The Big Pet Diabetes Survey: Perceived Frequency and Triggers for Euthanasia

Current pet diabetes mellitus (DM) treatment necessitates the active daily involvement of owners and can be costly. The current study aimed to investigate the owner population which opts for euthanasia instead of DM treatment. A survey was designed using multiple feedback steps and made available online to veterinarians world-wide. A total of 1192 veterinarians completed the survey and suggested a median one in 10 diabetic pets are euthanased at diagnosis; a further median one in 10 within one year because of lack of success or compliance. Perceived most important motivating factors included “presence concurrent disease” (45% respondents); “costs” (44%); “animal age” (37%); “problems obtaining adequate control” (35%); “pet welfare” (35%); and “impact owner’s lifestyle” (32%). Cats in Canadian (odds ratio (OR) 2.7), Australian (OR 2.3), rural (OR 1.6) and mixed (OR 1.7) practices were more likely to be euthanased because of DM diagnosis, while cats presented to referral/university were less likely to be euthanased (OR 0.6). Dogs were more likely to be euthanased because of DM in Canadian (OR 1.8), rural (OR 1.8) and mixed (OR 1.6) practices. The survey results suggest that benefit exists in improved DM education with emphasis on offering a choice of treatment styles ranging from intense and expensive to hands-off and cheap

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining ‘big’ data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype

Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns

Abstract Background Abattoir data are under-used for surveillance. Nationwide surveillance could benefit from using data on meat inspection findings, but several limitations need to be overcome. At the producer level, interpretation of meat inspection findings is a notable opportunity for surveillance with relevance to animal health and welfare. In this study, we propose that discovery and monitoring of relational patterns between condemnation conditions co-present in broiler batches at meat inspection can provide valuable information for surveillance of farmed animal health and welfare. Results Great Britain (GB)-based integrator meat inspection records for 14,045 broiler batches slaughtered in nine, four monthly intervals were assessed for the presence of surveillance indicators relevant to broiler health and welfare. K-means and correlation-based hierarchical clustering, and association rules analyses were performed to identify relational patterns in the data. Incidence of condemnation showed seasonal and temporal variation, which was detected by association rules analysis. Syndrome-related and non-specific relational patterns were detected in some months of meat inspection records. A potentially syndromic cluster was identified in May 2016 consisting of infection-related conditions: pericarditis, perihepatitis, peritonitis, and abnormal colour. Non-specific trends were identified in some months as an unusual combination of condemnation reasons in broiler batches. Conclusions We conclude that the detection of relational patterns in meat inspection records could provide producer-level surveillance indicators with relevance to broiler chicken health and welfare

Risk-based inspection as a cost-effective strategy to reduce human exposure to cysticerci of Taenia saginata in low-prevalence settings

Taenia saginata cysticercus is the larval stage of the zoonotic parasite Taenia saginata, with a life-cycle involving both cattle and humans. The public health impact is considered low. The current surveillance system, based on post-mortem inspection of carcasses has low sensitivity and leads to considerable economic burden. Therefore, in the interests of public health and food production efficiency, this study aims to explore the potential of risk-based and cost-effective meat inspection activities for the detection and control of T. saginata cysticercus in low prevalence settings

Modelling habitat suitability in Jordan for the cutaneous leishmaniasis vector (Phlebotomus papatasi) using multicriteria decision analysis

Cutaneous leishmaniasis (CL) is a zoonotic vector-borne neglected tropical disease transmitted by female Phlebotomine sand flies. It is distributed globally but a large proportion of cases (70–75%) are found in just ten countries. CL is endemic in Jordan yet there is a lack of robust entomological data and true reporting status is unknown. This study aimed to map habitat suitability of the main CL vector, Phlebotomus papatasi, in Jordan as a proxy for CL risk distribution to (i) identify areas potentially at risk of CL and (ii) estimate the human population at risk of CL. A literature review identified potential environmental determinants for P. papatasi occurrence including temperature, humidity, precipitation, vegetation, wind speed, presence of human households and presence of the fat sand rat. Each predictor variable was (a) mapped; (b) standardized to a common size, resolution and scale using fuzzy membership functions; (c) assigned a weight using the analytical hierarchy process (AHP); and (d) included within a multicriteria decision analysis (MCDA) model to produce monthly maps illustrating the predicted habitat suitability (between 0 and 1) for P. papatasi in Jordan. Suitability increased over the summer months and was generally highest in the north-western regions of the country and along the Jordan Valley, areas which largely coincided with highly populated parts of the country, including areas where Syrian refugee camps are located. Habitat suitability in Jordan for the main CL vector—P. papatasi—was heterogeneous over both space and time. Suitable areas for P. papatasi coincided with highly populated areas of Jordan which suggests that the targeted implementation of control and surveillance strategies in defined areas such as those with very high CL vector suitability (>0.9 suitability) would focus only on 3.42% of the country’s total geographic area, whilst still including a substantial proportion of the population at risk: estimates range from 72% (European Commission’s Global Human Settlement population grid) to 89% (Gridded Population of the World) depending on the human population density data used. Therefore, high impact public health interventions could be achieved within a reduced spatial target, thus maximizing the efficient use of resources

Eimeria species occurrence varies between geographic regions and poultry production systems and may influence parasite genetic diversity

Coccidiosis is one of the biggest challenges faced by the global poultry industry. Recent studies have highlighted the ubiquitous distribution of all Eimeria species which can cause this disease in chickens, but intriguingly revealed a regional divide in genetic diversity and population structure for at least one species, Eimeria tenella. The drivers associated with such distinct geographic variation are unclear, but may impact on the occurrence and extent of resistance to anticoccidial drugs and future subunit vaccines. India is one of the largest poultry producers in the world and includes a transition between E. tenella populations defined by high and low genetic diversity. The aim of this study was to identify risk factors associated with the prevalence of Eimeria species defined by high and low pathogenicity in northern and southern states of India, and seek to understand factors which vary between the regions as possible drivers for differential genetic variation. Faecal samples and data relating to farm characteristics and management were collected from 107 farms from northern India and 133 farms from southern India. Faecal samples were analysed using microscopy and PCR to identify Eimeria occurrence. Multiple correspondence analysis was applied to transform correlated putative risk factors into a smaller number of synthetic uncorrelated factors. Hierarchical cluster analysis was used to identify poultry farm typologies, revealing three distinct clusters in the studied regions. The association between clusters and presence of Eimeria species was assessed by logistic regression. The study found that large-scale broiler farms in the north were at greatest risk of harbouring any Eimeria species and a larger proportion of such farms were positive for E. necatrix, the most pathogenic species. Comparison revealed a more even distribution for E. tenella across production systems in south India, but with a lower overall occurrence. Such a polarised region- and system-specific distribution may contribute to the different levels of genetic diversity observed previously in India and may influence parasite population structure across much of Asia and Africa. The findings of the study can be used to prioritise target farms to launch and optimise appropriate anticoccidial strategies for long-term control

Assessment of animal African trypanosomiasis (AAT) vulnerability in cattle-owning communities of sub-Saharan Africa

Background: Animal African trypanosomiasis (AAT) is one of the biggest constraints to livestock production and a threat to food security in sub-Saharan Africa. In order to optimise the allocation of resources for AAT control, decision makers need to target geographic areas where control programmes are most likely to be successful and sustainable and select control methods that will maximise the benefits obtained from resources invested. Methods: The overall approach to classifying cattle-owning communities in terms of AAT vulnerability was based on the selection of key variables collected through field surveys in five sub-Saharan Africa countries followed by a formal Multiple Correspondence Analysis (MCA) to identify factors explaining the variations between areas. To categorise the communities in terms of AAT vulnerability profiles, Hierarchical Cluster Analysis (HCA) was performed. Results: Three clusters of community vulnerability profiles were identified based on farmers’ beliefs with respect to trypanosomiasis control within the five countries studied. Cluster 1 communities, mainly identified in Cameroon, reported constant AAT burden, had large trypanosensitive (average herd size = 57) communal grazing cattle herds. Livestock (cattle and small ruminants) were reportedly the primary source of income in the majority of these cattle-owning households (87.0 %). Cluster 2 communities identified mainly in Burkina Faso and Zambia, with some Ethiopian communities had moderate herd sizes (average = 16) and some trypanotolerant breeds (31.7 %) practicing communal grazing. In these communities there were some concerns regarding the development of trypanocide resistance. Crops were the primary income source while communities in this cluster incurred some financial losses due to diminished draft power. The third cluster contained mainly Ugandan and Ethiopian communities which were mixed farmers with smaller herd sizes (average = 8). The costs spent diagnosing and treating AAT were moderate here. Conclusions: Understanding how cattle-owners are affected by AAT and their efforts to manage the disease is critical to the design of suitable locally-adapted control programmes. It is expected that the results could inform priority setting and the development of tailored recommendations for AAT control strategies