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 estimates for lactational incidence or prevalence or both, 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 US$65 billion (B). Subclinical ketosis, clinical mastitis, and subclinical mastitis were the costliest diseases modeled, resulting in mean annual global losses of approximately US$18B, US$13B, and US$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 US$0.2B, US$0.6B, US$0.6B, US$6B, US$5B, US$0.6B, US$4B, US$4B, and US$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 (US$12B), the United States (US$8B), and China (US$5B), depending on the measure of losses used (losses as a percentage of gross domestic product, losses per capita, losses as a percentage of gross milk revenue), the relative economic burden of these dairy cattle diseases across countries varied markedly.

Quantifying cost of disease in livestock: a new metric for the Global Burden of Animal Diseases.

BACKGROUND: Increasing awareness of the environmental and public health impacts of expanding and intensifying animal-based food and farming systems creates discord, with the reliance of much of the world's population on animals for livelihoods and essential nutrition. Increasing the efficiency of food production through improved animal health has been identified as a step towards minimising these negative effects without compromising global food security. The Global Burden of Animal Diseases (GBADs) programme aims to provide data and analytical methods to support positive change in animal health across all livestock and aquaculture animal populations. METHODS: In this study, we present a metric that begins the process of disease burden estimation by converting the physical consequences of disease on animal performance to farm-level costs of disease, and calculates a metric termed the Animal Health Loss Envelope (AHLE) via comparison between the status quo and a disease-free ideal. An example calculation of the AHLE metric for meat production from broiler chickens is provided. FINDINGS: The AHLE presents the direct financial costs of disease at farm-level for all causes by estimating losses and expenditure in a given farming system. The general specification of the model measures productivity change at farm-level and provides an upper bound on productivity change in the absence of disease. On its own, it gives an indication of the scale of total disease cost at farm-level. INTERPRETATION: The AHLE is an essential stepping stone within the GBADs programme because it connects the physical performance of animals in farming systems under different environmental and management conditions and different health states to farm economics. Moving forward, AHLE results will be an important step in calculating the wider monetary consequences of changes in animal health as part of the GBADs programme. FUNDING: Bill & Melinda Gates Foundation, the UK Foreign, Commonwealth and Development Office, EU Horizon 2020 Research and Innovation Programme.

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.