Roll-out of the Global Burden of Animal Diseases programme

A framework for handling uncertainty in a large-scale programme estimating the Global Burden of Animal Diseases

Livestock provide nutritional and socio-economic security for marginalized populations in low and middle-income countries. Poorly-informed decisions impact livestock husbandry outcomes, leading to poverty from livestock disease, with repercussions on human health and well-being. The Global Burden of Animal Diseases (GBADs) programme is working to understand the impacts of livestock disease upon human livelihoods and livestock health and welfare. This information can then be used by policy makers operating regionally, nationally and making global decisions. The burden of animal disease crosses many scales and estimating it is a complex task, with extensive requirements for data and subsequent data synthesis. Some of the information that livestock decision-makers require is represented by quantitative estimates derived from field data and models. Model outputs contain uncertainty, arising from many sources such as data quality and availability, or the user's understanding of models and production systems. Uncertainty in estimates needs to be recognized, accommodated, and accurately reported. This enables robust understanding of synthesized estimates, and associated uncertainty, providing rigor around values that will inform livestock management decision-making. Approaches to handling uncertainty in models and their outputs receive scant attention in animal health economics literature; indeed, uncertainty is sometimes perceived as an analytical weakness. However, knowledge of uncertainty is as important as generating point estimates. Motivated by the context of GBADs, this paper describes an analytical framework for handling uncertainty, emphasizing uncertainty management, and reporting to stakeholders and policy makers. This framework describes a hierarchy of evidence, guiding movement from worst to best-case sources of information, and suggests a stepwise approach to handling uncertainty in estimating the global burden of animal disease. The framework describes the following pillars: background preparation; models as simple as possible but no simpler; assumptions documented; data source quality ranked; commitment to moving up the evidence hierarchy; documentation and justification of modelling approaches, data, data flows and sources of modelling uncertainty; uncertainty and sensitivity analysis on model outputs; documentation and justification of approaches to handling uncertainty; an iterative, up-to-date process of modelling; accounting for accuracy of model inputs; communication of confidence in model outputs; and peer-review.

A dynamic framework for calculating the biomass of fattening pigs with an application in estimating the burden of porcine reproductive and respiratory syndrome in the Netherlands

Gaining insight into the size and composition of national pig populations can support decisions on disease control, welfare, and environmental sustainability. However, if one needs to draw meaningful comparisons between the performance of various production systems or countries, a method for standardization is required. One approach to achieve this is by means of biomass estimation. The objective of this study was to develop a biomass estimation framework that can provide detailed and reliable estimates of fattening pig biomass disaggregated by pig life stage (suckling, weaning and fattening), while accounting for the dynamic nature of pig populations. The framework was developed on publicly accessible data pertaining to pig production in the Netherlands, and we additionally assessed availability of required data for several other European countries (Spain, Germany, and Great Britain). Three distinct life stages-suckling piglets, weaning pigs, and fattening pigs-are considered in the framework. Demographic and movement data, including yearly imports, exports, and slaughter numbers, along with standing populations, were collected from official governmental sources. Required production parameters were sourced from representative surveys, with missing parameters supplemented by private industry reports or expert elicitation. The results from the framework for the Netherlands yield insights into the Dutch pig sector. In 2020, 156 million kg, 552 million kg, and 1654 million kg of biomass were produced in the suckling, weaning, and fattening stages, respectively. The evaluation against census data indicated the framework's reliability, with deviations mostly below 10 %. Data availability assessments for Spain, Germany and Great Britain reveal variations in data completeness and underscore the importance of local contacts and language expertise when extending the framework to other countries. The framework's relevance was further demonstrated through an illustrative application, assessing the impact of porcine reproductive and respiratory syndrome on pig biomass in the Netherlands. In the most severe disease scenario, the produced biomass decreased by 13 %, 17 %, and 66 % in the suckling, weaning, and fattening stages, respectively. Beyond disease burden estimation, the biomass estimates can be used as a denominator for various purposes to provide efficiency metrics, such as the amount of antibiotics used or the volume of greenhouse gases emitted per kilogram of pig biomass produced. While the framework could benefit from further refinement regarding resource use and economic values, its current iteration provides a robust and unique foundation for estimating biomass disaggregated by pig life stage, aiding decision-makers in the agricultural and veterinary sector.

Economic assessment of animal disease burden in Senegalese small ruminants

Small ruminant production in sub-Saharan Africa is limited by a range of constraints, including animal health issues. This study aimed at estimating the impact of these issues on the small ruminant production in Senegal in a holistic manner, using an approach developed by the Global Burden of Animal Diseases (GBADs) programme. The estimation focused on the mixed crop-livestock system, representing a large proportion (>60 %) of the small ruminant population in the country. It was based on existing data collected via a systematic literature review, acquisition of secondary datasets from local stakeholders, and expert elicitation. A dynamic population model was used to calculate the gross margin of the sector under both the current health constraints and an ideal health state, where animals are not exposed to causes of morbidity and mortality. The difference between the current and ideal health scenarios, termed the Animal Health Loss Envelope (AHLE), provides a quantitative measure of the farm-level cost of disease in the system. The all-cause AHLE was estimated at 292 billion FCFA (468 million USD, with 95 % prediction interval 216 - 366 billion FCFA) per year for 2022, for a population of 8.8 million animals. The contribution of Peste des Petits Ruminants (PPR) was modelled separately, as an example of attributing part of the AHLE to a specific disease cause. PPR was estimated to contribute 5 % of the total AHLE. The animal disease burden experienced by Senegalese livestock keepers was largely due to loss in animals and production, with relatively small amounts of animal health expenditure. Implementation of this study contributed to the further development of the GBADs approach. Such estimates can support decision making at all levels, from investment decisions at the international level to local disease awareness campaigns targeting livestock keepers.

Prioritization, resource allocation and utilization of decision support tools in animal health: Results of qualitative interviews with experts

A follow up to an online questionnaire survey (in a kind of a sequential study design), qualitative assessment was made on the views of selected animal health experts on disease prioritization methods, resource allocation and use of decision-support tools. This was done through in-depth interviews with experts working for national or international organizations and sectors. A semi-structured question guide was formulated based on the information generated in the online questionnaire and a systematic content analysis of animal and human health manuals for disease prioritization and resource allocation. In-depth, one-on-one, online interviews on the process of disease prioritization, animal health decision-making, types of prioritization tools and aspects of improvements in the tools were conducted during March and April 2022 with 20 expert informants. Prioritization approaches reported by experts were either single criterion-based or multiple criteria-based. Experts appreciated the single-criterion-based approach (quantitative) for its objectivity in contrast to multicriteria prioritization approaches which were criticized for their subjectivity. Interviews with the experts revealed a perceived lack of quality and reliable data to inform disease prioritization, especially in smallholder livestock production systems. It was found that outputs of disease prioritization exercises do not generally directly influence resource allocation in animal health and highlighted the paucity of funding for animal health compared to other agricultural sectors. The experts considered that the available decision-support tools in animal health need improvement in terms of data visualization for interpretation, management decision making and advocacy. Further recommendations include minimizing subjective biases by increasing the availability and quality of data and improving the translation of disease prioritization outputs into actions and the resources to deliver those actions. DATA AVAILABILITY STATEMENT: The data can be obtained from the corresponding author upon request.

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.

The burden of antimicrobial resistance in livestock: A framework to estimate its impact within the Global Burden of Animal Diseases programme

In addition to affecting animal health and production, antimicrobial resistance (AMR) in livestock can have far-reaching social and economic consequences, including on human health and the environment. Given the diversity of data needs and the absence of standardised methodologies, the scale of antimicrobial use (AMU) and AMR's social and economic burden on livestock is complex to gauge. Yet, quantifying this impact can be an essential input for farm-level decision-making and, more widely, for policy development, public awareness, resource allocation to interventions and research and development prioritisation, particularly in a One Health context. This work proposes a conceptual framework to guide the assessment of the burden of AMU and AMR in livestock using the Global Burden of Animal Diseases (GBADs) approach. Its development identified and mapped critical socio-economic concepts in AMU and AMR in livestock and their relationships. The Animal Health Loss Envelope (AHLE), a monetary metric that sets a boundary for overall losses from health hazards and allows an understanding of the relative importance of health problems in livestock, was used as the metric in which the concepts and data needs for the AMU and AMR assessment were anchored. The proposed framework identifies pathways for losses and data inputs needed to estimate the burden of AMU and AMR within this wider envelope of losses. These include information on health expenditure and mortality and morbidity effects related to AMR in livestock. This work highlights the need for improved health and production data collection in livestock production as an essential stepping stone to accurately producing AMU and AMR burden estimates.

Current and potential use of animal disease data by stakeholders in the global south and north

What cannot be measured will not be managed. The Global Burden of Animal Diseases (GBADs) will generate information on animal disease burdens by species, production system, type and gender of farmer and consumer, geographical region, and time period. To understand the demand for burden of animal disease (BAD) data and how end-users might benefit from this, we reviewed the literature on animal diseases prioritisation processes (ADPP) and conducted a survey of BAD information users. The survey covered their current use of data and prioritizations as well as their needs for different, more, and better information. We identified representative (geography, sector, species) BAD experts from the authors' networks and publicly available documents and e-mailed 1485 experts. Of 791 experts successfully contacted, 271 responded (34% response rate), and 185 complete and valid responses were obtained. Most respondents came from the public sector followed by academia/research, and most were affiliated to institutions in low- and middle-income countries (LMICs). Of the six ADPPs commonly featured in literature, only three were recognised by more than 40% of experts. An additional 23 ADPPs were used. Awareness of ADDPs varied significantly by respondents. Respondents ranked animal disease priorities. We used exploded logit to combine first, second and third disease priorities to better understand prioritzation and their determinants. Expert priorities differed significantly from priorities identified by the ADDPs, and also from the priorities stated veterinary services as reported in a survey for a World Organisation of Animal Health (WOAH) technical item. Respondents identified 15 different uses of BAD data. The most common use was presenting evidence (publications, official reports, followed by disease management, policy development and proposal writing). Few used disease data for prioritzation or resource allocation, fewer routinely used economic data for decision making, and less than half were aware of the use of decision support tools (DSTs). Nearly all respondents considered current BAD metrics inadequate, most considered animal health information insufficiently available and not evidence-based, and most expressed concerns that decision-making processes related to animal health lacked transparency and fairness. Cluster analysis suggested three clusters of BAD users and will inform DSTs to help them better meet their specific objectives. We conclude that there is a lack of satisfaction with current BAD information, and with existing ADDPs, contributing to sub-optimal decision making. Improved BAD data would have multiple uses by different stakeholders leading to better evidenced decisions and policies; moreover, clients will need support (including DSTs) to optimally use BAD information.

Calculation of livestock biomass and value by province in Indonesia: Key information to support policymaking

Accurate estimations of the biomass and value of livestock in Indonesia are of great use in supporting investment decisions by the public and private sector and as a basis for estimating the losses due to animal disease. Biomass and the partial direct use value for key livestock species (cattle, buffalo, sheep, goats, pigs, chickens) for all provinces of Indonesia were derived from secondary data using a novel spreadsheet-based model. Using beef cattle as an example, we also explored the use of a herd dynamics model to validate base data on populations and productivity used to generate biomass values, and these were found to be generally robust. Total partial direct use value of livestock is estimated to be almost USD54 billion in 2021, comprising almost USD33 billion of population value and almost USD21 billion of production value. Beef cattle account for 44% of total value and chicken (broiler, layer and native chickens) account for a further 36% of the total. Breaking the data down by province reveals the regional importance of some livestock types that are of relatively minor importance nationally (pigs in East Nusa Tenggara and sheep in West Java). It also reveals the importance of livestock in the poorest provinces of Indonesia, where livestock acts as a store of wealth and serves socio-cultural purposes.

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.

Approximating the global economic (market) value of farmed animals

Understanding the global economic importance of farmed animals to society is essential as a baseline for decision making about future food systems. We estimated the annual global economic (market) value of live animals and primary production outputs, e.g., meat, eggs, milk, from terrestrial and aquatic farmed animal systems. The results suggest that the total global market value of farmed animals ranges between 1.61 and 3.3 trillion USD (2018) and is expected to be similar in absolute terms to the market value of crop outputs (2.57 trillion USD). The cattle sector dominates the market value of farmed animals. The study highlights the need to consider other values of farmed animals to society, e.g., finance/insurance value and cultural value, in decisions about the sector's future.

Attributing Ethiopian animal health losses to high-level causes using expert elicitation

The Global Burden of Animal Diseases programme is currently working to estimate the burden of animal health loss in Ethiopia. As part of this work, structured expert elicitation has been trialled to attribute the proportion of animal health losses due to three independent and exhaustive high-level causes (infectious, non-infectious, and external). Separate in-person workshops were conducted with eight cattle, nine small ruminant, and eight chicken experts. Following the Investigate-Discuss-Estimate-Aggregate protocol for structured expert elicitation, estimates were obtained for the proportion of animal health loss due to high-level causes in different combinations of health loss, species, age-sex class, and production system. Three-point questions were used to inform beta-pert distributions and capture uncertainty in estimates. Individual expert estimates were aggregated by quantile mean to produce average distributions. Random samples from these average distributions estimated that infectious causes inflict the highest proportion of health loss in Ethiopia, with at least 40 % of health losses estimated to be due to infectious causes in all categories. This study provides a rapid, simple, and engaging method to attribute the burden of animal health loss at a high-level. Results are informative, however will become increasingly useful once they can be compared with results from more sophisticated, data-driven models.

On-farm investments into dairy cow health: evidence from 15 case study countries

Managing investments in dairy cow health at a national and global scale, requires an improved understanding of current on-farm expenses for cow health (e.g., expenditure for medicine and veterinary consultations). The aim of this study was to assess on-farm health investments for typical dairy farms in 15 case study countries, including Argentina, Australia, Bangladesh, Brazil, Canada, India, China, Colombia, Indonesia, Kenya, New Zealand, Uganda, UK, Uruguay, and USA. The study was conducted using a descriptive analysis of a secondary data set that was obtained from the International Farm Comparison Network (IFCN). The results suggest that health expenditures take up a relatively small proportion (<10%) of the annual total production costs per cow across all countries in the sample. The means of production costs (e.g., feed, machinery) can take up to 90% of the total production costs for highly intensive systems, while these costs can be as low as 9% for extensive systems. This study highlights the importance of understanding on-farm animal health investments as a contribution to improved national and global decision making about animal health in the dairy sector.

The economic impact of endemic respiratory disease in pigs and related interventions - a systematic review

BACKGROUND

Understanding the financial consequences of endemically prevalent pathogens within the porcine respiratory disease complex (PRDC) and the effects of interventions assists decision-making regarding disease prevention and control. The aim of this systematic review was to identify what economic studies have been carried out on infectious endemic respiratory disease in pigs, what methods are being used, and, when feasible, to identify the economic impacts of PRDC pathogens and the costs and benefits of interventions.

RESULTS

By following the PRISMA method, a total of 58 studies were deemed eligible for the purpose of this systematic review. Twenty-six studies used data derived from European countries, 18 from the US, 6 from Asia, 4 from Oceania, and 4 from other countries, i.e., Canada, Mexico, and Brazil. Main findings from selected publications were: (1) The studies mainly considered endemic scenarios on commercial fattening farms; (2) The porcine reproductive and respiratory syndrome virus was by far the most studied pathogen, followed by Mycoplasma hyopneumoniae, but the absence or presence of other endemic respiratory pathogens was often not verified or accounted for; (3) Most studies calculated the economic impact using primary production data, whereas twelve studies modelled the impact using secondary data only; (4) Seven different economic methods were applied across studies; (5) A large variation exists in the cost and revenue components considered in calculations, with feed costs and reduced carcass value included the most often; (6) The reported median economic impact of one or several co-existing respiratory pathogen(s) ranged from €1.70 to €8.90 per nursery pig, €2.30 to €15.35 per fattening pig, and €100 to €323 per sow per year; and (7) Vaccination was the most studied intervention, and the outcomes of all but three intervention-focused studies were neutral or positive.

CONCLUSION

The outcomes and discussion from this systematic review provide insight into the studies, their methods, the advantages and limitations of the existing research, and the reported impacts from the endemic respiratory disease complex for pig production systems worldwide. Future research should improve the consistency and comparability of economic assessments by ensuring the inclusion of high impact cost and revenue components and expressing results similarly.

Characterizing Ethiopian cattle production systems for disease burden analysis

This paper addresses knowledge gaps in the biomass, productivity and value of livestock for the pastoral, mixed crop-livestock and specialized dairy systems in Ethiopia. Population size, reproductive performance, mortality, offtake and productivity of cattle were calculated from official statistics and a meta-analysis of data available in the published literature. This information was then used to estimate biomass and output value for 2020 using a herd dynamics model. The mixed-crop livestock system dominates the Ethiopian cattle sector, with 55 million cattle (78% total population) and contributing 8.52 billion USD to the economy through the provision of meat, milk, hides and draft power in 2021. By comparison, the pastoral (13.4 million head) and specialized dairy (1.8 million head) systems are much smaller. Productivity varied between different production systems, with differences in live body weight, productivity and prices from different sources. The estimated total cattle biomass was 14.8 billion kg in 2021, i.e., 11.3 billion kg in the mixed crop-livestock system, 2.60 billion kg in the pastoral system and 0.87 billion kg in the specialized dairy system. The total economic asset values of cattle in the mixed crop-livestock, pastoral and specialized dairy systems were estimated as 24.8, 5.28 and 1.37 billion USD, respectively. The total combined output value (e.g., beef, milk and draft power) of cattle production was 11.9 billion USD, which was 11.2% of the GDP in Ethiopia in 2021. This work quantifies the importance of cattle in the Ethiopian economy. These estimates of herd structure, reproductive performance, productivity, biomass, and economic value for cattle production systems in Ethiopia can be used to inform high-level policy, revealing under-performance and areas to prioritize and provide a basis for further technical analysis, such as disease burden.

A high level estimation of the net economic benefits to small-scale livestock producers arising from animal health product distribution initiatives

Introduction

A fundamental challenge for charities that facilitate distribution of animal health products to small-scale livestock producers (SSPs) in low and middle income countries (LMICs) is identifying the products and market mechanisms that provide the greatest positive impact for SSPs and estimating their associated impact. This paper describes a pragmatic approach to modeling the impact of market-led product distribution initiatives based on estimating the net economic benefit of administration of animal health products.

Methods

The model estimates the economic impact of diseases at the individual animal level for poultry, small ruminants, and cattle. The economic impact of mortality and growth inhibition associated with disease are then estimated in conjunction with the losses averted or recovered by preventing or treating the disease. Economic benefit is estimated in 2014-2017 values and also adjusted to 2023 values. The flexible model structure allows for addition of new geographies, new products, and increased granularity of modeled production systems.

Results

Applied to the Global Alliance for Livestock Veterinary Medicines (GALVmed) product distribution initiatives conducted in Africa and South Asia (SA) between 2014 and 2017, the model estimates an adjusted total net economic benefit of 139.9 million USD from sales of vaccines and poultry anthelminthics in these initiatives. Within SSA, the greatest net economic benefit was realized from East Coast fever and Newcastle disease vaccines, while in SA, peste des petits ruminants and Newcastle disease vaccines had the greatest net economic benefits. This translated to an adjusted $37.97 of net economic benefit on average per SSP customer, many of whom were small poultry producers.

Discussion

While the model currently estimates impacts from mortality and growth inhibition in livestock, there is the potential to extend it to cover impacts of further initiatives, including interventions targeted at diseases that impact production of milk, eggs, and reproduction.

Household production and consumption impacts of foot and mouth disease at the Uganda-Tanzania border

Introduction

Foot-and-mouth disease (FMD) is a highly contagious viral disease that is endemic in East Africa. FMD virus infection incurs significant control costs and reduces animal productivity through weight loss, lowered milk yield, and potentially death but how household's respond to these losses may differentially affect household income and food consumption.

Methodology

To address this, we use unique data from a FMD outbreak to assess how household production and consumption activities change from before to during the outbreak. Data came from a 2018 survey of 254 households in selected Tanzanian wards and sub-counties in Uganda. The data includes household recall of before and during an outbreak in the past year on livestock and livestock product sales, milk and beef consumption, as well as related changes in market prices. We apply both difference-in-difference and change in difference ordinary least squares regressions with fixed effects to evaluate the impact of FMD on household production and consumption.

Results and discussion

We find that households reported the largest reductions in livestock and livestock product sales, followed by reduced milk consumption and animal market prices. The changes in household income from livestock sales appears to be driven by FMD virus infection within the household herd while changes in market prices of substitute protein sources are primary associated with changes in milk and beef consumption. The role of widespread market price effects across both infected and uninfected herds and countries, tends to suggest that stabilizing prices will likely have a large impact on household nutritional security and income generation. We also propose that promoting diversity in market activity may mitigate differing impacts on households in FMD endemic regions.

Towards better survival: Modeling drivers for daily mortality in Norwegian Atlantic salmon farming

Mortality in the production of farmed salmonids is a major constraint to the sustainability of this form of animal husbandry. We have developed a model for the daily mortality in salmon farming over a full production cycle from stocking to harvest, considering different environmental and production factors. These factors included sea temperature, salinity, day within year, fish weight at stocking, stocking day, four types of lice treatments and the possible occurrence of pancreas disease (PD). We considered a generalized additive model following full production cycles, allowing for non-linear descriptions of how relevant factors relate to the daily mortality. We saw a high overall mortality rate immediately after stocking, which decreased the first three months in the cycle and thereafter increased. We found that the total mortality could be reduced by 21% if avoiding all lice treatments, and similarly reduced by 20% if no PD infections occurred. If avoiding jointly PD and all lice treatments, the accumulated mortality could be reduced by 34%. A single thermal or hydrogen peroxide treatment was associated with a mortality of around 1.6% and 1.3%, respectively. This modeling approach gave a unique opportunity to model how different factors interact on the overall global mortality and can easily be extended by other factors, such as additional fish diseases.

Methodological choices in brucellosis burden of disease assessments: A systematic review

BACKGROUND

Foodborne and zoonotic diseases such as brucellosis present many challenges to public health and economic welfare. Increasingly, researchers and public health institutes use disability-adjusted life years (DALYs) to generate a comprehensive comparison of the population health impact of these conditions. DALYs calculations, however, entail a number of methodological choices and assumptions, with data gaps and uncertainties to accommodate. Thisreview identifies existing brucellosis burden of disease studies and analyzes their methodological choices, assumptions, and uncertainties. It supports the Global Burden of Animal Diseases programme in the development of a systematic methodology to describe the impact of animal diseases on society, including human health.

METHODS/PRINCIPAL FINDINGS

A systematic search for brucellosis burden of disease calculations was conducted in pre-selected international and grey literature databases. Using a standardized reporting framework, we evaluated each estimate on a variety of key methodological assumptions necessary to compute a DALY. Fourteen studies satisfied the inclusion criteria (human brucellosis and quantification of DALYs). One study reported estimates at the global level, the rest were national or subnational assessments. Data regarding different methodological choices were extracted, including detailed assessments of the adopted disease models. Most studies retrieved brucellosis epidemiological data from administrative registries. Incidence data were often estimated on the basis of laboratory-confirmed tests. Not all studies included mortality estimates (Years of Life Lost) in their assessments due to lack of data or the assumption that brucellosis is not a fatal disease. Only two studies used a model with variable health states and corresponding disability weights. The rest used a simplified singular health state approach. Wide variation was seen in the duration chosen for brucellosis, ranging from 2 weeks to 4.5 years, irrespective of the whether a chronic state was included.

CONCLUSION

Available brucellosis burden of disease assessments vary widely in their methodology and assumptions. Further research is needed to better characterize the clinical course of brucellosis and to estimate case-fatality rates. Additionally, reporting of methodological choices should be improved to enhance transparency and comparability of estimates. These steps will increase the value of these estimates for policy makers.

Population, biomass, and economic value of small ruminants in Ethiopia

Ethiopia has a large population of small ruminants (sheep and goats) which are mostly kept in traditional subsistence production systems that are poorly described. Understanding these different systems, their population structure, biomass, production, and economic value is essential for further analysis and effective policy making. The objective of this study was to quantify these parameters for small ruminant production systems in Ethiopia to use them as a basis for analysis of disease burden within the Global Burden of Animal Diseases program. Population structure and trends of small ruminants were analyzed using data from ten annual national agriculture surveys. A stochastic herd model was used to simulate the small ruminant population, biomass, and economic value. The model was parameterised stochastically using data from statistical databases and the literature, and sensitivity analysis of main model outputs to the stochastic inputs was done. Small ruminants are held across the country mainly managed under two major production systems: the crop-livestock mixed system and the pastoral system. The small ruminant population has grown in the past 10 years with an average annual growth rate of 4.6% for sheep and 6.7% for goats. The national average small ruminant population for 2021 was projected at 96.4 (range 95.3–97.7) million heads and the mean stock biomass was about 2,129 (range 1,680–2,686) million kilograms. The monetary value of the small ruminant population was estimated at USD 5,953 (range 4,369–7,765) million. The annual monetary value of small ruminant production outputs was estimated at USD 1,969 (range 1,245–2,857) million. Although the small ruminant population is large and rapidly growing, contributing about 2% of national annual GDP, the sub-sector is characterized by low productivity, low offtake rates, and a limited range of production outputs with no signs of intensification. Efforts should be made to reduce small ruminant mortality, improve fertility, and better utilize products such as milk to improve the livelihoods of rural households and to benefit the national economy. The approaches developed in this study can be replicated in other systems and countries to reveal trends in the size and value of livestock systems, providing a better understanding of its economic importance and performance.

Longitudinal Study of Selected Bacterial Zoonoses in Small Ruminants in Tana River County, Kenya

Brucellosis, Q fever, and leptospirosis are priority zoonoses worldwide, yet their epidemiology is understudied, and studies investigating multiple pathogens are scarce. Therefore, we selected 316 small ruminants in irrigated, pastoral, and riverine settings in Tana River County and conducted repeated sampling for animals that were initially seronegative between September 2014 and June 2015. We carried out serological and polymerase chain reaction tests and determined risk factors for exposure. The survey-weighted serological incidence rates were 1.8 (95% confidence intervals [CI]: 1.3–2.5) and 1.3 (95% CI: 0.7–2.3) cases per 100 animal-months at risk for Leptospira spp. and C. burnetii, respectively. We observed no seroconversions for Brucella spp. Animals from the irrigated setting had 6.83 (95% CI: 2.58–18.06, p-value = 0.01) higher odds of seropositivity to C. burnetii than those from riverine settings. Considerable co-exposure of animals to more than one zoonosis was also observed, with animals exposed to one zoonosis generally having 2.5 times higher odds of exposure to a second zoonosis. The higher incidence of C. burnetii and Leptospira spp. infections, which are understudied zoonoses in Kenya compared to Brucella spp., demonstrate the need for systematic prioritization of animal diseases to enable the appropriate allocation of resources.

A scoping review of burden of disease studies estimating disability-adjusted life years due to Taenia solium

BACKGROUND

Taenia solium is the most significant global foodborne parasite and the leading cause of preventable human epilepsy in low and middle-income countries in the form of neurocysticercosis.

OBJECTIVES

This scoping review aimed to examine the methodology of peer-reviewed studies that estimate the burden of T. solium using disability-adjusted life years.

ELIGIBILITY CRITERIA

Studies must have calculated disability-adjusted life years relating to T. solium.

CHARTING METHODS

The review process was managed by a single reviewer using Rayyan. Published data relating to disease models, data sources, disability-adjusted life years, sensitivity, uncertainty, missing data, and key limitations were collected.

RESULTS

15 studies were included for review, with seven global and eight national or sub-national estimates. Studies primarily employed attributional disease models that relied on measuring the occurrence of epilepsy before applying an attributable fraction to estimate the occurrence of neurocysticercosis-associated epilepsy. This method relies heavily on the extrapolation of observational studies across populations and time periods; however, it is currently required due to the difficulties in diagnosing neurocysticercosis. Studies discussed that a lack of data was a key limitation and their results likely underestimate the true burden of T. solium. Methods to calculate disability-adjusted life years varied across studies with differences in approaches to time discounting, age weighting, years of life lost, and years of life lived with disability. Such differences limit the ability to compare estimates between studies.

CONCLUSIONS

This review illustrates the complexities associated with T. solium burden of disease studies and highlights the potential need for a burden of disease reporting framework. The burden of T. solium is likely underestimated due to the challenges in diagnosing neurocysticercosis and a lack of available data. Advancement in diagnostics, further observational studies, and new approaches to parameterising disease models are required if estimates are to improve.

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.

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Three approaches to impact aggregation for multiple endemic diseases explored.

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Flexible method proposed to avoid double counting impacts within a livestock system.

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Illustrated using 13 endemic diseases and health conditions in UK dairy cattle.

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Provides an alternative perspective on ranking disease prevention priorities.

Estimating the financial impact of livestock schistosomiasis on traditional subsistence and transhumance farmers keeping cattle, sheep and goats in northern Senegal

BACKGROUND

Schistosomiasis is a disease that poses major threats to human and animal health, as well as the economy, especially in sub-Saharan Africa (SSA). Whilst many studies have evaluated the economic impact of schistosomiasis in humans, to date only one has been performed in livestock in SSA and none in Senegal. This study aimed to estimate the financial impact of livestock schistosomiasis in selected regions of Senegal.

METHODS

Stochastic partial budget models were developed for traditional ruminant farmers in 12 villages in northern Senegal. The models were parameterised using data from a cross-sectional survey, focus group discussions, scientific literature and available statistics. Two scenarios were defined: scenario 1 modelled a situation in which farmers tested and treated their livestock for schistosomiasis, whilst scenario 2 modelled a situation in which there were no tests or treatment. The model was run with 10,000 iterations for 1 year; results were expressed in West African CFA francs (XOF; 1 XOF was equivalent to 0.0014 GBP at the time of analysis). Sensitivity analyses were conducted to assess the impact of uncertain variables on the disease costs.

RESULTS

Farmers surveyed were aware of schistosomiasis in their ruminant livestock and reported hollowing around the eyes, diarrhoea and weight loss as the most common clinical signs in all species. For scenario 1, the median disease costs per year and head of cattle, sheep and goats were estimated at 13,408 XOF, 27,227 XOF and 27,694 XOF, respectively. For scenario 2, the disease costs per year and head of cattle, sheep and goats were estimated at 49,296 XOF, 70,072 XOF and 70,281 XOF, respectively.

CONCLUSIONS

Our findings suggest that the financial impact of livestock schistosomiasis on traditional subsistence and transhumance farmers is substantial. Consequently, treating livestock schistosomiasis has the potential to generate considerable benefits to farmers and their families. Given the dearth of data in this region, our study serves as a foundation for further in-depth studies to provide estimates of disease impact and as a baseline for future economic analyses. This will also enable One Health economic studies where the burden on both humans and animals is estimated and included in cross-sectoral cost-benefit and cost-effectiveness analyses of disease control strategies.