Using a One Health approach to assess the impact of parasitic disease in livestock: how does it add value?

Human population increases, with greater food demands, have resulted in a rapid evolution of livestock food systems, leading to changes in land and water use. The scale of global livestock systems mean that changes in animal health status, particularly in parasite levels, have impacts that go beyond farm and sector levels. To quantify the true impact of parasites in livestock, frameworks that look at both resources and services valued in markets and those that have no true market value are required. Mitigating the effects of parasitic disease in livestock will not only increase productivity, but also improve animal welfare and human health, whilst reducing the environmental burden of livestock production systems. To measure these potential benefits, a One Health approach is needed. This paper discusses the types of methods and the data collection tools needed for a more holistic perspective and provides a framework with its application to coccidiosis in poultry. To build a body of knowledge that allows the ranking of parasite diseases in a wider animal health setting, such One Health frameworks need to be applied more frequently and with rigour. The outcome will improve the allocation of resources to critical constraints on parasite management

Changes in parental anxiety and intention to demand antibiotics: A longitudinal study among parents during the COVID-19 pandemic

Aims: Assessing the effects of the COVID-19 pandemic on parental anxiety and preferences for antibiotic treatment can help inform antibiotic stewardship strategies. Therefore, this study aimed to examine COVID-19 pandemic-related changes in parental anxiety levels, their intentions to demand antibiotics and frequencies of practising preventative behaviours. Design: This longitudinal quantitative study compared two groups of parents, those from Victoria and Western Australia, who experienced high and low COVID-19 risk, respectively. Methods: Participants were recruited through an online panel to complete three waves of surveys between October 2020 and August 2021. Anxiety scores and frequency of preventative behaviours were analysed using mixed-effects tobit regression, considering time, state, and their interaction as fixed effects predictors. Intention to demand antibiotics was modelled using multinomial logistic regression, with time, state, and their interaction as the predictors. Results: The final longitudinal sample comprised 50 participants from Victoria and 51 from Western Australia. Parental anxiety did not significantly change over time for either state. Intention to demand antibiotics was also stable over time within each state; however, participants from Victoria exhibited stronger intentions to demand antibiotics compared to those from Western Australia. Frequencies of parental preventative behaviours declined from Wave 1 to Wave 2 before increasing again in Wave 3, but only for Western Australia. Conclusion: This longitudinal study among Australian parents found stable parental anxiety and intention to demand antibiotics within each state. However, the intention to demand antibiotics and preventative behaviours varied between states as per the COVID-19 risk. Thus, viral pandemics may not affect judicious antibiotic use, though the intention to demand antibiotics may increase in states with high COVID-19 risk. Impact: Though parental anxiety may not impact antibiotic stewardship during viral respiratory illness outbreaks, tailored messaging to maintain appropriate antibiotic use may be necessary, especially when the disease risk is high

Genomic analysis of clostridioides difficile recovered from horses in Western Australia

Clostridioides difficile poses an ongoing threat as a cause of gastrointestinal disease in humans and animals. Traditionally considered a human healthcare-related disease, increases in community-associated C. difficile infection (CDI) and growing evidence of inter-species transmission suggest a wider perspective is required for CDI control. In horses, C. difficile is a major cause of diarrhoea and life-threatening colitis. This study aimed to better understand the epidemiology of CDI in Australian horses and provide insights into the relationships between horse, human and environmental strains. A total of 752 faecal samples from 387 Western Australian horses were collected. C. difficile was isolated from 104 (30.9%) horses without gastrointestinal signs and 19 (37.8%) with gastrointestinal signs. Of these, 68 (55.3%) harboured one or more toxigenic strains, including C. difficile PCR ribotypes (RTs) 012 (n = 14), 014/020 (n = 10) and 087 (n = 7), all prominent in human infection. Whole-genome analysis of 45 strains identified a phylogenetic cluster of 10 closely related C. difficile RT 012 strains of equine, human and environmental origin (0–62 SNP differences; average 23), indicating recent shared ancestry. Evidence of possible clonal inter-species transmission or common-source exposure was identified for a subgroup of three horse and one human isolates, highlighting the need for a One Health approach to C. difficile surveillance

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

3rd Annual Conference of the Leverhulme Centre for Integrative Research on Agriculture and Health (LCIRAH), Developing methods in agriculture and health research, London, 13–14 June 2013

Non-PRIFPRI3; ISI; CRP4; B Promoting healthy food systemsPHND; A4NHCGIAR Research Program on Agriculture for Nutrition and Health (A4NH

Scaling up One Health: a network analysis in Lao PDR

Background: One Health focuses on sustainable health for humans, animals, and ecosystems. The approach has been well demonstrated, yet most efforts have not been scaled up. Understanding the organisations involved in scaling up processes is critical to translating research into practice. The Lao People's Democratic Republic has successfully implemented One Health projects for multiple decades; however, the organisational network has not been described and scaling up efforts have been limited. Methods: Data from organisations involved in One Health projects over the past five years were collected by keyinformant interview or workshop. The network was investigated using a mixture of quantitative network analysis and qualitative thematic analysis. Results: The organisational network was quantitatively described as sparse and centralised. Organisations were required to harness pre-existing relationships to maximise scarce resources and make co-ordination and alignment of priorities more efficient. A lack of international organisations in the top 10% of resource sharing metrics suggests a potential disconnect between donors. This was reflected in the challenges faced by national organisations and a feeling of being stretched thin over numerous externally funded projects with donor-driven priorities. Conclusions: It appears that high-level political support for country ownership of development and aid priorities remains unrealised. Developing network capacity and capability may assist scaling up efforts and build resilience in the network and its core organisations. This may allow for the inclusion of more development, education, environment, and water, sanitation, and hygiene organisations that were perceived to be lacking. Future One Health programmes should focus on practical activities that do not overload staff capacity. There is much for One Health to learn about the art of scaling up and organisations are encouraged to include implementation science in their research to inform future scaling up efforts

Profiling Detection and Classification of Lameness Methods in British Dairy Cattle Research: A Systematic Review and Meta-Analysis

Lameness is a serious concern in the dairy sector, reflecting its high incidence and impact on animal welfare and productivity. Research has provided figures on its frequency using different methodologies, making it difficult to compare results and hindering farm-level decision-making. The study's objectives were to determine the frequency levels of lameness in British dairy cattle through a meta-analysis approach, and to understand the chronological patterns of how lameness cases are detected and classified in scientific research. A systematic review was conducted using PRISMA-P guidelines for article selection. Random-effects models estimated the pooled frequency measure of lameness with heterogeneity managed through subgroup analysis and meta-regression. Sixty-eight papers were identified, 50 included prevalence and 36 incidence data. The pooled prevalence of lameness in British dairy cattle was estimated at 29.5% (95% CI 26.7–32.4%) whilst all-cause lameness incidence rate indicated 30.9 cases of lameness per 100 cow-years (95% CI 24.5–37.9). The pooled cause-specific lameness incidence rate per 100 cow-years was 66.1 (95% CI 24.1–128.8) for white line disease, 53.2 (95% CI 20.5–101.2) for sole ulcer, 53.6 (95% CI 19.2–105.34) for digital dermatitis, with 51.9 (95% CI 9.3–129.2) attributable to other lameness-related lesions. Heterogeneity levels remained high. Sixty-nine papers contributed to a chronological overview of lameness data source. Although the AHDB Dairy mobility scoring system (MSS) was launched in the UK in 2008 and adopted shortly after by the British Dairy sector as the standard tool for assessing lameness, other methods are used depending on the investigator. Automated lameness detection systems may offer a solution for the subjective nature of MSSs, yet it was utilized in one study only. Despite the recognition of under-reporting of lameness from farm records 22 (31.9%) studies used this data source. The diversity of lameness data collection methods and sources was a key finding. It limits the understanding of lameness burden and the refinement of policy making for lameness. Standardizing case definition and research methods would improve knowledge of and ability to manage lameness. Regardless of the measurement method lameness in British dairy cattle is high

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