# Performing Economic Evaluations of Veterinary Interventions


## Key Takeaways

- Economic evaluation in veterinary medicine quantifies the comparative costs and consequences of alternative interventions (preventive, therapeutic, diagnostic) to determine value for money, applicable across companion animals, livestock, and public health programs.
- The choice of analytical technique: Cost-Effectiveness Analysis (CEA), Cost-Utility Analysis (CUA), or Cost-Benefit Analysis (CBA), is dictated by the outcome type and decision context, with CEA for natural units (e.g., cases prevented), CUA for quality-adjusted outcomes (e.g., animal welfare), and CBA for monetary valuation across diverse outcomes.
- The perspective adopted (societal, payer, producer, clinic) critically influences which costs and consequences are counted, potentially altering conclusions; for instance, a producer perspective might favor an intervention that a societal perspective deems unfavorable due to external costs like antimicrobial resistance.
- Robust economic evaluations require a clearly defined comparator reflecting actual practice, an appropriate time horizon to capture all relevant costs and outcomes, and explicit consideration of uncertainty through sensitivity analysis rather than relying on single point estimates.
- Reporting adherence to standards like the CHEERS statement is crucial for transparency and appraisal, ensuring readers can reconstruct the analysis; common failure modes include mismatching the evaluation question with the method, omitting a comparator, conflating financial with economic costs, and inappropriate discounting.
- Transferability of results across geographic areas or production systems is limited by differences in resource prices (e.g., labor rates, drug prices), disease dynamics (e.g., parasite prevalence, herd immunity), and regulatory environments, necessitating local parameterization and validation.

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Economic evaluation in veterinary medicine is the comparative analysis of the costs and consequences of alternative interventions, whether those interventions are preventive, therapeutic, or diagnostic. This article provides a procedural framework for veterinary researchers who design, conduct, or appraise such evaluations across species and production systems. It answers the question of how to structure a study so that its results are credible, transferable, and useful for decision makers, whether those decisions concern individual patients, herd health, or national disease control policy.

The methods described here apply to companion animal practice, livestock production medicine, and public health programs that involve animal populations. The reader is assumed to be familiar with clinical trial design and biostatistics but not necessarily with health economics terminology. The article covers the conceptual foundations of economic evaluation, the principal analytical techniques, the measurement and valuation of costs and outcomes, and the reporting standards that govern publication. It does not address human health economics except where human health outcomes are integral to a veterinary intervention, as occurs in zoonosis control.

Economic evaluation is distinct from simple cost accounting. A cost description records what an intervention costs. An economic evaluation compares those costs with the consequences of the intervention, and it does so in a way that permits a judgment about whether the intervention represents good value. The choice of analytical technique depends on the nature of the outcomes being measured and the decision context in which the results will be used.

## At a Glance

| Parameter | Decision or Fact |
|---|---|
| Primary question | Does the intervention produce benefits worth its costs compared with a relevant alternative? |
| Analytical technique | Cost-effectiveness analysis, cost-utility analysis, or cost-benefit analysis, selected by outcome type |
| Perspective | Determines which costs and consequences are counted, societal, payer, producer, or clinic perspective |
| Time horizon | Must be long enough to capture all relevant costs and outcomes, including delayed effects |
| Comparator | Must reflect actual practice, not an artificial or no-treatment baseline |
| Outcome measure | Natural units for cost-effectiveness, quality-adjusted life years or similar for cost-utility, monetary value for cost-benefit |
| Discounting | Applied to future costs and outcomes when the time horizon exceeds one year |
| Uncertainty | Addressed through sensitivity analysis, not by presenting a single point estimate |
| Reporting standard | CHEERS statement for economic evaluations, ARRIVE for animal studies |

## The Logic of Comparative Evaluation

Every economic evaluation answers a comparative question. An intervention is never valuable or cost-effective in isolation. It is valuable relative to the next best alternative use of the same resources. The comparator may be current standard practice, a less expensive intervention, a more intensive intervention, or no intervention at all. The choice of comparator is the single most consequential decision in study design, because it determines the incremental cost and the incremental effect that form the basis of the analysis.

The analytical framework rests on the concept of opportunity cost. Resources used for one intervention are unavailable for other purposes. A veterinary practice that invests in a new diagnostic imaging system cannot spend those funds on vaccination outreach. A national program that funds compulsory testing for one disease reduces the budget available for surveillance of another. Economic evaluation makes these trade-offs explicit by quantifying both sides of the exchange.

The incremental nature of the analysis deserves emphasis. A study that reports only the total cost of a program, or only the total number of cases averted, has not performed an economic evaluation. The evaluation must compare the additional cost of one intervention over another with the additional benefit obtained. This incremental ratio, expressed as cost per unit of outcome, is the core result of most veterinary economic evaluations.

## Perspectives and Their Consequences

The perspective of an evaluation determines which costs and consequences are counted. A societal perspective counts all costs and all benefits, regardless of who bears them. A producer perspective counts only the costs and revenues that affect the farm enterprise. A clinic perspective counts the costs incurred by the practice and the revenue it receives. A payer perspective, common in public health evaluations, counts the costs borne by the funding agency.

The choice of perspective can change the conclusion of an evaluation. An intervention that appears cost-effective from a producer perspective may appear unfavourable from a societal perspective if it imposes external costs, such as environmental contamination or increased antimicrobial resistance. Conversely, an intervention that is costly to the producer may be highly cost-effective from a societal perspective if it reduces zoonotic transmission to humans. The perspective must be stated explicitly and defended in the methods section of any evaluation.

For livestock production medicine, the producer perspective is the most common choice because the decision maker is the farm owner. For companion animal medicine, the relevant perspective is usually that of the owner or the clinic. For zoonotic disease control, the societal perspective is often appropriate because the benefits accrue across human and animal populations. The evaluation of surveillance systems illustrates this point, as such systems produce benefits that are diffuse and difficult to attribute to any single stakeholder.

## Selecting the Evaluation Method

The choice among cost-effectiveness analysis (CEA), cost-utility analysis (CUA), and cost-benefit analysis (CBA) depends on the intervention's primary outcome and the decision context. CEA expresses results as cost per natural unit of effect, such as cost per case prevented, cost per life-year gained, or cost per kilogram of weight gain. It is appropriate when a single, clinically meaningful outcome dominates the comparison and when stakeholders agree that the outcome matters. CEA cannot compare interventions with different outcome types, which limits its use across disparate disease categories.

CUA extends CEA by weighting outcomes for quality or utility, producing cost per quality-adjusted life year (QALY) or, in veterinary applications, cost per animal welfare-adjusted outcome. The method requires a validated utility instrument, which is rarely available for non-human species. Some veterinary researchers adapt human utility frameworks, but the validity of cross-species utility measurement remains contested. Use CUA only when welfare outcomes are the explicit decision criterion and when a species-appropriate utility instrument has been published and validated.

CBA converts all consequences into monetary terms and reports net benefit or a benefit-cost ratio. It is the only method that permits comparison across entirely different interventions, such as vaccination programs versus biosecurity infrastructure, because both costs and benefits share a common numeraire. CBA requires defensible monetary valuation of outcomes, including production losses, mortality, treatment costs, and, where relevant, zoonotic human cases. The valuation step introduces uncertainty, and sensitivity analysis becomes mandatory instead of optional.

Table 1 summarizes the selection criteria.

| Method | Outcome metric | Best suited to | Limitation |
|---|---|---|---|
| CEA | Cost per natural unit (cases prevented, kg gained) | Single-outcome comparisons within one disease or production system | Cannot compare across different outcome types |
| CUA | Cost per quality-adjusted outcome | Welfare-focused decisions with validated utility instruments | Utility measurement across species is poorly validated |
| CBA | Net monetary benefit or benefit-cost ratio | Cross-program resource allocation, policy appraisal | Requires credible monetary valuation of all consequences |

Production system changes the correct choice. In companion animal practice, owner willingness to pay and welfare outcomes often drive decisions, favouring CUA or CBA with stated preference valuation. In production animal medicine, output prices and input costs are observable, so CBA aligns with producer objectives. In public health-oriented veterinary programs, such as zoonosis control, the analysis must extend beyond the animal sector to include human health costs, and the perspective expands accordingly. The [evaluation of animal and public health surveillance systems](https://pubmed.ncbi.nlm.nih.gov/22074638/) shows that comprehensive assessments addressing multiple attributes are uncommon, and the choice of attributes is often disconnected from stated objectives. The same failure mode applies to economic evaluations: the method must follow the decision question, not the convenience of available data.

## Building the Cost Side

Cost identification begins with a clear definition of the intervention pathway. Enumerate every resource consumed from the point of decision through completion of the intervention and its follow-up period. Standard cost categories include veterinary labor, consumables, pharmaceuticals, diagnostic testing, facility use, animal handling, and owner or producer time. In production systems, include opportunity costs of labor diverted from other tasks and the value of production lost during treatment or withdrawal periods.

Measure resource use in natural units first, then apply unit prices. This separation protects the analysis from price volatility and permits transferability of resource-use data across regions. Unit prices should reflect the perspective of the analysis. A producer perspective uses market prices paid. A societal perspective uses opportunity costs, which may differ from market prices when subsidies, taxes, or distorted markets exist. The [transferability of economic evaluation data across geographic areas](https://pubmed.ncbi.nlm.nih.gov/17407623/) depends on separating resource use from unit prices, because resource use transfers more readily than prices. Cost categories that transfer poorly include labor rates, drug prices, and facility overheads.

Discounting applies when costs or benefits extend beyond one year. Veterinary interventions with multi-year horizons include vaccination programs, breeding programs, and control campaigns for chronic or endemic disease. Discount both costs and benefits at the same rate, and test the discount rate in sensitivity analysis. The choice of discount rate materially changes the ranking of programs with different time profiles, so report the rate explicitly and justify it with reference to regional norms.

## Constructing the Outcome Side

Outcome measurement must match the method selected. For CEA, define the outcome with an unambiguous numerator and denominator. Cases prevented requires a counterfactual incidence estimate from a control group or a modelled baseline. Kilograms of weight gain requires a defined production period and a standardized weighing protocol. For CBA, convert outcomes to monetary terms using market prices where they exist, and stated preference or revealed preference methods where they do not.

Production losses in livestock frequently dominate the benefit side. Parasitic disease provides a worked example: the [systematic review of economic losses from cattle parasites](https://pubmed.ncbi.nlm.nih.gov/30068403/) reports average reductions in milk production of 1.16 L per animal per day and average financial losses of US$50.67 per animal per year across parasitic infections. These figures illustrate the scale of avoidable loss, but they also demonstrate the need for local parameterisation. Herd-level prevalence, production system, and management intensity shift both the loss and the intervention cost.

Zoonotic disease requires a broader outcome boundary. The [socio-economic assessment of echinococcosis](https://pubmed.ncbi.nlm.nih.gov/19575305/) shows that consequences in humans, including treatment costs and lost productivity, can exceed livestock losses, and that many consequences resist monetary valuation. When human health outcomes enter the analysis, the veterinary evaluation must either adopt a societal perspective or clearly state the excluded human costs and their likely direction of bias.

## Worked Example: Endemic Parasite Control in Dairy Cattle

Consider a dairy herd with endemic gastrointestinal nematodosis, where the decision is whether to implement a targeted selective treatment protocol against the current whole-herd schedule. The analysis adopts a producer perspective over one production year.

Cost side: enumerate anthelmintic product costs per treated animal, veterinary labor for fecal egg count sampling and interpretation, handling time per animal, and any milk withdrawal losses. The targeted protocol reduces product and labor costs but adds diagnostic costs. Resource use data come from the practice's own records or published benchmarks.

Outcome side: the primary outcome is milk production retained, measured as the difference in milk yield between protocols. Secondary outcomes include clinical disease cases averted and mortality. Convert retained milk to monetary value using the farm's milk price. Include the value of reduced anthelmintic resistance risk only if the analysis can quantify it, otherwise state it as a qualitative benefit.

The analysis produces three metrics: incremental cost per liter of milk retained (CEA), net benefit in currency units (CBA), and, if a welfare instrument exists, cost per welfare-adjusted outcome (CUA). The CEA result is compared against the producer's willingness to pay for retained production. The CBA result is compared against zero. The CUA result is compared against published thresholds, which are scarce in veterinary medicine.

Sensitivity analysis tests the parameters with the greatest uncertainty: milk price, prevalence of resistant nematodes, diagnostic test sensitivity, and the production loss per infected animal. One-way sensitivity analysis varies each parameter across a plausible range. Scenario analysis tests the extremes of low and high challenge seasons. The [risk of bias assessment literature](https://pubmed.ncbi.nlm.nih.gov/32111253/) identifies health economic evaluation as a distinct study type requiring its own appraisal tool, and the same discipline applies to the modeling assumptions in sensitivity analysis.

## Reporting and Appraisal

Report the evaluation against a recognized reporting standard. The [Consolidated Health Economic Evaluation Reporting Standards (CHEERS)](https://pubmed.ncbi.nlm.nih.gov/30310289/) checklist, maintained within the [EQUATOR Network library of reporting guidelines](https://www.equator-network.org/), specifies the minimum items for transparent reporting, including perspective, time horizon, discount rate, and sensitivity analysis. Adherence to reporting guidelines in the medical literature remains incomplete despite decades of availability, and veterinary economic evaluations face the same risk. A reader should be able to reconstruct the analysis from the report alone.

Appraise the completed evaluation for methodological quality before using its results. Key appraisal questions include whether the comparator reflects current practice, whether all relevant costs and outcomes were identified and measured credibly, whether discounting was applied correctly, and whether sensitivity analysis covered the parameters that materially change the conclusion. The [methodological quality assessment tools review](https://pubmed.ncbi.nlm.nih.gov/32111253/) lists health economic evaluation among the study types with dedicated appraisal instruments, and veterinary researchers should select the appropriate tool before interpreting results.

Species and production system determine the transferability of any published evaluation. A dairy herd evaluation in a pasture-based system does not transfer to a housed system with different feed costs and disease dynamics. The [geographic transferability literature](https://pubmed.ncbi.nlm.nih.gov/17407623/) distinguishes factors that transfer readily, such as biological parameters, from those that do not, such as labor costs and drug prices. When adapting a published evaluation, re-estimate all price-dependent parameters and validate biological parameters against local data.

## Recognized Complications and Failure Modes

Economic evaluations fail in predictable ways, and most failures are detectable before results are reported. The most common complication is a mismatch between the evaluation question and the chosen method. A cost-effectiveness analysis that reports a single incremental cost-effectiveness ratio for a disease with multiple clinical endpoints will mislead decision makers who care about those endpoints. Detect this early by returning to the stated objective and asking whether the outcome measure captures what the stakeholder actually values.

A second failure mode is the omission of a comparator. Evaluations that report only the cost of an intervention, without a baseline or alternative strategy, cannot support a comparative judgment. The discriminating check is simple: if the analysis cannot answer "compared with what?", the design is incomplete.

A third complication is the conflation of financial cost with economic cost. Financial costs are accounting entries. Economic costs include opportunity costs, which are the value of the best alternative use of the same resources. When a veterinary practice uses a treatment room for a herd health consultation, the economic cost includes the foregone surgical procedure that could have occupied that room. Evaluations that ignore opportunity costs systematically understate the true resource burden.

A fourth failure mode is the use of inappropriate discounting. Costs and benefits that occur in different time periods must be discounted to present value. Failure to discount, or use of inconsistent discount rates, distorts comparisons between interventions with different cost and benefit timelines. This is particularly relevant for control programs where costs are front-loaded and benefits accrue over years, as seen in evaluations of echinococcosis control where the economic case depends heavily on the time horizon chosen.

## Common Errors and Corrective Actions

Less experienced analysts frequently make errors in three areas: outcome measurement, cost attribution, and uncertainty handling.

In outcome measurement, the most common error is using a surrogate outcome when a final outcome is available. Milk production loss is a legitimate outcome in dairy parasite control, but it is a surrogate for the broader production system impact. The corrective action is to specify the decision context first and select outcomes that match the stakeholder's objective. Reviews of parasite-associated economic losses in cattle show that production losses, mortality costs, and control costs are frequently reported separately, which makes aggregation difficult and invites double counting.

In cost attribution, the typical error is assigning fixed costs to a single intervention when those costs are shared across multiple activities. Laboratory equipment, vehicle use, and personnel time are often shared. The corrective action is to use a transparent allocation rule, such as time-motion data or activity-based costing, and to state the rule explicitly in the methods.

In uncertainty handling, the common error is presenting a single point estimate without sensitivity analysis. The corrective action is to vary the key parameters across plausible ranges and report how the conclusion changes. If the conclusion is robust across the range, the evaluation is stable. If it flips, the decision maker needs to know which parameter drives the result.

## Limitations of the Current Evidence

The veterinary economic evaluation evidence base is thinner than the human health equivalent. Several structural reasons explain this. First, veterinary interventions often produce multiple outputs, including animal health, production, welfare, and public health benefits, and no single outcome measure captures all of them. Second, data on the full cost of disease are frequently incomplete. Surveillance system evaluations, for example, often address only one or two system attributes, and comprehensive evaluations are uncommon, which limits the generalizability of their economic findings.

Third, transferability of results across regions is a recognized problem. Resource prices, production systems, disease prevalence, and regulatory environments differ substantially between jurisdictions. Approaches to geographic transferability exist, but they require explicit adjustment of both cost and effect parameters, and the adjustments themselves carry uncertainty.

Expert opinion still differs on several points. One is whether to include animal welfare as an outcome in economic evaluations. Some analysts argue that welfare is a production input, others that it is a final outcome, and the choice changes the analysis structure. Another point of difference is the appropriate perspective for companion animal evaluations, where owner willingness to pay may exceed the societal value assigned to the animal's life. A third area of disagreement is the handling of zoonotic disease externalities, where the veterinary intervention produces human health benefits that fall outside the animal health budget.

## Referral, Consultation, and Regulatory Reporting

Most economic evaluations do not require regulatory reporting, but some circumstances do trigger external involvement. When an evaluation informs a claim about product efficacy or cost performance that will be used in marketing, regulatory oversight may apply. When the evaluation involves a notifiable disease, the underlying surveillance data must be reported through the appropriate animal health authority, and the evaluation should be designed to accommodate that reporting pathway.

Specialist consultation is warranted when the evaluation requires advanced statistical methods, such as probabilistic sensitivity analysis or value-of-information analysis, that the primary analyst cannot execute reliably. Consultation is also appropriate when the evaluation crosses species or production system boundaries and the analyst lacks domain knowledge in one of the systems.

Laboratory involvement is indicated when the evaluation depends on diagnostic test performance data. The accuracy of the diagnostic test directly affects the cost-effectiveness conclusion, and the test characteriztics must be sourced from validated studies instead of assumed. Reporting standards for diagnostic accuracy studies exist precisely because poor reporting of test performance is common. The analyst should verify that the diagnostic performance data come from a study that meets current reporting expectations before using those data in the model.

| Observation | Likely Cause | Discriminating Check |
|---|---|---|
| Single cost-effectiveness ratio reported for multiple outcomes | Outcome measure mismatch | Re-read the objective, confirm the outcome matches the stakeholder's decision |
| No comparator in the analysis | Design omission | Ask "compared with what?", if unanswered, redesign |
| Costs understated relative to practice experience | Opportunity costs ignored | Audit the cost list for shared resources and foregone alternatives |
| Conclusion changes when discount rate varies | Discounting error or time horizon sensitivity | Run sensitivity analysis on discount rate and horizon |
| Results not applicable to another region | Transferability failure | Compare resource prices, prevalence, and production systems |
| Diagnostic cost data inconsistent with clinical reality | Test performance data from low-quality source | Verify the source study meets reporting standards |

When the evaluation informs a policy decision with public health implications, such as zoonotic disease control, consultation with public health economists is advisable. The social consequences of zoonoses extend beyond the veterinary sector, and an evaluation that ignores those consequences will understate the value of control. The decision to escalate should be made early, because retrofitting a missing perspective or an additional outcome domain is substantially more costly than building it into the design from the outset.

## Frequently Asked Questions

### How do I choose between cost-effectiveness analysis and cost-benefit analysis when I have limited time and resources?

Select the method that matches the decision you must defend. Cost-effectiveness analysis suits clinical comparisons where the outcome, such as cases prevented or life-years gained, is shared across interventions. Cost-benefit analysis suits decisions requiring a single monetary figure, such as justifying a herd health program to a farm owner. When resources are tight, cost-effectiveness analysis is usually simpler because it avoids monetising animal welfare and production outcomes. If you must compare interventions with different outcome types, cost-benefit analysis becomes necessary. Whichever method you choose, report the perspective, time horizon, and discount rate explicitly, since these determine whether the result transfers to another setting. Transferability depends heavily on local cost structures and production systems.

### What do I do when the ideal data for my evaluation are unavailable or of poor quality?

Use the best available data and state the limitations plainly. Production records, treatment logs, and slaughterhouse data often substitute for controlled trial outcomes. When published effect sizes are missing, model the intervention across a plausible range of values using sensitivity analysis. This approach shows whether the conclusion holds despite uncertainty. For costs, local prices and veterinary fee schedules are preferable to published figures from other regions, because geographic transferability of economic data is frequently poor. If you rely on expert opinion, name the experts and the basis for their estimates. Report your assumptions in enough detail that another analyst could reproduce the model. The Consolidated Health Economic Evaluation Reporting Standards checklist provides a practical structure for documenting data sources and analytical choices.

### How does the economic evaluation change when I move from dairy cattle to companion animals?

The perspective and outcome measures shift substantially. In production animals, outcomes are typically monetised through milk yield, weight gain, mortality, and treatment costs, as demonstrated in economic loss models for parasitic disease in cattle. In companion animals, the owner is both the payer and the beneficiary of improved welfare, so willingness to pay and quality-of-life measures become relevant. Cost-effectiveness analysis using clinical outcomes such as survival time or remission duration is common. Cost-benefit analysis in companion animals requires assigning monetary value to outcomes owners may not price directly, which introduces methodological controversy. The analytical framework remains the same, but the cost side must capture species-specific diagnostics, hospitalization, and aftercare, and the outcome side must reflect the owner's decision context instead of herd productivity.

### What records should I keep during an intervention to support a later economic evaluation?

Maintain itemised records of every resource consumed, including drugs, consumables, staff time, diagnostic tests, and facility use. Record the date and quantity for each input, and note whether costs were fixed or variable. For production animals, capture production data such as milk yield, weight gain, feed intake, and mortality at defined intervals. For companion animals, record the number and type of revisits, complications, and duration of treatment. Keep a log of any deviations from the planned protocol, since these affect both costs and outcomes. Surveillance evaluations are strengthened when objectives are stated in advance and the attributes to be measured are linked to those objectives. Consistent record keeping also supports reporting guideline compliance, which remains incomplete across much of the medical and veterinary literature.

### How should I explain the economic evaluation to a farm owner or client who wants a simple answer?

Lead with the decision, not the method. State the expected outcome in practical terms, such as cases prevented per year or expected change in production, then give the cost per unit of that outcome. If you used cost-benefit analysis, present the net benefit or benefit-cost ratio as a single figure. Explain that the estimate depends on assumptions about disease pressure, prices, and response to treatment, and that you tested these assumptions. Offer a range instead of a single point estimate when uncertainty is material. Avoid technical terms such as incremental cost-effectiveness ratio unless the client asks. The goal is to support an informed decision, not to present a complete economic model. For zoonotic diseases, note that benefits may extend beyond the farm to public health, which can justify shared funding.

### When should I seek specialist help for an economic evaluation instead of conducting it myself?

Seek specialist input when the decision involves large capital expenditure, regulatory approval, or public funding, and when the consequences of a wrong conclusion are substantial. Evaluations of disease control programs with public health implications, such as echinococcosis control, require expertise in both veterinary and human health economics. Specialist help is also warranted when you need advanced methods such as stochastic modeling, value-of-information analysis, or complex sensitivity analysis. If you are publishing the evaluation, involve an economist early so the study design supports the analytical approach. Methodological quality assessment tools for health economic evaluations differ from those used for clinical trials, and an experienced reviewer can help you select the appropriate framework. For routine clinical or herd-level decisions, a transparent spreadsheet model with clearly stated assumptions is usually sufficient.

## Related Clinical & Scientific Guides

* [Conducting Systematic Reviews of Veterinary Diagnostic Test Accuracy](/knowledge/veterinary-medicine/veterinary-research-methods/conducting-systematic-reviews-veterinary-diagnostic-test-accuracy)
* [Bias in Veterinary Research: Types, Sources, and Mitigation](/knowledge/veterinary-medicine/veterinary-research-methods/bias-veterinary-research-types-sources-mitigation)
* [Cluster Randomized Trials in Veterinary Research: Design and Analysis](/knowledge/veterinary-medicine/veterinary-research-methods/cluster-randomized-trials-veterinary-research-design-analysis)


## References and Further Reading

- [Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better?](https://pubmed.ncbi.nlm.nih.gov/32111253/). 2020.
- [Does the medical literature remain inadequately described despite having reporting guidelines for 21 years? - A systematic review of reviews: an update.](https://pubmed.ncbi.nlm.nih.gov/30310289/). 2018.
- [Transferability of economic evaluations: approaches and factors to consider when using results from one geographic area for another.](https://pubmed.ncbi.nlm.nih.gov/17407623/). 2007.
- [Evaluation of animal and public health surveillance systems: a systematic review.](https://pubmed.ncbi.nlm.nih.gov/22074638/). 2012.
- [A systematic review on modeling approaches for economic losses studies caused by parasites and their associated diseases in cattle.](https://pubmed.ncbi.nlm.nih.gov/30068403/). 2019.
- [Echinococcosis: costs, losses and social consequences of a neglected zoonosis.](https://pubmed.ncbi.nlm.nih.gov/19575305/). 2009.
- [ARRIVE Guidelines 2.0 for Reporting Animal Research](https://arriveguidelines.org/). PLOS Biology, 2020.
- [EQUATOR Network Reporting Guidelines](https://www.equator-network.org/). EQUATOR Network.
- [MSD Veterinary Manual, Professional Edition](https://www.msdvetmanual.com/). MSD Veterinary Manual.

## Related Articles

- [Conducting Systematic Reviews of Veterinary Therapeutic Interventions](/knowledge/veterinary-medicine/veterinary-research-methods/conducting-systematic-reviews-veterinary-therapeutic-interventions)
- [Applying Competing Risks Analysis in Veterinary Research](/knowledge/veterinary-medicine/veterinary-research-methods/applying-competing-risks-analysis-veterinary-research)
- [Appraising Diagnostic Accuracy Studies in Veterinary Medicine](/knowledge/veterinary-medicine/veterinary-research-methods/appraising-diagnostic-accuracy-studies-veterinary-medicine)
- [The ARRIVE Guidelines for Animal Research: Implementation and Compliance](/knowledge/veterinary-medicine/veterinary-research-methods/arrive-guidelines-animal-research-implementation-compliance)
- [Assessing Risk of Bias in Veterinary Randomized Trials](/knowledge/veterinary-medicine/veterinary-research-methods/assessing-risk-bias-veterinary-randomized-trials)

> This article is educational professional reference material for veterinary audiences. It is not a substitute for veterinary diagnosis, individual clinical judgment, current product labeling, or applicable regulatory requirements.