Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis.

An economic simulation was carried out over 183 milk-producing countries to estimate the global economic impacts of 12 dairy cattle diseases and health conditions: mastitis (subclinical and clinical), lameness, paratuberculosis (Johne's disease), displaced abomasum, dystocia, metritis, milk fever, ovarian cysts, retained placenta, and ketosis (subclinical and clinical). Estimates of disease impacts on milk yield, fertility, and culling were collected from the literature, standardized, meta-analyzed using a variety of methods ranging from simple averaging to random-effects models, and adjusted for comorbidities to prevent overestimation. These comorbidity-adjusted disease impacts were then combined with a set of country-level lactational incidence and/or prevalence estimates, herd characteristics, and price estimates within a series of Monte Carlo simulations that estimated and valued the economic losses due to these diseases. It was estimated that total annual global losses are USD 65 billion (B). Subclinical ketosis, clinical mastitis, and subclinical mastitis were the costliest diseases modeled, resulting in mean annual global losses of approximately USD 18B, USD 13B, and USD 9B, respectively. Estimated global annual losses due to clinical ketosis, displaced abomasum, dystocia, lameness, metritis, milk fever, ovarian cysts, paratuberculosis, and retained placenta were estimated to be USD 0.2B, 0.6B, 0.6B, 6B, 5B, 0.6B, 4B, 4B, and 3B, respectively. Without adjustment for comorbidities, when statistical associations between diseases were disregarded, mean aggregate global losses would have been overestimated by 45%. Although annual losses were greatest in India (USD 12B), the USA (USD 8B), and China (USD 5B), depending on the measure of losses used (losses as a percent of GDP, losses per capita, losses as a percent of gross milk revenue), the relative economic burden of these dairy cattle diseases across countries varied markedly.

Prediction of coccidiosis prevalence in extensive backyard chickens in countries and regions of the Horn of Africa.

Coccidiosis is one of the leading morbidity causes in chickens, causing a reduction of body weight and egg production. Backyard chickens are at risk of developing clinical and subclinical coccidiosis due to outdoor housing and scavenging behaviour, jeopardizing food security in households. The objectives of this study were to estimate clinical prevalence of coccidiosis at country and regional levels in the Horn of Africa in extensive backyard chickens. A binomial random effects model was developed to impute prevalence of coccidiosis. Previously gathered prevalence data (n = 40) in backyard chickens was used to define the model. Precipitation (OR: 1.09 (95% CI: 1.05-1.13) and the presence of seasonal rainfall (OR: 1.85, 95% CI: 1.27-2.70) significantly increase prevalence. Results showed an overall prevalence of coccidiosis in the Horn of Africa of 0.21 (95% CI: 0.15-0.29). Ethiopia, the Republic of South Sudan and Kenya showed the highest prevalence and Djibouti the lowest. Significant differences between Djibouti and the countries with highest prevalence were found. However, no evidence of a significant difference between the rest of the countries. Kenya and Ethiopia showed larger prevalence differences between regions. Results could assist with the targeting of testing for coccidiosis, the observation for clinical disease of chickens living in specific regions and as a baseline for the evaluation of future control measures.

Rationalising development of classification systems describing livestock production systems for disease burden analysis within the Global Burden of Animal Diseases programme.

The heterogeneity that exists across the global spectrum of livestock production means that livestock productivity, efficiency, health expenditure and health outcomes vary across production systems. To ensure that burden of disease estimates are specific to the represented livestock population and people reliant upon them, livestock populations need to be systematically classified into different types of production system, reflective of the heterogeneity across production systems. This paper explores the data currently available of livestock production system classifications and animal health through a scoping review as a foundation for the development of a framework that facilitates more specific estimates of livestock disease burdens. A top-down framework to classification is outlined based on a systematic review of existing classification methods and provides a basis for simple grouping of livestock at global scale. The proposed top-down classification framework, which is dominated by commodity focus of production along with intensity of resource use, may have less relevance at the sub-national level in some jurisdictions and will need to be informed and adapted with information on how countries themselves categorize livestock and their production systems. The findings in this study provide a foundation for analysing animal health burdens across a broad level of production systems. The developed framework will fill a major gap in how livestock production and health are currently approached and analysed.

Impact of Aging and Lifelong Exercise Training on Mitochondrial Function and Network Connectivity in Human Skeletal Muscle.

Aging is associated with metabolic decline in skeletal muscle, which can be delayed by physical activity. Moreover, both lifelong and short-term exercise training have been shown to prevent age-associated fragmentation of the mitochondrial network in mouse skeletal muscle. However, whether lifelong endurance exercise training exerts the same effects in human skeletal muscle is still not clear. Therefore, the aim of the present study was to examine the effect of volume-dependent lifelong endurance exercise training on mitochondrial function and network connectivity in older human skeletal muscle. Skeletal muscle complex I+II-linked mitochondrial respiration per tissue mass was higher, but intrinsic complex I+II-linked mitochondrial respiration was lower in highly trained older subjects than in young untrained, older untrained, and older moderately trained subjects. Mitochondrial volume and connectivity were higher in highly trained older subjects than in untrained and moderately trained older subjects. Furthermore, the protein content of the ADP/ATP exchangers ANT1 + 2 and VDAC was higher and of the mitophagic marker parkin lower in skeletal muscle from the highly trained older subjects than from untrained and moderately trained older subjects. In contrast, H2O2 emission in skeletal muscle was not affected by either age or exercise training, but SOD2 protein content was higher in highly trained older subjects than in untrained and moderately trained older subjects. This suggests that healthy aging does not induce oxidative stress or mitochondrial network fragmentation in human skeletal muscle, but high-volume exercise training increases mitochondrial volume and network connectivity, thereby increasing oxidative capacity in older human skeletal muscle.

Estimating the burden of multiple endemic diseases and health conditions using Bayes' Theorem: A conditional probability model applied to UK dairy cattle.

The Global Burden of Animal Diseases (GBADs) is an international collaboration aiming, in part, to measure and improve societal outcomes from livestock. One GBADs objective is to estimate the economic impact of endemic diseases in livestock. However, if individual disease impact estimates are linearly aggregated without consideration for associations among diseases, there is the potential to double count impacts, overestimating the total burden. Accordingly, the authors propose a method to adjust an array of individual disease impact estimates so that they may be aggregated without overlap. Using Bayes' Theorem, conditional probabilities were derived from inter-disease odds ratios in the literature. These conditional probabilities were used to calculate the excess probability of disease among animals with associated conditions, or the probability of disease overlap given the odds of coinfection, which were then used to adjust disease impact estimates so that they may be aggregated. The aggregate impacts, or the yield, fertility, and mortality gaps due to disease, were then attributed and valued, generating disease-specific losses. The approach was illustrated using an example dairy cattle system with input values and supporting parameters from the UK, with 13 diseases and health conditions endemic to UK dairy cattle: cystic ovary, disease caused by gastrointestinal nematodes, displaced abomasum, dystocia, fasciolosis, lameness, mastitis, metritis, milk fever, neosporosis, paratuberculosis, retained placenta, and subclinical ketosis. The diseases and conditions modelled resulted in total adjusted losses of £ 404/cow/year, equivalent to herd-level losses of £ 60,000/year. Unadjusted aggregation methods suggested losses 14-61% greater. Although lameness was identified as the costliest condition (28% of total losses), variations in the prevalence of fasciolosis, neosporosis, and paratuberculosis (only a combined 22% of total losses) were nearly as impactful individually as variations in the prevalence of lameness. The results suggest that from a disease control policy perspective, the costliness of a disease may not always be the best indicator of the investment its control warrants; the costliness rankings varied across approaches and total losses were found to be surprisingly sensitive to variations in the prevalence of relatively uncostly diseases. This approach allows for disease impact estimates to be aggregated without double counting. It can be applied to any livestock system in any region with any set of endemic diseases, and can be updated as new prevalence, impact, and disease association data become available. This approach also provides researchers and policymakers an alternative tool to rank prevention priorities.

Economic premiums associated with Mycobacterium avium ssp. paratuberculosis-negative replacement purchases in major dairy-producing regions.

Johne's disease, or paratuberculosis, is an infectious disorder of the intestines that can affect domestic and wild ruminants that is caused by an infection with Mycobacterium avium ssp. paratuberculosis (MAP). Although the economic losses due to Johne's disease in dairy cattle herds and the benefits and costs of various potential control practices have been estimated before, little is known about the economic value of purchasing MAP-negative dairy replacements in major dairy-producing regions. This study used Markov Chain Monte Carlo simulation techniques to compare 2 sets of MAP-negative and MAP-positive herds across a comprehensive selection of regions: herds purchasing MAP-negative replacement animals and herds purchasing replacement animals with unknown MAP infection status. The economic benefits per MAP-negative replacement purchased were then estimated over a 10-yr horizon, and the additional value of MAP-negative replacements when compared with unknown status replacements were calculated as a percentage premium of the average aggregated dairy replacement price in each region. An average benefit of US$76 per MAP-negative replacement purchase was estimated in major dairy-producing regions, equivalent to a premium of 13%, with higher premiums in regions characterized by below-average replacement prices and on-average farm-gate prices. It was also estimated that the greatest benefits from MAP-negative replacement purchases are associated with MAP-negative herds that successfully remain uninfected.

Corrigendum: Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds.

[This corrects the article DOI: 10.3389/fvets.2020.614727.].

Estimation of the value of Johne's disease (paratuberculosis) control to Canadian dairy producers.

Johne's disease (JD), or paratuberculosis, is an infectious disorder primarily associated with cattle and sheep and resulting in significant economic losses for dairy producers. The dairy cattle herd-level prevalence in Canada has recently been estimated to be greater than 40%, but the willingness to pay for JD control practices such as testing-and-culling and vaccination among Canadian dairy producers is unknown. This study used confidential cost-of-production data from the Canadian Dairy Commission to develop a Canadian dairy production model incorporating feed, land, labor, and machinery. A second dataset from a nationally distributed questionnaire (closed in March 2020) was used to estimate individual dairy producer valuations of the reduced per-cow cost of milk production that would result from JD control. This is a novel application of compensating variation and equivalent variation (CV and EV), with dairy producers framed as consumers of production inputs and milk output as a proxy for utility. Assuming a within-herd prevalence of 12.5% and a 50% reduction of that prevalence over 10 years, it was estimated JD control has an annual value of CA$28 per cow for the average Canadian dairy producer. Within-herd prevalence, the effectiveness of control at reducing within-herd prevalence, and the time required to achieve that reduction were identified as important factors. With the same assumption of 12.5% within-herd prevalence but with 100% reductions in that prevalence, estimated values ranged from over CA$55 to over CA$90 per cow per year depending on the timeframe of the control program. When assuming a 10-year period required to achieve control, the estimated values exceeded CA$90 per cow per year in various scenarios for herds with higher within-herd prevalence (greater than 20%).

Economic losses due to Johne's disease (paratuberculosis) in dairy cattle.

Johne's disease (JD), or paratuberculosis, is an infectious inflammatory disorder of the intestines primarily associated with domestic and wild ruminants including dairy cattle. The disease, caused by an infection with Mycobacterium avium subspecies paratuberculosis (MAP) bacteria, burdens both animals and producers through reduced milk production, premature culling, and reduced salvage values among MAP-infected animals. The economic losses associated with these burdens have been measured before, but not across a comprehensive selection of major dairy-producing regions within a single methodological framework. This study uses a Markov chain Monte Carlo approach to estimate the annual losses per cow within MAP-infected herds and the total regional losses due to JD by simulating the spread and economic impact of the disease with region-specific economic variables. It was estimated that approximately 1% of gross milk revenue, equivalent to US$33 per cow, is lost annually in MAP-infected dairy herds, with those losses primarily driven by reduced production and being higher in regions characterized by above-average farm-gate milk prices and production per cow. An estimated US$198 million is lost due to JD in dairy cattle in the United States annually, US$75 million in Germany, US$56 million in France, US$54 million in New Zealand, and between US$17 million and US$28 million in Canada, one of the smallest dairy-producing regions modeled.

Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds.

Johne's disease (JD or paratuberculosis) control programs have been established in many dairy-producing regions. However, the effectiveness (reduction of within-herd prevalence) and the relative economic impact as measured by, for example, the ratio of benefits to costs (BCR) across a comprehensive selection of regions and potential control practices require further investigation. Within a Markovian framework using region-specific economic variables, it was estimated that vaccination was the most promising type of JD control practice modeled, with dual-effect vaccines (reducing shedding and providing protective immunity) having BCRs between 1.48 and 2.13 in Canada, with a break-even period of between 6.17 and 7.61 years. Dual-effect vaccines were also estimated to yield BCRs greater than one in almost all major dairy-producing regions, with greater ratios in regions characterized by above-average farm-gate prices and annual production per cow. Testing and culling was comparably effective to a dual-effect vaccine at test sensitivities >70% but would remain economically unviable in almost all regions modeled.