Scientific and Technical Review 43 2024 | 58-68 https://doi.org/10.20506/rst.43.3518 Loss of production and animal health costs in assessing economic burden of animal disease T.L. Marsh* (1, 2), D. Pendell (1, 3), P. Schrobback (1, 4), G. Shakil (1, 2) & P. Tozer (5) (1) Global Burden of Animal Diseases (GBADs) Programme, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, 146 Brownlow Hill, Liverpool, L3 5RF, United Kingdom (https://animalhealthmetrics.org) (2) School of Economic Sciences and Paul G. Allen School for Global Health, Washington State University, Hulbert 101, Pullman, WA 99164, United States of America (3) Department of Agricultural Economics, Kansas State University, 342 Waters Hall, 1603 Old Claflin Place, Manhattan, KS 66506, United States of America (4) Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, 306 Carmody Road, St Lucia, QLD 4067, Australia (5) School of Agriculture and Environment, Massey University, Private Bag 11 222, Palmerston North, 4442, New Zealand *Corresponding author: tl_marsh@wsu.edu Summary This article focuses on identifying the loss of production and costs (or lack thereof) associated with livestock health as well as animal disease externalities, with the intent to estimate economy-wide burden. It limits its scope to terres- trial livestock and aquaculture, wherein economic burden is predominately determined by market forces. Losses and costs are delineated into both direct losses and costs and indirect losses and costs, as well as ex post costs and ex ante costs. These costs include not only private expenditures but also public expenditures related to the prevention of, treatment of, and response to livestock disease. This distinction is important because a primary role of government is to mitigate externalities. The article then discusses market impacts and investments. Finally, it provides selected examples and illustrative observations and discusses future directions for research and application. Keywords Animal – Burden – Costs – Diseases – Expenditures – Externalities – Health – Human – Losses – Markets. Introduction A primary motivation for this article is to summarise the exist- ing knowledge and information gaps in assessing the global burdens of animal diseases and how these economic bur- dens are distributed across value-added supply chains [1-3]. The article focuses specifically on identifying the losses in production and costs of livestock health and animal disease externalities, with the intent to estimate economy-wide bur- den. Specifying losses (e.g. morbidity and mortality) distinct from production is essential as loss relationships have dif- ferent outcomes and properties than do production func- tions, while specifying costs is necessary to fully identify economic burden [2]. The authors limit their scope to terres- trial livestock and aquaculture, wherein the economic bur- den is predominately determined by market forces, and do not consider companion animals or wildlife. Consequently, the framework is laid out by economic principles of produc- tion, losses and costs, market forces and failures, trade and welfare economics [2,4-6]. The article also discusses infor- mation and data required to assess total economic burden from losses and costs due to animal health and livestock dis- ease externalities, which are often sparse or missing in many countries across the world (e.g. Schrobback et al. [7]). When data are sparse or missing, alternative means by which to elicit loss and cost data, such as use of non-market data, are also suggested. Finally, the article provides selected ex- amples and illustrative observations, then addresses some empirical issues and future directions for research and appli- cation. The overall intent is to improve understanding for pol- icy-makers regarding the importance of production loss and cost data in estimating economic burden for more informed decision-making and the importance of measuring the im- pacts of those decisions. https://doi.org/10.20506/rst.43.3518 https://animalhealthmetrics.org/ mailto:tl_marsh@wsu.edu 59Scientific and Technical Review 43 2024 Background The general approach to assessing the economic burden of animal disease, common in economics literature, is to use supply-and-demand relationships to provide a framework with which to analyse trade outcomes and to assess economic bur- den of diseases at equilibrium prices and quantities [2,8]. The authors maintain that supply is derived from profit maximisa- tion of the firm [9,10], and also that consumer demand is de- rived from utility maximisation subject to a budget constraint with the standard assumptions under classical duality theory and consequent properties [9,11]. Hence, optimisation, rather than advocacy, is the driving objective of this approach, allow- ing economic efficiency to enter into the burden assessment. Drawing from the theory of welfare economics, principles of economic surplus are applied to measure the well-being of firms along a supply chain and the well-being of consumers, an approach that, in practice, requires changes in market equilibrium prices and quantities from a baseline to identify the values of the requisite counterfactual scenarios [2,6,12,13]. Profit maximisation is an appropriate metric for live animal production and processing to assess economic burden in a market setting [2,5,14,15]. There are several reasons for this. First, profit in animal agriculture reflects revenues from product sales less production costs for smallhold- ers and commercial operators alike. Operators both small and large, and at any stage of the supply chain, must make non-negative economic profits over the long run to stay in business. Second, profit is the difference between revenue and costs. Losses due to morbidity dictate reductions in pro- ductive output, and these are reflected in revenue decreases, while costs adjust according to treatments [2]. Third, live- stock are considered capital assets; as a result, the value of an asset is determined by its equilibrium market price [7,16]. Hence, losses in livestock due to mortality result in losses in asset values. In all, changes in profit plus changes in asset value reflect the net change in direct economic burden for the live animal producer [2,5,6,15]. Finally, the field of welfare economics identifies changes in profit maximisation – and not simply changes in supply – as a metric consistent with the concept of economic welfare for a firm and for society [2,5,6]. For example, instances of oversupply in milk are common in agricultural production (say, from increases of productivity). Yet, in some circumstances, more milk does not necessar- ily improve the welfare of the producer. Rather, instances of oversupply of milk can coincide with lower prices, such that revenues are less than costs of production. Hence, profits are negative, and it is the profit metric that is consistent with decreases in economic welfare to the producer. The upshot is that the economic burden of livestock disease and animal health is translated through profit, and not some other ad hoc value or quantity, as an appropriate metric. More generally, assessing livestock disease burden is differ- ent from assessing the same for human health [1,17]. Livestock lifespan is dictated by market forces, such that metrics like disability-adjusted life years (DALYs) that are generally ap- plied to human health are not sufficient to assess the eco- nomic burden of farmed animals in a value-added supply chain. Livestock are farmed animals that provide livelihoods to households across the world. Therefore, losses and costs that arise in both the production and the trade of animals and animal products along the value chain to consumption are key components in assessing the economic burden on those households. Under competitive markets, well-defined tech- niques exist to monetise both benefits and costs of mortality and morbidity outcomes in animal value chains that con- tribute to burden [2,6]. Under non-market circumstances, in which prices are not reported or not available, one can apply experiments to monetise an individual’s willingness to pay (WTP) to avoid a human health risk or an animal health risk (e.g. Goldberg and Roosen [18], Pendell et al. [19], Alolayan et al. [20]). It is reasonable to measure the social burden of market failures (e.g. responses to disease externalities and inter- ventions), as well as the distributional impacts from trade embargoes, on economic agents vertically along the sup- ply chain from firms to consumers [21]. For animal agricul- ture, wherein live animal producers exchange with traders or buyers, and animals are slaughtered and processed with capacity utilisation and scale economies, driving market out- comes, the impacts along the supply chain are particularly important to understand [22]. These costs include not only private expenditures, but also public expenditures related to prevention of, treatment of and response to livestock disease. This is important because a primary role of government is to mitigate externalities, including animal diseases. For exam- ple, this framework has been applied to assess the economic burden of foot and mouth disease (FMD) in livestock in the United States of America (US) [10,23], Mexico [24], Australia [25] and Canada [26]. In the context of livestock disease and animal health, Marsh et al. [6] and Hennessy and Marsh [2] provide guidance on welfare economics, economic surplus, present value and discounting. One can extend this approach to a One Health framework integrating both animal and human health to assess the eco- nomic burden of zoonotic diseases [27]. For instance, Pendell et al. [19] assess the economic impacts of a hypothetical Rift Valley fever outbreak in the US. Rift Valley fever is a zoonotic disease endemic across much of the world. In livestock, it can lead to abortions, haemorrhages and death, while in humans it can lead to illness, blindness and death [28]. Pendell et al. [19] assessed not only the economic impacts on agricultural producers and consumer demand, government costs of response, and costs and disruptions to non-agricul- tural activities in the regions, but also human health (mor- bidity and mortality) outcomes. Specifically, they estimated WTP to monetise illness and blindness and applied the value of statistical life to monetise loss of life. Rahman [29] also 60Scientific and Technical Review 43 2024 applied a One Health approach to assess the dual burden of anthrax in Tanzania, estimating WTP for illness in both humans and livestock. In all, economists can and often do monetise the conse- quences of events or policies into a single monetary unit that is readily comparable, scalable and useful for measuring changes in efficiency (the size of the economic pie) and ex- amining equity (the distribution of the economic pie) [5,30]. This approach also allows for disaggregation of the distribu- tion of private and public benefits and costs vertically along the supply chain, as well as horizontally across different mar- kets [13]. In this manner, economists measure who is bur- dened and how much. Losses and costs Economies face both losses and costs due to disease and health events. It is commonplace to delineate losses and costs into both direct losses and costs and indirect losses and costs, as well as ex post costs and ex ante costs [31]. The authors adopt and acknowledge this perspective and extend it into a One Health framework for zoonotic diseases. Before going into detail on losses and costs, the article highlights how these are applied in wider economic assessment, as well as the information and models used for doing so. Figure  1 provides an overview of how losses and costs due to livestock disease and animal health may be applied in a wider economic assessment. First, losses and costs are identified, collected and/or estimated from the literature or from output of an epidemiological model. These estimates are then entered as direct exogenous shocks to produc- tion (e.g. changes in morbidity or mortality of livestock), to demand for products (e.g. changes in consumer demand) and/or to trade (e.g. changes in trade status or embargoes) into an economic equilibrium model to estimate changes in markets (prices and quantities). Economic outcomes from equilibrium models vary with the exogenous shifts applied at different stages of the value chain [32]. As such, the losses and costs may induce changes in broader economic out- comes (e.g. gross domestic product, income), in government expenditures (e.g. response costs) and in the economic bur- den on human health (e.g. morbidity and mortality). The sum of these impacts is total economic impact. Paarlberg et al. [21] and Pendell et al. [19,23] provide examples of how losses and costs have been applied in assessing livestock disease outbreaks in the US. For the interested reader, Pritchett et al. [33] provide an overview of modelling approaches in assess- ing livestock disease and animal health events. Underlying the losses and costs are maintained information and additional data on livestock inventories, market struc- ture and firm behaviour, human population and culture, and institutional structures of the region of interest that are necessary to predict outcomes of wider economic scenarios. Equilibrium models encompass this information and data in a systematic structure of the economy. These models are then used to simulate counterfactual scenarios to evaluate alter- native events, and the outcomes of those scenarios in turn are Direct, indirect and market losses Agricultural sector • Production • Processing • Imports and exports • Consumption • Partial equilibrium or • General equilibrium Non-agricultural • Tourism • Travel • Lodging and food • Input–output models or • General equilibrium Government • Surveillance • Biosecurity • Indemnification • Response • Clean-up • Budgeting and/or • General equilibrium Human • Morbidity • Mortality • Labour • Income • Cost-effective analysis with DALYs or • Willingness to pay with value of statistical life Indirect losses Ex ante and ex post costs Direct and indirect losses Total economic impacts DALYs: disability-adjusted life years Figure 1 Illustrative losses and costs in burden assessment for economic impacts on livestock disease Source: adapted from Pendell et al. [19,23] 61Scientific and Technical Review 43 2024 used to better plan resource use, mitigate risk and capitalise on opportunities. More specifically, livestock inventories and livestock products produce revenues, while livestock them- selves are capital goods that produce asset values for the household or firm. Perhaps surprisingly, significant gaps in these data exist across the world [7] (see Table I for additional details and observations). Market structure dictates the sup- ply chain, and firm behaviour dictates patterns of substitution among goods and efficiency of resource use. Human popula- tion and culture are key determinants of demand for livestock and livestock products. Market structure and demand are typically captured in the configuration of equilibrium models. For example, equilibrium displacement models capture this behaviour with price, income and substitution elasticities, as well as other relationships and constraints, as specified in the model [21]. Government institutions are key in determining public expenditures and determining efficient and sustaina- ble trajectories of economic growth. Partial equilibrium mod- els often budget government expenses outside the model, while general equilibrium models such as the Global Trade Analysis Project model include governments as an economic component within the model [34]. While the primary focus here is on live animal production, losses and costs can also arise vertically upstream or downstream of live animal production in the value-added supply chain (Fig. 2) or horizontally across economic sec- tors. For instance, losses and costs may arise upstream in sourcing inputs (e.g. labour) and downstream in the processing of commodities and distribution of products (e.g. infected animals and/or contaminated carcasses) [19,21,23]. Alternatively, examples of horizontal sectors are the pharmaceutical [35] and tourism sectors [19,23,36]. On the human health side, observations from the COVID-19 pandemic are particularly insightful, as both losses and costs due to human disease and health arose during the pandemic [37]. Barrett et al. [38] argue that the major agri-food system disruptions from COVID-19 originated predominately in the retail mar- ket from demand-side shocks caused by workplace closures, with labour shortages throughout the value chain. The Global Burden of Animal Diseases (GBADs) programme [1,17] implements approaches to provide information on direct productivity changes for live ani- mal producers through its Animal Health Loss Envelope, as well as the indirect economic impacts of livestock disease and animal health through partial and general equilibrium models. Direct losses Direct losses are losses from physical output (morbidity) and Table I Livestock disease burden data requirements, availability, gaps and observations across countries Term Requirements Availability Gaps Observations Direct losses and costs Production output quantities and prices; production input quantities and prices; morbidity and mortality estimates; livestock inventories, replacements and prices Production for primary output (meat, milk, eggs, etc.) and prices; production inputs and prices for feed; livestock inventories and prices Production inputs for capital, labour, energy, animal health, land and resources; costs for draught animals; replacement numbers and prices; morbidity and mortality estimates (a) Systematically collect input data akin to crop agriculture; morbidity and mortality estimates by species and disease akin to human health; costs for draught animals; replacement numbers and prices by species Indirect losses and costs Production outputs, inputs and prices along supply chains for processors, wholesalers and retailers Sparse input and output data exist for processing, wholesaling and retailing across sectors (b) Data gaps in outputs and inputs of firms between producer and consumer (a) Improve systematic collection of data along supply chains; especially for animal agriculture Trade data Domestic and international trade data Supply and demand data, import and export data (c) Inspection and quarantine data; embargo data (c) Multiple sources provide access to national and global trade data Public expenditure Ex ante: biosecurity, surveillance, stockpiling Ex post: response, clean- up and recovery; as well as research and development, engagement Data may be collected ad hoc and reported internally to government agencies Data are often not collected, confounded with other public expenditure data, not reported or not available for public use (d) Systematically collect public and private expenditure data akin to human health; standardise collection of national accounts, and have open access to data (a) Data usually generated at firm level, but not necessarily available at national or global level for every species (b) Selected input–output and equilibrium models provide multipliers, elasticities, social accounting matrices and other parameters at regional or national levels; usually available but not necessarily free (c) Data usually reported at regional or national level and aggregated to global level, but not at disaggregated firm level (d) Public expenditure data usually not available at firm or global levels but may be collected at regional or national level. Private expenditure data generated at firm level, but often not reported or not available at national or global level 62Scientific and Technical Review 43 2024 assets (mortality). On the upstream part of the supply chain, for livestock production these could be, for example, from the reduction in meat or milk output or loss of livestock itself [39]. Peterman and Posadas [40] reported direct economic impacts of fish diseases. On the downstream end of the sup- ply chain, a direct loss could be from an adverse consumer reaction to a food safety outbreak (e.g. E. coli contamination in meat products) in the retail market [41,42]. Costs for di- rect losses are often quantified by changes in market input and output quantities with fixed market prices [15]. If market prices are not sensitive to a disease outbreak or health event, then this is appropriate. Otherwise, for wider economic ef- fects, when applying equilibrium models, the direct losses are quantified with changes in both quantity and prices [4,10,23]. The GBADs programme estimates direct financial effects on the live animal producer in the form of the Animal Health Loss Envelope, which calculates changes in revenue and livestock assets with fixed prices plus changes in input expenditures [15]. It is relevant to point out and emphasise that direct losses can arise horizontally in other sectors of the economy out- side of agriculture. For example, consider quarantine im- pacts on tourism. Blake et al. [36] estimate that the direct losses to tourism following the 2001 FMD outbreak in the United Kingdom were equal to the losses in the agricultural sector, excluding the producer compensation from the gov- ernment. Pendell et al. [23] have also recognised and cal- culated tourism impacts from hypothetical FMD outbreaks in the US. For human health, direct losses caused by COVID-19 arose from people dying from COVID-19 or suffering short-term illnesses or long-term health consequences. DALYs, a nonmonetary measure of morbidity and mortality applied to assessment of human health burden along with cost- effective analysis, are often applied in the context of human health [43]. Direct losses and costs for humans can also be monetised by economists with WTP or cost of illness (COI) to assess morbidity, or with the value of statistical life to assess the loss of human life [18,20,44]. In the case of Rift Valley fever, Pendell et al. [19] estimated WTP to avoid illness (US$ 1,525 per adult) and blindness (US$ 75,833 per adult), and the value of statistical life to monetise death (US$ 8,160,000 per adult) based on Viscusi and Aldy [44]. Rahman [29] reports direct animal or asset losses to anthrax in a hyper-endemic area of Eastern Africa, the Ngorongoro Conservation Area of northern Tanzania. Households’ willingness to contribute to prevention and treatment measures for humans and livestock was driven by the effectiveness of those measures and the severity of infection in humans. Figure 2 Vertical market model of livestock production and value-added supply Outputs: live animals (meat, hides), milk, eggs, manure, draught, etc. Inputs: capital, labour, land and resources, feed, animal health Wholesale supply Live animal production Nutrition Exports Exports Livestock inventories Imports Imports Management Retail consumer Processing 63Scientific and Technical Review 43 2024 Indirect losses Indirect losses are subsequent secondary losses that follow from the initial physical damages. Like direct losses, indirect losses may arise upstream or downstream of live animal pro- duction (Fig. 2). Indirect losses may come from transporta- tion or travel disruptions and business interruptions along the entire supply chain, but more broadly include the loss of wages and tax revenue. On the downstream end of the sup- ply chain, there could be an indirect loss translated through higher prices or lower consumer income curbing purchases in the retail market [41,42]. Stress and mental health issues contribute to indirect losses as well [45]. Indirect losses come in many forms and are critical com- ponents of an economic assessment. For instance, live- stock disease events and subsequent quarantines tend to create spillovers out of agriculture into other sectors of the economy (e.g. pharmaceuticals, transportation, tourism). Blake et al. [36] estimated the indirect losses to tourism following the 2001 FMD outbreak in the United Kingdom, finding the indirect effects on tourism 20 times greater than the indirect effects on agriculture. In the case of COVID-19, indirect losses included loss of income and an overloaded human health system [37]. The aquaculture industry also experienced indirect effects due to COVID-19, as discussed in Aarstad et al. [46]. Partial equilibrium mod- els generally require explicit inclusion of the sectors in which the exogenous shocks were applied and therefore are not suited to indirect cost assessment like input–output and general equilibrium models [47]. The authors note that gen- eral equilibrium models are particularly effective in estimat- ing indirect losses, including estimating spillovers from one sector of the economy into other sectors of the economy. For example, the GBADs programme captured indirect effects of livestock disease and animal health in Ethiopia using a general equilibrium model [35]. From a broader social per- spective, indirect losses could also consist of limitations on health through nutrition, education opportunities and future economic growth [39,48,49]. Ex ante and ex post costs Expenditures come in the form of ex ante costs and ex post costs. Ex ante costs are preventive mitigation expenditures prior to an event, such as biosecurity, surveillance and stock- piling costs. Ex post costs are mitigation expenditures made during and after an event and during the recovery period, such as response, clean-up and recovery costs. These costs include private expenditures by firms and pub- lic expenditures by governments. Private costs may include expenditures on surveillance, biosecurity and prevention, as well as response, clean-up, recovery and business inter- ruption [50]. Private costs also include asset loss with live- stock death. Because a primary role of the government is to mitigate negative externalities [5], public costs include not only preventive expenditures on surveillance, biosecurity and stockpiling in an effort to mitigate disease externalities, but also response, clean-up, recovery and indemnification expenditures [31]. Indemnification expenditures by govern- ments tend to partially offset private asset losses [2]. As such, while private expenditures are intent on safeguarding individual herds, public expenditures mitigate negative ex- ternalities and safeguard society. Several examples are noteworthy. Seeger et al. [51] provide comprehensive estimates of ex post government costs for the 2014–2015 high pathogenicity avian influenza (HPAI) outbreak in the US, which required $US 879 million in pub- lic expenditures to eradicate the disease from poultry pro- duction. Total response costs for government and farmers were $US 459 million, of which $US 70 million were farmer costs. Those authors also report cost by response activity and per bird. This study is an exception, as government costs for animal health events are generally not system- atically collected and can be difficult to access or are not publicly available. Dorn et al. [37] provide examples and estimates for selected COVID-19 costs. Historically, to- tal public expenditures on research and development have been explored by Wohlgenant [12], Alston [13] and Holloway [32]. Market impacts and investment Market impacts are a particularly important component of livestock burden. Changes in the status of livestock disease or animal health often lead to changes in market outcomes (prices and quantities) for inputs, outputs and assets in both the domestic and international markets (Fig.  2). Such changes could arise via shocks in demand or supply, as well as government-imposed quarantines or trade embargoes or other constraints on the system [19,23,52]. Quantification of market impacts on both prices and quantities typically relies on either partial equilibrium or general equilibrium models of the sector or sectors in the country or region under study [2,6,21,35]. It is standard practice to measure these market impacts by applying welfare measures of economic surplus, such as consumer surplus, producer surplus and asset value [2,4-6,13]. In doing so, changes in revenue for livestock and livestock products in both domestic and international mar- kets, as well as the costs of trade, can be captured from quarantines or trade embargoes [10,19,23-26]. The GBADs programme measures market impacts of livestock disease and animal health translated through the Animal Health Loss Envelope and its attribution [15,35,52]. Additional observations about trade and investment are in order. Since the onset of COVID-19, global supply chains have experienced increased trade costs and reduced labour participation along the supply chain [53]. Moreover, invest- ment in animal and human infrastructure and health was also 64Scientific and Technical Review 43 2024 impacted by COVID-19. Farms, processing firms and other firms increased investment in robots invulnerable to infec- tious diseases [38]. Adjustment costs arise when farms and firms respond to livestock disease and animal health events in dynamic economic models [10,24-26]; for instance, vac- cines were stockpiled after the 2014–2015 HPAI outbreak [54], while investment and adjustment costs expanded dur- ing COVID-19 [38]. Discussion As noted in the introduction, this article has limitations. It focuses on losses and costs needed to estimate wider eco- nomic effects from livestock disease and animal health ex- ternalities. Its scope is limited to terrestrial livestock and aquaculture and does not include companion animals or wildlife. Finally, its primary focus is on economic surplus and not cost-effective analysis with DALYs. While not addressed in this article, the topic of adaptation through adjustments in ecological, social or economic sys- tems in response to actual or expected shocks is a critical next step in GBADs or other economic assessments. In this light, and in addition to the above discussion of past re- search, intertemporal economic equilibrium models that in- tegrate population dynamics, and in which economic agents adjust to historical outcomes, will need past and current pop- ulation parameters and estimates and/or forecasts of them, as well as assumptions about future changes in technology and preferences [10,24-26]. These models provide short- and long-term outcomes for both economic surplus and the intertemporal redistribution of that surplus to firms and con- sumers. Moreover, intertemporal econometric models, such as those introduced by Barratt et al. [55] and Rahman and Marsh [56], demonstrate statistical approaches to provide data-driven estimates of loss and costs in data-challenged environments. That said, the discussion above provides the basic insights into the data and information required in con- structing specific counterfactual scenarios to quantify wider economic effects. There are additional issues and gaps in the literature on assessing wider economic burden, including framing, specification, stress and mental health, structural change, redistribution, forecasting and interpretation. A selective discussion on non-market impacts and WTP, COI and other issues is provided below, followed by suggestions for future directions. Non-market impacts Non-market impacts include social costs to the environ- ment or culture [7,57]. They could also include expected private costs of vaccines under development but not yet on the market [58]. Estimation of such costs or, for example, option value and other non-use values may require complex primary data collection and analysis methods. These meth- ods can include choice experiments (e.g. WTP ensuring breed continuation) or contingent valuation [57,58]. The choice of experimental design and analysis also depends on the specific research question and context, as well as the data units and platforms available for collection [59]. WTP has been used to assess drivers of vaccination preferences and vaccine adoption for a low-value livestock resource, poultry [60-62]. Cost of illness To place a value on morbidity, two approaches are gener- ally used: COI and WTP [2,19]. The most commonly used approach, COI, is calculated by summing up the direct medical expenses (e.g. expense of doctor’s office visit) in- curred by individuals and the indirect expenses related to productivity. Although the COI approach is commonly used, it has several shortcomings. Firstly, most COI studies use ex post data to calculate expenses. If those data are not available, then it is impossible to use COI data to calculate the expenses. Secondly, costs associated with pain and suffering are ignored. For most individuals willing to pay some amount to avoid symptoms, the COI approach likely under-estimates the true cost of morbidity. As an example of this approach, Rahman [29] has applied WTP and COI to assess zoonotic diseases. Looking forward As noted above, large data gaps persist regarding animal populations, as well as mortalities and morbidities of ani- mal populations, worldwide. Sourcing consistent quantity and price data series for many countries across the world also remains a critical problem [7]. In contrast to human health, there is limited information on public and private expenditures and investments in animal health across the world. In the private sector, such information is typically proprietary, often viewed as confidential and generally not shared. In the public sector, limited resources, low prior- ity or little political interest prevent an accurate and pre- cise accounting of these populations and expenditures. In all, continued effort on systematic data collection that is openly accessible, collaboration on that data collection, quality control of the data, standardisation of the data across countries, and leadership to do so are required. Programmes such as GBADs provide a vision and focal point to champion these efforts. Disease management is difficult given these gaps in the context of disease burdens [1]. Nevertheless, opportunities exist to close these gaps, including taking advantage of private–public data sharing, triangulating known datasets, and exploiting technologies to generate data, such as us- ing crowdsourcing or geographic information system tools to track herd movements. These efforts will require novel 65Scientific and Technical Review 43 2024 methods and analytical tools but will also ensure a bright fu- ture for empirical analysis and implementation of theoretical methods and hopefully, ultimately, for policy contributions. For example, new tools are being created to collect private and public expenditure data on animal disease outbreaks [63]. Hennessy and Marsh [2] point out the need for addi- tional work on issues of antibiotic resistance, gender, behav- ioural economics and institutional failure. There is also a critical nexus in animal health, climate change and the environment that is inextricably linked by key inputs and management of animal feed and nutrition [64]. Returning to Figure 2, the supply chain can be expanded upstream to include demand and supply of animal feed, which are trans- lated into nutrition. This is important because the level of nu- trition fed to an animal not only impacts animal health, but also impacts methane gas release into the environment from animal production. This illustrates an important production externality. Further examples include the impacts of drought shocks on pastures and croplands, which in turn impact feed and nutrition and then translate into animal health and cli- mate change outcomes. To mitigate these events, consistent policies are needed that cut across animal health, climate change and the environment, as is an understanding of the impacts of such policies. To assess impacts, data on losses and costs are needed. Financial instruments and mechanisms are becoming more important and more complicated in the agricultural sector. For example, indemnification often arises in animal culling, with the funding for it coming not only from governments, but also from levies collected from producers by govern- ments. Besides indemnification for livestock losses by gov- ernments, other financial mechanisms exist or are on the horizon. Firms may bear abatement costs when required to remove and/or reduce undesirable nuisances or negative by-products created during production, such as spillovers of agricultural waste into the environment or greenhouse gas emissions. Climate-smart programmes attempt to address the interlinked challenges of the food system and climate change by identifying incentives for producers to more fully participate in a sustainable manner. Again, to effectively as- sess the impacts of these programmes, data on losses and costs are needed. The final point relates to institutional failure, wherein gov- ernments themselves face the risk of failure as they are resource constrained, lack incentives, have imperfect or incomplete information and are vulnerable to regulatory capture [65]. Government failure arises where government intervention creates inefficiency and leads to a misallo- cation of scarce resources. Such failure also includes not collecting relevant data and not publicly reporting it. In the future, constraints, costs of externalities (e.g. the environ- ment and climate change), alternative scenarios and adap- tation need to be recognised in assessment and forecasting of the burden of disease. Les pertes de production et les coûts liés à la santé animale dans les estimations du fardeau économique des maladies animales T.L. Marsh, D. Pendell, P. Schrobback, G. Shakil & P. Tozer Résumé Cet article examine les pertes de production et les coûts associés (ou non) à la santé animale ainsi que les externalités liées aux maladies animales, dans le but d’estimer le fardeau pour l’ensemble de l’économie. L’examen se limite à la production d’animaux terrestres et aquatiques, secteurs où le fardeau économique est principalement déterminé par les forces du marché. Les pertes et les coûts sont répartis en pertes et coûts directs et indirects, ainsi qu’en coûts ex post et ex ante. Ces coûts comprennent non seulement les dépenses privées, mais aussi les dépenses publiques liées à la prévention, au traitement et aux réponses aux maladies des animaux d’élevage. Il s’agit d’une distinction impor- tante car l’une des fonctions premières d’un gouvernement est d’atténuer les externalités. Les auteurs examinent en- suite les impacts sur les marchés et les investissements. Pour conclure, à partir d’exemples choisis et d’observations illustrant leur propos, les auteurs proposent des voies d’exploration pour la recherche et ses applications. Mots-clés Animal – Coûts – Dépenses – Externalités – Fardeau – Humain – Maladies – Marchés – Pertes – Santé. 66Scientific and Technical Review 43 2024 Pérdidas de producción y costos de sanidad animal en la evaluación del impacto económico de las enfermedades animales T.L. Marsh, D. Pendell, P. Schrobback, G. Shakil & P. Tozer Resumen Este artículo se centra en determinar las pérdidas de producción y los costos (o la ausencia de ellos) asociados con las externalidades de la sanidad del ganado y las enfermedades animales, con el objetivo de estimar su impacto en toda la economía. El ámbito del artículo se limita a la ganadería terrestre y la acuicultura, donde el impacto económico está principalmente determinado por las fuerzas del mercado. Las pérdidas y los costos se clasifican en pérdidas y costos directos e indirectos, así como en costos ex post y ex ante. Dichos costos incluyen no solo los gastos privados, sino también los gastos públicos relacionados con la prevención y el tratamiento de las enfermedades del ganado y la respuesta ante estas, una distinción que es importante habida cuenta de que una de las principales funciones del gobierno es mitigar las externalidades. 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