Dairy cows in field

A long life in good health is the obvious ideal for humans. A productive life in good health is the equivalent target for dairy cattle.  

Over the past decades there has been an increasing awareness of the detrimental impact on profitability and welfare due to levels of dairy cow mortality in the U.S. and abroad.  Similarly, the consequences of forced or biological culling of dairy cows due to ill health and injury have highlighted the importance of animal well-being and associated economic opportunity costs.  Underlying these issues are the health and welfare implications of conditions such as lameness and mastitis with the potential to decrease production and cause pain and suffering.  Such costly diseases or injuries pose an economic problem for farmers and raise the broader question of appropriate cow longevity in contemporary production.

Questions about the DairyLifetime program??
Contact Dr. Craig McConnelExtension Veterinariancmcconnel@wsu.edu or 509-335-0776.

From the cradle to the grave is an expression often used to capture the full spectrum of human life from birth to death.  It speaks to the process of living and existence as a whole.  Although dairy cattle do not begin life in a cradle or end in a grave, their existence is very much a function of a continuum of events defining the process of living.  In some cases that continuum of events includes diseases and injuries that eventuate in death; therefore, assessing end of life outcomes in dairy cows may be one of the most effective means for describing their existence.  Ultimately, understanding the timing and fates of animals that die on farms can be informative in the reflection of management conditions and production efficiencies, and provide a foundation for improved understanding of animal health and features of farm management that present risks of poor outcomes.

Research Abstracts

Invited Review: Why cows die in US dairy herds

McConnel C, Garry F. Appl Anim Sci. 2019; 35 (6): 596-605.

Purpose: Over the past several decades there has been an appreciable, persistent, and concerning rise in dairy cow mortality. The purpose of this review was to integrate epidemiological, pathophysiological, and historical perspectives to improve our understanding of why dairy cows die and what can be done about it.

Sources: Refereed scientific journal articles, USDA reports, and conference proceedings available in online databases were consulted in this review.

Synthesis: Explorations of causes of dairy cow death frequently have focused on associations between mortality and population characteristics, management, and environmental factors. These studies often suggest that intensification of the dairy industry may influence high on-farm dairy cattle mortality. Other studies have focused on pathophysiologic descriptions of specific deaths, alongside the utility of incorporating postmortem evaluations into on-farm management. Although it is most certainly useful to establish broad associations between population characteristics or specific disease entities and higher death rates, mitigation strategies must be based on an understanding of why those associations or diseases are present in the first place.

Conclusion and Applications: A multitude of factors and complexities act in concert to influence why cows die in US dairy herds. Understanding differences related to why cows die requires insight into the impacts of environment, operational practices, economic concerns, and animal interactions on overall performance. Although there are practical suggestions for addressing dairy cow mortality such as incorporating postmortem examinations and standardized nomenclature, questioning why dairy cows die is part of a larger discussion regarding the welfare of animals in modern agricultural systems.

Clarifying dairy calf mortality phenotypes through postmortem analysis

McConnel CS, Nelson DD, Miller CB, Buhrig SM, Wilson EA, Klatt CT, Moore DA. J Dairy Sci. 2019. 102 (5): 4415-4426. 

Health problems can be thought of as phenotypic expressions of the complex relationships between genes, environments, and phenomes as a whole. Detailed evaluations of phenotypic expressions of illness are required to characterize important biological outcomes. We hypothesized that classifying dairy calf mortality phenotypes via a systematic postmortem analysis would identify different cause-of-death diagnoses than those derived from treatments alone. This cross-sectional study was carried out on a dairy calf ranch in the northwestern United States from June to September 2017 and focused on calves ≤90 d of age. Comparisons were made between causes of death based on 3 levels of information: on-farm treatment records alone, necropsy-based postmortem analyses in addition to treatment records, and Washington Animal Disease Diagnostic Laboratory (WADDL) results in addition to all other information. A total of 210 dairy calves were necropsied during this study, of which 122 cases were submitted to WADDL. Necropsy- and WADDL-derived mortality phenotypes were in almost perfect agreement (Cohen’s κ = 0.86) when broadly categorized as diarrhea, respiratory, diarrhea and respiratory combined, or other causes. The level of agreement between on-farm treatment records and postmortem-derived results was low and varied by the level of diagnostic detail provided. There was just fair agreement (κ = 0.22) between treatment-based and necropsy-based phenotypes without WADDL input and only slight agreement (κ = 0.13) between treatment-based and corresponding necropsy-based phenotypes with WADDL input. Even for those cases in which causes of death aligned along a comparable pathologic spectrum, the lack of detail inherent to standard treatment-based causes of death failed to identify meaningful target areas for intervention. This was especially apparent for numerous cases of necrotizing enteritis and typhlitis (cecal inflammation) that were variously categorized as diarrhea and pneumonia by treatment-based diagnoses. The specificity of these lesions stood in stark contrast to the otherwise generic cause of death diagnoses derived from treatments. The findings from this study supported the hypothesis and highlighted the value of on-farm necropsies and laboratory-based diagnostics to (1) detect antemortem disease misclassifications, (2) provide detail regarding disease processes and mortality phenotypes, and (3) direct disease mitigation strategies.

Dairy cow mortality data management:  the dairy certificate of death

McConnel CS, Garry FB. Bov. Pract. 2017; 51 (1): 64-72.

On-farm cow mortality is a significant problem for North American dairies. Analysis of causes of death should provide important information about outcomes of current management, and direction for management changes required to improve cow health, production, and well-being. Currently available information about mortality losses is not useful for making appropriate changes because information gathering and storage are inadequate for that purpose. Here we propose and analyze the use of a dairy cow death certificate that provides an information gathering tool intended to improve analysis and communication about outcomes of dairy management.

Herd factors associated with dairy cow mortality

McConnel C, Lombard J, Wagner B, Kopral C, Garry F. Animal. 2015; 9 (8): 1397-1403.

Summary studies of dairy cow removal indicate increasing levels of mortality over the past several decades. This poses a serious problem for the US dairy industry. The objective of this project was to evaluate associations between facilities, herd management practices, disease occurrence and death rates on US dairy operations through an analysis of the National Animal Health Monitoring System’s Dairy 2007 survey. The survey included farms in 17 states that represented 79.5% of US dairy operations and 82.5% of the US dairy cow population. During the first phase of the study operations were randomly selected from a sampling list maintained by the National Agricultural Statistics Service. Only farms that participated in phase I and had 30 or more dairy cows were eligible to participate in phase II. In total, 459 farms had complete data for all selected variables and were included in this analysis.  Univariable associations between dairy cow mortality and 162 a priori identified operation-level management practices or characteristics were evaluated. Sixty of the 162 management factors explored in the univariate analysis met initial screening criteria and were further evaluated in a multivariable model exploring more complex relationships. The final weighted, negative binomial regression model included six variables. Based on the incidence rate ratio, this model predicted 32.0% less mortality for operations that vaccinated heifers for at least one of the following: bovine viral diarrhea, infectious bovine rhinotracheitis, parainfluenza 3, bovine respiratory syncytial virus, Haemophilus somnus, leptospirosis, Salmonella, Escherichia coli or clostridia. The final multivariable model also predicted a 27.0% increase in mortality for operations from which a bulk tank milk sample tested ELISA positive for bovine leukosis virus. Additionally, an 18.0% higher mortality was predicted for operations that used necropsies to determine the cause of death for some proportion of dead dairy cows. The final model also predicted that increased proportions of dairy cows with clinical mastitis and infertility problems were associated with increased mortality. Finally, an increase in mortality was predicted to be associated with an increase in the proportion of lame or injured permanently removed dairy cows. In general terms, this model identified that mortality was associated with reproductive problems, non-infectious postpartum disease, infectious disease and infectious disease prevention, and information derived from postmortem evaluations. Ultimately, addressing excessive mortality levels requires a concerted effort that recognizes and appropriately manages the numerous and diverse underlying risks.

Conceptual modeling of postmortem evaluation findings to describe dairy cow deaths

McConnel CS, Garry FB, Hill AE, Lombard JE, Gould DH.  J. Dairy Sci. 2010; 93 (1) 373-386.

Dairy cow mortality levels in the United States are excessive and increasing over time. To better define   cause and effect and combat rising mortality, clearer definitions of the reasons that cows die need to be acquired through thorough necropsy-based postmortem evaluations. The current study focused on organizing information generated from postmortem evaluations into a monitoring system that is based on the fundamentals of conceptual modeling and that will potentially be translatable into on-farm relational databases. This observational study was conducted on 3 high- producing, commercial dairies in northern Colorado.  Throughout the study period a thorough postmortem evaluation was performed by veterinarians on cows that died on each dairy.  Postmortem data included necropsy findings, life-history features (e.g., birth date, lactation number, lactational and reproductive status), clinical history and treatments, and pertinent aspects of operational management that were subject to change and   considered integral to the poor outcome.  During this study, 174 postmortem evaluations were performed.  Postmortem evaluation results were conceptually modeled to view each death within the context of the web   of factors influencing the dairy and the cow.  Categories were formulated describing mortality in terms of functional characteristics potentially amenable to easy   performance evaluation, management oversight, and research.  In total, 21 death categories with 7 category themes were created.  Themes included specific disease processes with variable etiologies, failure of disease recognition or treatment, traumatic events, multifactorial failures linked to transition or negative energy balance issues, problems with feed management, miscellaneous events not amenable to prevention or treatment, and undetermined causes. Although postmortem evaluations provide the relevant information necessary for framing a cow’s death, a restructuring of on-farm databases is needed to integrate this level of detail into useful monitoring systems.  Individual operations can focus on combating mortality through the use of employee training related to postmortem evaluations, detailed   forms for capturing necropsy particulars and other relevant information related to deaths, and standardized nomenclature and categorization schemes.  As much as anything, the simple act of recognizing mortality as a problem might be the most fundamental step toward controlling its progression.

A necropsy-based descriptive study of dairy cow deaths on a Colorado dairy

McConnel CS, Garry FB, Lombard JE, Kidd JA, Hill AE, Gould DH.  J. Dairy Sci. 2009; 92 (5) 1954-1962.

Increasing levels of dairy cow mortality pose a challenge to the US dairy industry. The industry’s current understanding of dairy cow mortality is reliant upon descriptions largely based on producer or veterinary assumptions regarding cause of death without the benefit of detailed postmortem evaluations. A thorough necropsy is a superior tool for establishing a cause of death, except for cases involving euthanasia for traumatic accidents or severe locomotor disorders. Information provided from a necropsy examination would be most valuable if it were categorized and combined with cow health information in a complete postmortem evaluation designed to guide future management decisions. The objective of this study was to describe dairy cow deaths on a Colorado dairy over a 1-yr period and explore classification systems for necropsy findings that might inform management actions aimed at reducing dairy cow mortality. Throughout the study period a thorough necropsy examination was performed on every cow that died. Based upon this examination each death was characterized by a proximate cause (i.e., the most likely immediate cause of the death). Each proximate cause of death was then categorized using 3 alternate schemes founded on generalized etiologic principles and influenced by previous clinical history and treatments. These schemes included the broad categories commonly used for classifying findings within a review of literature related to dairy cow mortality, a diagnostic scheme used within the problem-oriented veterinary medical record, and an analysis focusing on the primary physiologic system derangement for each death. A total of 2,067 cows were enrolled during the study period of which 1,468 cows freshened, 507 cows were sold, and 94 cows died, resulting in a mortality risk of 6.4 deaths per 100 lactations at risk. The distribution of deaths by parity was significantly different from the herd distribution at the end of study with the largest percentage of death present in parity > or =4. Postmortem findings attributable to a specific cause of death were present for all but 4 of the 94 deaths. Assignment of the proximate causes of death to categories within the 3 alternate schemes provided a means for classifying necropsy findings and causes of death with different levels of detail. Creating categories with more selective groupings may provide a means for capturing specifics related to deaths that can be used to guide management decisions.

Evaluation of factors associated with increased dairy cow mortality on United States dairy operations

McConnel CS, Lombard JE, Wagner BA, Garry FB.  . J. Dairy Sci. 2008; 91 (4) 1423-1432.

Dairy cow mortality is an increasingly severe problem for the US dairy industry. The objective of this study was to examine a variety of herd management practices and herd characteristics to identify factors associated with increased cow mortality in US dairy herds. The National Animal Health Monitoring System’s Dairy 2002 study surveyed dairy operations in 21 major dairy states. The complete data set included results from 953 dairy farms with a minimum of 30 dairy cows per farm. Associations between dairy cow mortality and 119 a priori-selected management practices or characteristics of 953 operations were evaluated. Eighty of the 119 risk factors explored in a univariate analysis met initial inclusion criteria for further evaluation of association with dairy cow mortality. A multivariable analysis was conducted to explore more complex relationships. The final multivariable model included 7 representative variables: herd levels of respiratory disease, lameness, and antibiotic use for treating sick cows, the percentage of culled cows less than 50 d in milk, the average calving interval, the use of a total mixed ration, and the region of the country. Increased odds of a greater level of mortality on farms was associated with greater percentages of lameness, respiratory disease, and sick cows treated with antibiotics, demonstrating the influence of physical derangements and disease on dairy cow mortality. Increased odds of a greater level of mortality was also associated with feeding a total mixed ration, culling fewer cows in early lactation, and herds located in western, midwestern, and southeastern regions relative to the northeastern United States, pointing to the importance of management decisions and operation characteristics on mortality outcomes. Further, an important interplay between facets of health and management on dairy cow mortality was suggested through the inclusion of the calving interval, with a longer calving interval leading to increased odds of a greater level of mortality on farms. Analysis of a variety of herd characteristics and practices with nationally representative data suggests that several health problems in tandem with aspects of operational construct and management are associated with increasing mortality.

Industry Publications

  • Garry, F. and McConnel, C. 2017. One for the record books. Hoard’s Dairyman. Feb. 10, 2017. Pg. 81.
  • Garry, F. and McConnel, C. 2017. Play Sherlock Holmes. Hoard’s Dairyman. Jan. 26, 2017. Pg. 45.
  • Garry, F. and McConnel, C. 2017. Cows don’t just die. Hoard’s Dairyman. Jan. 10, 2017. Pg. 9.


  1. Garry F, McConnel C.  Dairy cow death certificate: Why? Proceedings of the Western Dairy Management Conference, Reno, NV, USA, 28 February-2 March, 2017.
  2. Garry F, McConnel C.  Why cows die on dairy farms. Proceedings of the 22nd Tri-State Dairy Nutrition Conference, Fort Wayne, Indiana, USA, 23-24 April, 2013.
  3. Garry F, McConnel C.  Why cows die on dairies. Proceedings of the 45th Annual Conference of the American Association of Bovine Practitioners, Montreal, Canada, 20-22 September, 2012.

Management Tools

  1. Calf Necropsy Video Playlist
  2. Dairy cow mortality data management
  3. Dairy Cow Certificate of Death Colorado State University (pdf form)
  4. Dairy Calf Certificate of Death WSU (pdf form)
  5. Removal -Dead and Culled- Categorization Schemes (pdf form)

How do early life experiences impact later life outcomes in a dairy cow?  Attempting to assess the impact of the continuum of health events from birth through death or removal is a difficult proposition at best.  Comparisons across management systems is even more difficult.  This is particularly true when attempting to draw comparisons across farms with variable calf rearing strategies related to nutrition and housing.  Previous studies have investigated impacts of calfhood respiratory and digestive diseases on future productivity but have tended to focus solely on frequency measures of disease and are limited in their assessments of comorbidities.  A measure of the cumulative burden of disease from birth through culling or death would provide the necessary foundation for an assessment of the impact of calf management and health on dairy cow disease incidence, longevity, and overall well-being.

Current Research

Addressing the problem of dairy calf gastrointestinal disease through enhanced diagnostics, novel therapeutics, and practical education.

Supporting Agency: USDA-AFRI: Crosscutting Programs, Critical Agriculture Research and Extension. Award No. 2019-68008-29897.

Background: The goal for the U.S. food system is to provide access to affordable and nutritious food. For food animal production systems this means rearing healthy animals and managing input costs. Antibiotics are a tool often used to control health issues such as neonatal calf gastrointestinal (GI) disease, which remains one of the most problematic diseases in dairy calves. However, analytic accuracy of GI disease phenotypes and prudent use of antibiotics are hindered by limited diagnostics and few postmortem evaluations. This project’s objectives address these limitations by delineating dairy calf GI disease phenotypes, applying and evaluating fecal microbiota transplants (FMT) for the treatment of GI diseases as an alternative to antibiotic use, and generating and disseminating information regarding enhanced diagnostic and therapeutic options for neonatal dairy calf GI disease. Specifically, dairy calf GI disease gradients will be assessed based on modifications in fecal microbiotas, interleukin-6 levels, GI epithelial cell gene expression, and pathologic outcomes. The integration of these parameters will inform novel phenotypic classifications of GI disease and allow for the development and assessment of therapeutic FMT. The success of this study will be within the dissemination of applicable knowledge to relevant stakeholders including food animal practitioners. We will create and deliver an extension program addressing neonatal calf management, including diagnostic oversight, therapeutic alternatives to antibiotic use, and impacts of disease. These outcomes align with the mission of Crosscutting Program A1701 to support farm efficiency, profitability, and sustainability while mitigating constraints on food production.

Utilizing novel diagnostics to describe risk factors and impacts of Jersey calf gastrointestinal disease.

Supporting Agency: American Jersey Cattle Association Research Foundation.

Background: Neonatal calf gastrointestinal (GI) disease is one of the most problematic diseases in dairy calves. However, analytic accuracy of breed specific GI disease phenotypes is hindered by limited diagnostics and few postmortem evaluations. We recently conducted a project utilizing postmortem evaluations on a dairy calf ranch to clarify calf mortality phenotypes, and found that Jersey calf deaths were dramatically overrepresented by necrotizing, ulcerative enterocolitis and typhlitis. This findings aligned with previous research at Washington State University demonstrating that a specific microbiota may be associated with diarrhea in neonatal calves. The current project’s objective is to improve our understanding of neonatal Jersey calf GI disease phenotypes through enhanced diagnostics, including epigenetic and microbial community comparisons between healthy vs diarrheic calves. Specifically, dairy calf GI disease gradients will be assessed based on breed specific modifications in fecal microbiotas, interleukin-6 levels, GI epithelial cell gene expression, and pathologic outcomes. The integration of these parameters will inform novel phenotypic classifications of GI disease that can help navigate inherent differences in Jersey phenotypic responses to management inputs. The success of this study will be within the dissemination of applicable knowledge to relevant stakeholders including dairy producers and practitioners. We will create and deliver an extension program addressing neonatal calf management, including diagnostic oversight, therapeutic alternatives to antibiotic use, and impacts of disease particularly as they pertain to the management of Jersey calves.

Management Tools

Accounting for the burden of disease during a dairy cow’s lifetime requires practical assessments of disease and injuries, and consistent documentation of forced removal or death. Although modern population medicine has focused extensively on establishing genetic associations to understand phenotypes such as disease phenotypes and mortality, these associations tend to explain only a small proportion of phenotypic variance.  Detailed evaluations of phenotypic expressions of illness are required to characterize important biological outcomes including morbidity and mortality.  Summary measures of population health provide such evaluations by combining information on mortality and non-fatal health outcomes.  Such measures have a variety of uses such as comparisons of health across different populations, and assessments of the relative contributions of different diseases and injuries to the total disease burden of a population.

Research Abstracts

A comparison of a novel time-based summary measure of dairy cow health against cumulative disease frequency

McConnel CS, McNeil AA, Hadrich JC, Lombard JE, Heller J, Garry FB. Ir Vet J. 2018. 71 (7).

Background: There is an increasing push for dairy production to be scientifically grounded and ethically responsible in the oversight of animal health and well-being. Addressing underlying challenges affecting the quality and length of productive life necessitates novel assessment and accountability metrics. Human medical epidemiologists developed the Disability-Adjusted Life Year metric as a summary measure of health addressing the complementary nature of disease and death. The goal of this project was to develop and implement a dairy Disease-Adjusted Lactation (DALact) summary measure of health, as a comparison against cumulative disease frequency.

Methods: A total of 5694 cows were enrolled at freshening from January 1st, 2014 through May 26th, 2015 on 3 similarly managed U.S. Midwestern Plains’ region dairies. Eleven health categories of interest were tracked from enrollment until culling, death, or the study’s completion date. The DALact accounted for the days of life lost due to illness, forced removal, and death relative to the average lactation length across the participating farms.
Results: The DALact consistently identified mastitis as the primary disease of concern on all 3 dairies (19,007–23,955 days lost). Secondary issues included musculoskeletal injuries (19,559 days), pneumonia (11,034 days), or lameness (8858 days). By comparison, cumulative frequency measures pointed to mastitis (31–50%) and lameness (25–54%) as the 2 most frequent diseases. Notably, the DALact provided a robust accounting of health events such as musculoskeletal injuries (5010–19,559 days) and calving trauma (2952–5868 days) otherwise overlooked by frequency measures (0–3%).Conclusions: The DALact provides a time-based method for assessing the overall burden of disease on dairies. It is important to emphasize that a summary measure of dairy health goes beyond simply linking morbidity to culling and mortality in a standardized fashion. A summary measure speaks to the burden of disease on both the well-being and productivity of individuals and populations. When framed as lost days, years, or lactations the various health issues on a farm are more comprehensible than they may be by frequency measures alone. Such an alternative accounting of disease highlights the lost opportunity costs of production as well as the burden of disease on life as a whole.

Dairy cow disability weights

McConnel CS, McNeil AA, Hadrich JC, Lombard JE, Garry FB, Heller J. Prev Vet Med. 2017; 143: 1-10.

Over the past 175 years, data related to human disease and death have progressed to a summary measure of population health, the Disability-Adjusted Life Year (DALY). As dairies have intensified there has been no equivalent measure of the impact of disease on the productive life and well-being of animals. The development of a disease-adjusted metric requires a consistent set of disability weights that reflect the relative severity of important diseases. The objective of this study was to use an international survey of dairy authorities to derive disability weights for primary disease categories recorded on dairies. National and international dairy health and management authorities were contacted through professional organizations, dairy industry publications and conferences, and industry contacts. Estimates of minimum, most likely, and maximum disability weights were derived for 12 common dairy cow diseases. Survey participants were asked to estimate the impact of each disease on overall health and milk production. Diseases were classified from 1 (minimal adverse effects) to 10 (death). The data was modelled using BetaPERT distributions to demonstrate the variation in these dynamic disease processes, and to identify the most likely aggregated disability weights for each disease classification. A single disability weight was assigned to each disease using the average of the combined medians for the minimum, most likely, and maximum severity scores. A total of 96 respondents provided estimates of disability weights. The final disability weight values resulted in the following order from least to most severe: retained placenta, diarrhea, ketosis, metritis, mastitis, milk fever, lame (hoof only), calving trauma, left displaced abomasum, pneumonia, musculoskeletal injury (leg, hip, back), and right displaced abomasum. The peaks of the probability density functions indicated that for certain disease states such as retained placenta there was a relatively narrow range of expected impact whereas other diseases elicited a wider breadth of impact. This was particularly apparent with respect to calving trauma, lameness and musculoskeletal injury, all of which could be redefined using gradients of severity or accounting for sequelae. These disability weight distributions serve as an initial step in the development of the disease-adjusted lactation (DALact) metric. They will be used to assess the time lost due to dynamic phases of dairy cow diseases and injuries.

Current Research

Mothers in danger: Precision dairying to measure the burden of maternal disease phenotypes. 

Supporting Agency:  USDA National Institute of Food and Agriculture-1014680

Specific Aims:  Dairy cattle health problems can be thought of as phenotypic expressions of the complex relationships between genes and environments.  The highest frequency of health disorders are associated with the transition from late gestation to early lactation, with most infectious or metabolic diseases likely to occur during early lactation.  Current assessments of dairy cow health problems tend to view diseases in isolation and use simple frequency measures to monetize disease events based on the cost per clinical case.  Human medical epidemiology offers useful insights into improving the depth of analysis of maternal disease.  The World Health Organization has attempted to standardize the burden of disease through a time-based summary measure of health termed a Disability-Adjusted Life Year (DALY).  The DALY helps health authorities assess the effectiveness of a country’s health system, and determine whether they are focusing on the right kind of health actions that will reduce the number of preventable deaths and diseases. The dairy industry needs to incorporate a similar innovation into evaluations of the burden of early lactation cow morbidity and mortality.

Preliminary efforts to develop a dairy summary measure of health have focused on time lost to clinical disease during individual lactations through the creation of the Disease-adjusted Lactation (DALact) metric.  As with the DALY, the DALact is reliant on disability weights that quantify health losses for all non-fatal consequences of disease and injury.  Disability weights are central to the comparable measurement of disease burden across diverse causes, and must account for broad considerations of health and well-being, methods of measurement, and the universality of their application.  A range of conceptual and methodological issues concern the definition and measurement of such weights.  The current disability weights established for common dairy cow clinical disease phenotypes are based on subjective input from experts in the field with inherent liabilities related to experience and perspective.  The primary goal of this proof of concept study is to develop a standardized approach for objective measurements of dairy disability weights for post-partum disease phenotypes.  This project will be the first attempt to expand the conception of dairy disability weights beyond professional judgment and standard etiologies through the input of experimental evidence based on precision dairy farming. Precision dairying involves the use of technologies to measure physiological, behavioral, and production indicators on individual animals. We will conduct a comprehensive empirical investigation of the impacts of subclinical and clinical disease on physiologic imbalance, as indicated by deviations in biochemical markers, gene expression, behavior, and production.  Improving existing disability weights by accounting for diverse influences and levels of severity will provide a method for discriminating proportional health loss and opportunity costs.  The availability of such disability weights will provide empirical estimations of the burden of disease and injury to be incorporated into a robust time-based summary measure of dairy cow health and well-being.  In the end, prioritizing health interventions based on time will expand the discussion of animal health and well-being to view profits and losses in light of the quality and length of life.