when the infestation is terminated. In the same disease, corticosteroid levels rise and thyroxine levels fall in response to the parasite, while insulin levels fall apparently in response to reduced intake rasher then directly due to the parasite (Prichard et al., 1974; Hennessy and Prichard, 1981). The disease agent may also in some cases produce a toxic substance which depresses intake directly (Seebeck et al., 1971). It is important to differentiate between diseases which merely depress feed intake and those which lower the efficiency of feed conversion - with or without any effect on feed intake. Seebeck et al. (1971) called the effect on intake the anorectic effect and that on feed conversion efficiency the specific effect. The specific effect is the more serious of the two, since lower production is achieved from the same feed intake and efficiency of the production process is adversely affected, whereas the anorectic effect reduces both intake and output without altering the efficiency of production. This differentiation is an important consideration in studies of animals which consume purchased feed, such as pigs. It is less important in grazing ruminants, for which feed production is closer to being a fixed cost.
Effects of disease on feed digestibility
Disease agents do not normally seem to affect feed digestibility, even in the case of diseases which undoubtedly alter the morphology and physiological function of the gastrointestinal tract (Parkins et al., 1973; Reveron et al., 1974). Barker (1974) found that abnormal mucosa was not necessarily linked to poor growth, and it seems that changes in the mucosal surface itself are not responsible for the change in feed conversion efficiency which results from parasitism and other diseases, but rather the physiological processes that occur after absorption. Similar findings have been obtained with parasites such as Fasciola hepatica which do not cause mucosal changes (Hawkins and Morris, 1978). One of the few reports of a reduction in feed digestibility for ruminants was for magnesium deficiency in dairy cows (Wilson, 1980). However the situation may be different in monogastric animals, since two studies of the effects of internal parasites in pigs both showed reductions in feed digestibility (Hale and Stewart, 1979; Hale et al., 1981).It nevertheless seems likely that, at least in ruminants, adverse effects of disease on productivity which cannot be explained by reduction in feed intake can reasonably be attributed to lower feed conversion efficiency; although as Symons (1969) points out, digestibility trials are a crude method of assessing changes in digestive function. It is also clear that the nature and extent of pathological changes in the body cannot be used as any direct guide to the severity of effects of a disease on productivity.
Effects of disease on physiological processes
Diseases can modify many different physiological processes, such as nutrient metabolism, respiration and excretion. Most of the available data relate to parasitic diseases and the evidence from these studies suggests that the fundamental effect is on protein metabolism.Steel (1974) and Symons and Steel (1978) have reviewed the metabolic consequences of gastrointestinal parasitism, with particular reference to sheep. They conclude that helminth disease causes a series of metabolic changes to occur in the animal, the primary impact of which is on protein metabolism. The effects, however, carry through to the metabolism of other nutrients. The result is to produce a syndrome analogous to undernutrition.
In gastrointestinal nematode infestations, plasma is lost into the digestive tract at the attachment sites of the parasites, and haemoglobin is also removed by blood-sucking parasites. Much of this protein is digested and reabsorbed lower in the tract, but the host uses energy and protein to replenish the mucosa and plasma proteins which have been depleted. This places demands on the liver and increases its nutrient utilization. There is increased excretion of nitrogen as urea in urine, demonstrating that recycling of the nutrients is not completely efficient in maintaining nitrogen balance, even though considerable energy costs are incurred by the host for increased protein synthesis.
Animals tend under these circumstances to run down their pool of plasma proteins because production in the liver cannot keep pace with the loss, even though the synthesis rate is unusually high. Adjustments are made to other nitrogen-using processes of lower priority, notably synthesis of wool protein and muscle protein. In sheep, sulphur-containing proteins are put in especially short supply by Trichostrongylus colubriformis infestation, demand cannot be met, and wool production shows an exceptionally large fall.
If feed intake is reduced either due to the parasite or to a low plane of nutrition, protein intake may fall below the level required to maintain an adequate serum protein pool. Bown et al. (1986) have shown that direct post-ruminal infusion of casein in sheep receiving daily doses of larvae of Trichostrongylus colubriformis increased nitrogen retention five-fold, and supported the argument as outlined above that the primary defect is one of protein loss and an anabolic cost of tissue regeneration. Infusion of glucose in amounts isocaloric with the casein only doubled nitrogen retention, showing that energy supplementation was not as beneficial as protein replacement.
A contrasting example to Trichostrongylus colubriformis is the cattle tick Boophilus microplus, which sucks blood much like some internal parasites, but differs in that the animal cannot recover any of the nutrient content of the blood in this case. The effects of ticks on host metabolism have been studied by Seebeck et al. (1971), O'Kelly et al. (1971) and Springell et al. (1971). Haemoglobin and plasma albumin fell, whereas globulin rose. Thus the animal was able to synthesize increased supplies of globulins, but could not maintain levels of the other two blood constituents. This was attributed in part to a disturbance of protein metabolism, but the injection of a toxin by the tick was also hypothesized. To further emphasize the tenuous link between the pathology of a disease and its effects on productive processes, O'Kelly and Kennedy (1981) found that ticks adversely affected function in the gastrointestinal tract and reduced organic matter digestibility. It is difficult to explain why this should be so when such effects are not common for parasites directly affecting the tract.
Although these are the two most fully studied diseases, evidence for other diseases in a variety of species confirms the central importance of the derangement of protein metabolism in the disease process. There is also impairment of energy metabolism, but this appears to be largely secondary to the alterations in protein metabolism, and is a result primarily of the energy costs of tissue regeneration.
Mineral and micronutrient metabolic flows are also altered by parasitic diseases, which are the only ones to have been studied. There is reduced retention of ingested calcium and phosphorus in growing sheep infested with Trichostrongylus colubriformis or Ostertagia circumcincta (Symons and Steel, 1978). Consequently, bone growth and skeletal development are impaired, and this can reduce mature body size and capacity to accumulate muscle (Sykes et al., 1977). Cobalt, copper and vitamin status of animals have all been reported to be affected by parasitism (Downey, 1965, 1966a, 1966b) as well.
Since lung disease can adversely affect productivity, another mechanism by which disease might impair physiological function is a reduction in respiratory function. It seems more likely, however, that it is the regenerative process following lung disease which cause the production deficit.
Measurable effects of diseases on livestock productivity
The functional derangements described above translate into measurable economic effects in a number of waysPremature Death
This effect is the easiest of all the consequences of disease to measure, and therefore tends to be considerable over-emphasized in comparison with other effects. In economic studies, death losses should be measured as the difference between the potential market value of the animal and its value when dead (which may not be zero), less the costs which would have been incurred in obtaining the market value (such as extra feed and care to market age, marketing costs, etc.).
Changed Value of Animals and Products From Slaughtered Animals
Diseased animals may have lower market value either due to visible lesions or due to indirect changes in appearance or body conformation which make them less attractive to buyers. True market value of final products may be altered due to changes in the ratio of meat to fat or to bone (Springell et al., 1971; Sykes et al., 1980), or reduced protein content. The value of offals may also be reduced due to pathological changes caused by agents such as Fasciola hepatica or Echinococcus granulosus. Presence of lesions of a zoonotic disease may render the animal totally unfit for consumption.
Some diseases (such as caseous lymphadenitis in sheep) may render products less attractive to the consumer for aesthetic reasons, and hence may reduce meat consumption. Diseases which affect the skin, such as warble fly infestation or even sheep lice (Britt et al., 1986), may reduce the market value of hides or their value to the user.
Reduced Liveweight Gain
There have been well in excess of 50 published studies on the effect of diseases on weight gain in animals and in general they find that diseased animals gain weight more slowly than equivalent disease-free animals. Notable as an exception is lice infestation in cattle. It has been among the most intensively studied but the evidence shows that differences in weight gain between infested and free animals are modest or negligible, and certainly not enough to yield an economic benefit from treatment. Therefore caution is required in assuming an effect on weight gain of a disease without experimental data to support it.
Reduced Yield and Quality of Products From Live Animals
Yield of products such as milk, wool and eggs may also be reduced by disease, and there have been numerous papers showing the effect of various diseases on wool growth or milk-yield. Quality of the products may also be reduced, as in the case of the changes in milk composition which result from bovine mastitis, and these may or may not be detectable by the consumer. In the first case price will fall and the livestock producer will suffer; in the second case, the consumer will suffer the loss. For example, parasitic disease can reduce the market value of wool per kg, as well as the quantity produced (Morris et al., 1977); but the structural characteristics of the wool may also be altered in ways which reduce its value to the manufacturer but cannot be detected in the normal marketing process (Johnstone et al., 1976). It has also been shown that parasitic disease can affect the taste of meat (Garriz et al., 1987).
Reduced Capacity for Work
Worldwide, the single most important use of animals is as a source of traction. The second largest (after dung) productive energy output of animals in developing countries is for work, and products considered as of central importance in developed countries are seen as bi-products under those conditions (Odend'hal, 1972). There have been no published reports directly measuring the effects of diseases on capacity for work, but field evidence is that diseases can severely curtail rice paddy preparation and other tasks for which animals are essential, so this effect can be very important and should be considered in developing countries.
Altered Production of Dung for Fuel and Fertilizer
In Asia and Africa cattle dung is a vital source of cooking fuel and in much of the developing world it is an important fertilizer. Diseases which cause high death rates in cattle will also indirectly influence human nutrition by reducing dung supplies.
Altered Feed Conversion Efficiency
As discussed earlier, it appears that disease primarily affects animal productivity by altering the metabolic processes for protein and other nutrients, thereby reducing the feed conversion efficiency of affected animals and producing a number of ramifications which reduce herd productivity. Feed intake may also be reduced, but this is not usually the primary effect.
Feed conversion efficiency is the ultimate measure of the influence of disease on the production process, but its measurement requires accurate measurement of feed intake, and that is only possible under controlled feeding conditions. In grazing systems it is usually reasonable to take changes in productivity as an adequate indication of changes in feed conversion efficiency when comparing diseased and disease-free animals kept under identical conditions.
Intuitively, it seems likely that the rate of decline in productivity would increase as the disease becomes more severe and body functions become more deranged. However, the limited evidence available favours the alternative view that the most dramatic changes occur at low or subclinical levels of disease, and that each additional parasite, for example, has less effect than the one before it (Hawkins and Morris, 1978). This emphasizes the importance of the health management approach in which the focus is on optimizing productive efficiency rather than the clinical approach in which a disease must be detectable to be considered important.
Effects of disease on herd productivity
The effects of disease flow through from consequences for individual animals to broader ramifications for herd replacement and improvement.Reduced Productive Life of Animals
Apart from animals which die, all remaining herd members are culled when the manager considers them less potentially productive than the animal which would replace them. This issue has been investigated in detail by Renkema and his co-workers (Renkema and Stelwagen, 1979; Korver and Renkema, 1979; Dijkhuizen et al., 1985a, 1985b). They showed that in general a substantial economic benefit could be achieved by taking action to extend the herd life of the average dairy cow, principally by reducing the amount of involuntary culling due to health-related causes. This is not limited to disposal specifically because of disease, but also includes culling for low yield or other causes, where the underlying cause is lowered productivity due to disease, but the manager is unaware of this fact.
Less Accurate Genetic Selection
If a disease alters any of the components of productivity which are the subject of genetic selection pressure in the herd (such as milk or wool yield), it will affect the efficiency with which animals of superior genetic merit are identified, especially if the probability of an animal being affected by the disease is unrelated to yield level. Provided susceptibility to the disease and yield level are not correlated, the presence of the disease will confound the genetic selection effort. For example, Johnstone et al. (1976) showed that internal parasitism can affect wool production by sheep in ways which distort selection by objective measurement of wool characteristics. Since resistance to internal parasitism cannot be regarded as a heritable trait for practical purposes, genetic selection will be more efficient if effective parasite control is being carried out in the herd.
Effects on capacity to maintain and improve herd
If fewer progeny are born, less animals are available as herd replacements or for sale as market products. Thus not only will livestock sale income be reduced, but management flexibility for herd improvement will be curtailed. It is self-evident that diseases of the reproductive tract in both males and females can substantially reduce the level of reproductive performance, and hence the number of progeny born in the herd.Less obviously, diseases which adversely affect body metabolism (but do not directly affect the reproductive tract) can also affect the number of progeny born. The mechanisms have not been fully explored, but may well operate through an effect on liveweight and condition, or through indirect means such as the induction of pyrexia at critical stages in the reproductive process. For example, both gastrointestinal parasites (Murray et al., 1971) and liver fluke (Hope Cawdery, 1976) have been shown to affect reproductive performance in ewes. In cattle, bovine leucosis (Schmied et al., 1979; Parchinski, 1979) and ephemeral fever (Theodoris et al., 1973) have been reported to affect reproduction. If reproductive performance is too poor, it may even become impossible to maintain herd size through home-bred replacements, necessitating the purchase of breeding animals with all the additional risks which that entails.
Effect of disease control measures in productivity of animals
In evaluating the economic benefit of disease control, it is necessary to consider not only the difference in productivity between diseased and disease-free animals, but also the changes in productivity which follow elimination of a disease from an affected animal.This has not been studied for very many diseases, but some examples exist. For instance, bovine mastitis appears to be a disease for which complete regeneration occurs in most animals over the dry period following elimination of an infection (Morris, 1973), although yield remains depressed for the rest of the lactation in which a cure is achieved. Conversely, when infestations with Fasciola hepatica are eliminated in growing animals, sheep do not regain their former productivity or feed conversion efficiency, even when the infestation had existed for as little as eight weeks (Hawkins and Morris, 1978). In a study of a nematode parasite, wool growth and liveweight gain responded quite differently to anthelmintic treatment (Coop et al., 1984).
Therefore each disease type must at least in the first instance be considered separately, since the nature and extent of recovery following elimination of a disease is not predictable from general principles. The selection of an economically optimal control strategy will be strongly influenced by this consideration.
Effects of animal disease on human welfare
Effects on Human NutritionThe major direct effect of animal disease on human well-being is through reducing the supply of high quality protein, such as diseases which reduce the supply of milk for young children. Animal products are also important sources of other nutrients, notably minerals and vitamins, and diseases can both reduce the total supply of animal products and modify the composition of animal products in ways which reduce their nutritional value (Huss-Ashmore and Curry, 1992).
Effects on Community Development
As well as the effects on human nutrition, animal diseases can affect other aspects of community welfare, especially in developing countries. As discussed earlier, the two most important services provided by animals in such circumstances are traction and dung production, and disease may reduce the supply of both of these. Animals are also important sources of products (wool, hair, hides, feathers, fur, etc.) used for clothing, decoration and for manufacture of utensils and other products. A further effect of those animal diseases which are zoonotic is to cause disease in the human as well as the animal population, thus amplifying their impact.
Cultural Significance of Animals
In most communities animals serve functions far beyond the utilitarian roles which are the focus of this paper. While these are not strictly economic in nature, they are vital functions which should be included in any consideration of the significance of animal disease.
Effects of disease on animal welfare
In considerations of animal welfare issues, little is said about the importance of ensuring through disease control that animals are in a healthy state - yet this is a vitally important issue in protecting the welfare of managed animals. It deserves more prominent attention in discussions of animal welfare matters.Inclusion of economic effects in a disease model
The formulation of an economic analysis for parasitic diseases is described by Morris and Meek (1980). Meek and Morris (1981) showed how economic components could be built into a computer model, which could then be used to conduct comprehensive evaluations of alternative parasite control programs.Provided that the relevant items from Figure 2 are included into the total simulation model by linking them to the appropriate ecological and epidemiological indices within the overall system model, then estimation of the benefits of disease control strategies within the simulation model becomes straightforward, and depends only on the availability of suitable field data on the effects of the disease on various yield measures. If such data are unavailable when the model is formulated, guesstimates can be used initially and sensitivity analysis applied to determine which of the productivity indicators most urgently need field refinement.
Estimation of costs at farm level can usually be done quite simply from information on the unit costs of control measures, since a partial budgeting approach to such economic analyses is almost always adopted at this level.
In regional evaluations it may be necessary to build a complete model of a regional disease control program. However in many cases it is sufficient to run the model for various types of farms and sets of conditions and then to combine these through an electronic spreadsheet in which the regional total effects are calculated, taking into account costs above the farm level and possible supply/demand consequences of disease control programs.
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