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

Global and regional prediction of heterakidosis population prevalence in extensive backyard chickens in low-income and middle-income countries

Extensive backyard chickens are one of the most common production systems in low-income and middle-income countries (LMICs). In this production system, chickens are exposed to infectious forms of parasites as a result of the outdoor access and scavenging behaviour. Heterakis gallinarum is one of the most common nematode parasites present in the environment, and estimating its global and regional prevalence is essential for attributing the economic losses in extensive backyard chickens. The objective of this study is to predict the prevalence of heterakidosis in extensive backyard chickens at global and regional levels in LMICs using regression imputation methods. A binomial random effect model was developed using empirical data on heterakidosis prevalence and climatic factors as main predictors. Prevalence data were then imputed in all regions based on the regression model. Global and country prevalence were estimated based on regional predictions and their beta distributions. Minimum precipitation, minimum temperature and maximum temperature were selected as significant predictors. The population prevalence of heterakidosis was 0.24 (0.19-0.29). Countries with continental and dry climates had a higher mean prevalence, whereas countries with tropical climates had a lower mean prevalence of heterakidosis. As more empirical data on heterakidosis prevalence become available, this model and predictions should be redefined and updated to capture a more representative association and increase the accuracy of the predictions. The results of this study can be used to attribute the economic losses of extensive backyard chickens, taking into account a holistic approach as promoted by the GBADs programme and therefore, to identify which diseases are more costly to backyard farmers. Furthermore, results can be also served as a proxy for the risk of histomoniasis in extensive backyard chickens.

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.

Improve animal health to reduce livestock emissions: quantifying an open goal

Greenhouse gas (GHG) emissions from livestock production must be urgently tackled to substantially reduce their contribution to global warming. Simply reducing livestock numbers to this end risks impacting negatively on food security, rural livelihoods and climate change adaptation. We argue that significant mitigation of livestock emissions can be delivered immediately by improving animal health and hence production efficiency, but this route is not prioritized because its benefits, although intuitive, are poorly quantified. Rigorous methodology must be developed to estimate emissions from animal disease and hence achievable benefits from improved health through interventions. If, as expected, climate change is to affect the distribution and severity of health conditions, such quantification becomes of even greater importance. We have therefore developed a framework and identified data sources for robust quantification of the relationship between animal health and greenhouse gas emissions, which could be applied to drive and account for positive action. This will not only help mitigate climate change but at the same time promote cost-effective food production and enhanced animal welfare, a rare win-win in the search for a sustainable planetary future.

Setting the boundaries-an approach to estimate the Loss Gap in dairy cattle

Dairy production in the UK has undergone substantial restructuring over the last few decades. Farming intensification has led to a reduction in the total numbers of farms and animals, while the average herd size per holding has increased. These ever-changing circumstances have important implications for the health and welfare of dairy cows, as well as the overall business performance of farms. For decision-making in dairy farming, it is essential to understand the underlying causes of the inefficiencies and their relative impact. The investigation of yield gaps regarding dairy cattle has been focused on specific causes. However, in addition to the risk of overestimating the impact of a specific ailment, this approach does not allow understanding of the relative contribution to the total, nor does it allow understanding of how well-described that gap is in terms of underlying causes. Using the English and Welsh dairy sectors as an example, this work estimates the Loss Gap-composed of yield losses and health expenditure - using a benchmarking approach and scenario analysis. The Loss Gap was estimated by comparing the current performance of dairy herds as a baseline with that of scenarios where assumptions were made about the milk production of cows, production costs, market prices, mortality, and expenditure related to health events. A deterministic model was developed, consisting of an enterprise budget, in which the cow was the unit, with milking herd and young stock treated separately. When constraining milk production, the model estimated an annual Loss Gap of £148 to £227 million for the whole sector. The reduction in costs of veterinary services and medicines, alongside herd replacement costs, were important contributors to the estimate with some variation between the scenarios. Milk price had a substantial impact in the estimate, with revenue from milk yield representing more than 30% of the Loss Gap, when milk price was benchmarked against that of the top performing farms. This framework provides the boundaries for understanding the relative burden from specific causes in English and Welsh dairy cattle, ensuring that the sum of the estimated losses due to particular problem does not exceed the losses from all-causes, health or non-health related.

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.

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.

Population, distribution, biomass, and economic value of Equids in Ethiopia

BACKGROUND

Equids play a crucial role in the Ethiopian economy, transporting agricultural inputs and outputs in the dominant subsistence agricultural systems and the critical link for value chains throughout the country. However, these species are often neglected in policies and interventions, which reflects the data and information gaps, particularly the contribution of working equids to Ethiopia.

OBJECTIVE

To assess population dynamics, distribution, biomass, and economic value of equids in Ethiopia.

MATERIALS AND METHODS

Equine population data were obtained from the Ethiopian Central Statistics Agency (CSA) annual national agriculture surveys published yearbooks from 2004 to 2020. Parameters such as the number of effective service days and daily rental value were obtained from interviews and literature to estimate the stock monetary and service value of equids. Descriptive statistics were used to assess population dynamics and the geographical distribution was mapped.

RESULTS

The estimated total Ethiopian equid population increased by more than doubled (by 131%) between 2004 and 2020 from 5.7 (4.9-6.6) million to 13.3 (11.6-15) million with 2.1 million horses, 10.7 million donkeys, and 380 thousand mules. Similarly, the number of households owning a working equid has increased. Equine populations are unevenly distributed across Ethiopia, although data were lacking in some districts of the country. The per human-capita equine population ranged from 0-0.52, 0-0.13, and 0-0.02 for donkeys, horses, and mules, respectively. The equid biomass was 7.4 (6.3-8.4) million Tropical livestock unit (TLU) (250 kg liveweight), 10% of total livestock biomass of the country. The stock monetary value of equids was USD 1,229 (651-1,908) million, accounting for 3.1% of total livestock monetary value and the services value of equids was USD 1,198 (825-1,516) million, which is 1.2% of Ethiopian 2021 expected GDP.

CONCLUSION

The Ethiopian equine population has grown steadily over the last two decades. Equids play a central role in transportation and subsistence agriculture in Ethiopia and contribute significantly to the national economy. This pivotal role is insufficiently recognized in national livestock investments.

Immunoproteomic analysis of the serum IgG response to cell wall-associated proteins of Staphylococcus aureus strains belonging to CC97 and CC151

CC97 and CC151 are two of the most common Staphylococcus aureus lineages associated with bovine intramammary infection. The genotype of the infecting S. aureus strain influences virulence and the progression of intramammary disease. Strains from CC97 and CC151 encode a distinct array of virulence factors. Identification of proteins elaborated in vivo will provide insights into the molecular mechanism of pathogenesis of these lineages, as well as facilitating the development of tailored treatments and pan-lineage vaccines and diagnostics. The repertoire of genes encoding cell wall-anchored (CWA) proteins was identified for S. aureus strains MOK023 (CC97) and MOK124 (CC151); MOK023 encoded more CWA proteins than MOK124. Serum collected during an in vivo challenge trial was used to investigate whether the humoral response to cell wall proteins was strain-specific. Immunoproteomic analysis demonstrated that the humoral response in MOK023-infected cows predominantly targeted high molecular weight proteins while the response in MOK124-infected cows targeted medium or low molecular weight proteins. Antigenic proteins were identified by two-dimensional serum blotting followed by mass spectometry-based identification of immunoreactive spots, with putative antigens subsequently validated. The CWA proteins ClfB, SdrE/Bbp and IsdA were identified as immunogenic regardless of the infecting strain. In addition, a number of putative strain-specific imunogens were identified. The variation in antigens produced by different strains may indicate that these strains have different strategies for exploiting the intramammary niche. Such variation should be considered when developing novel control strategies including vaccines, therapeutics and diagnostics.

Protective Effect against Neosporosis Induced by Intranasal Immunization with Neospora caninum Membrane Antigens Plus Carbomer-Based Adjuvant

Neospora caninum is an obligate intracellular protozoan responsible for abortion and stillbirths in cattle. We previously developed a mucosal vaccination approach using N. caninum membrane proteins and CpG adjuvant that conferred long-term protection against neosporosis in mice. Here, we have extended this approach by alternatively using the carbomer-based adjuvant Carbigen™ in the immunizing preparation. Immunized mice presented higher proportions and numbers of memory CD4⁺ and CD8⁺ T cells. Stimulation of spleen, lungs and liver leukocytes with parasite antigens induced a marked production of IFN-γ and IL-17A and, less markedly, IL-4. This balanced response was also evident in that both parasite-specific IgG1 and IgG2c were raised by immunization, together with specific intestinal IgA. Upon intraperitoneal infection with N. caninum, immunized mice presented lower parasitic burdens than sham-immunized controls. In the infected immunized mice, memory CD4⁺ T cells predominantly expressed T-bet and RORγt, and CD8⁺ T cells expressing T-bet were found increased. While spleen, lungs and liver leukocytes of both immunized and sham-immunized infected animals produced high amounts of IFN-γ, only the cells from immunized mice responded with high IL-17A production. Since in cattle both IFN-γ and IL-17A have been associated with protective mechanisms against N. caninum infection, the elicited cytokine profile obtained using Carbigen^TM as adjuvant indicates that it could be worth exploring for bovine neosporosis vaccination.