Rapid detection and molecular epidemiology of ß-lactamase producing Enterobacteriaceae isolated from food animals and in-contact humans in Nigeria.

The emergence and spread of ß-lactamase-producing Enterobacteriaceae poses a significant threat to public health, necessitating the rapid detection and investigation of the molecular epidemiology of these pathogens. We modified a multiplex real-time (RT)-PCR to concurrently detect ß-lactamase genes (blaCTX-M, blaTEM, and blaSHV) and Enterobacteriaceae 16S ribosomal RNA. qPCR probes and primers were validated using control isolates, and the sensitivity and specificity assessed. The optimised multiplex qPCR was used to screen 220 non-clinical Enterobacteriaceae from food animals and in-contact humans in Southeast Nigeria selected on cefotaxime-supplemented agar plates. Binary logistic regression was used to explore factors associated with the presence of the blaTEM and blaSHV genes in these isolates, and a subset of isolates from matched sampling sites and host species were whole genome sequenced, and their antimicrobial resistance (AMR) and plasmid profiles determined. The sensitivity and specificity of the qPCR assay was 100%. All isolates (220/220) were positive for Enterobacteriaceae ribosomal 16S rRNA and blaCTX-M, while 66.4% (146/220) and 9% (20/220) were positive for blaTEM and blaSHV, respectively. The prevalence of blaTEM and blaSHV varied across different sampling sites (farm, animal market and abattoirs). Isolates from Abia state were more likely to harbour blaTEM (OR = 2.3, p = 0.04) and blaSHV (OR = 5.12,p = 0.01) than isolates from Ebonyi state; blaTEM was more likely to be detected in isolates from food animals than humans (OR = 2.34, p = 0.03), whereas the reverse was seen for blaSHV (OR = 7.23, p = 0.02). Furthermore, Klebsiella and Enterobacter isolates harboured more AMR genes than Escherichia coli, even though they were isolated from the same sample. We also identified pan resistant Klebsiella harbouring resistance to ten classes of antimicrobials and disinfectant. Therefore, we recommend ESKAPE pathogens are included in AMR surveillance in future and suggest qPCRs be utilised for rapid screening of Enterobacteriaceae from human and animal sources.

Is UK Puppy Purchasing Suffering a Long COVID Effect? Ongoing Negative Impacts of the COVID-19 Pandemic upon Puppy Purchase Motivations and Behaviours in 2021.

The COVID-19 pandemic led to a surge in acquisitions of puppies in the UK, dubbed the "Pandemic Puppy" phenomenon. In addition to an increased demand for puppies, widespread changes to both why and how puppies were purchased during this period compared to pre-pandemic 2019 purchases were documented, many of which threatened canine welfare (e.g., puppies being collected away from their place of birth, without seeing their mother). This study aimed to explore which changes to the pre-purchase and purchase motivations and behaviours of UK owners who purchased a puppy aged <16 weeks in the 2020 phase of the COVID-19 pandemic had persisted into 2021 or had returned to pre-pandemic 2019 levels. An online survey was conducted during February to April 2022 from which 2080 valid responses were analysed ("2021 puppies") and compared with previously collected data from comparable cohorts in 2019 (n = 1148, "2019 puppies") and 2020 (n = 4369, "Pandemic Puppies"). While the majority of the peak pandemic changes documented in 2020 had returned to their 2019 pre-pandemic baseline, others persisted into 2021. Multinomial logistic regression models revealed that the shifts during 2020 towards owners viewing their puppy pre-purchase over video calls or via video recordings/photos rather than in-person and towards collecting their puppy from outside of their breeders' property rather than inside had persisted into 2021 and had not returned to pre-pandemic levels. Year-on-year significant rises in the number of puppies sold with a passport were documented between 2019 and 2021, with over 1 in 10 2021 puppies having been sold with a passport, the figure more than doubling since 2019. An increasing number of these puppies sold with a passport were under the minimum legal age for import at sale. Going forward, these concerning changes require further monitoring and human behaviour change interventions to tackle, including increased buyer awareness but also legislative approaches to prevent the greatest harm.

Factors associated with foot-and-mouth disease seroprevalence in small ruminants and identification of hot-spot areas in northern Nigeria.

Many small ruminants infected with foot-and-mouth disease (FMD) remain asymptomatic, with the capacity to promote silent viral spread within domestic and wildlife species. However, little is known about the epidemiological role played by small ruminants in FMD. In particular, there are few studies that examine FMD seroprevalence, spatial patterns and risk factors for exposure in small ruminants. A cross-sectional study was conducted in northern Nigeria (Bauchi, Kaduna, and Plateau States) to determine the true seroprevalence of FMD in backyard small ruminants, identify factors associated with FMD seroconversion at animal and household levels, and identify spatial patterns for FMD virus exposure. Data on animal (n = 1800) and household (n = 300) characteristics were collected using a standardised questionnaire. Sera samples from 1800 small ruminants were tested for antibodies against non-structural proteins of FMD virus. True seroprevalence was estimated stochastically to account for variability and uncertainty in the test sensitivity and specificity previously reported. Risk factors for FMD seropositivity were identified at animal and household levels and spatial patterns were determined. The overall true seroprevalence for FMD virus, in the small ruminant population tested, was estimated to be 10.2 % (95 % Credible Interval (CrI) 0.0-19.0), while State-level estimates were 17.3 % (95 % CrI 0.0-25.8) for Kaduna, 6.9 % (95% CrI 0.0-15.8) for Bauchi, and 3.6 % (95 % CrI 0.0-12.6) for Plateau. State and species were the main risk factors identified at animal level, with interaction detected between them. Compared to goats in Plateau, the odds of testing positive were higher for goats in Bauchi (Odds Ratio (OR)= 1.83, 95 % CI 1.13-2.97, p = 0.01) and Kaduna (OR=2.97, 95 % CI 1.89-4.67, p < 0.001), as well as for sheep in Plateau (OR=3.78, 95 % CI 2.08-6.87, p < 0.001), Bauchi (OR=1.61, 95 % CI 0.91-2.84, p = 0.10), and Kaduna (OR=3.11, 95 % CI 1.61-6.01, p = 0.001). Households located in Kaduna were more likely to have a higher number of seropositive SR compared to those in Plateau (Prevalence Ratio (PR)= 1.75, 95 % CI 1.30-2.36, p < 0.001), and households keeping sheep flocks were more likely to be seropositive (from 1 to 10 sheep: PR=1.39, 95 % CI 1.05-1.82, p = 0.02; more than 10 sheep: PR=1.55, 95 % CI 1.12-2.15, p = 0.008) compared to those that did not keep sheep. A hot-spot was detected in Kaduna, and a cold-spot in Plateau. These results reveal that small ruminants had been recently exposed to FMD virus with spatial heterogeneity across the study area.

Molecular characterization of extended spectrum cephalosporin resistant Escherichia coli isolated from livestock and in-contact humans in Southeast Nigeria.

The rise in antimicrobial resistance (AMR) in bacteria is reducing therapeutic options for livestock and human health, with a paucity of information globally. To fill this gap, a One-Health approach was taken by sampling livestock on farms (n = 52), abattoir (n = 8), and animal markets (n = 10), and in-contact humans in Southeast Nigeria. Extended spectrum cephalosporin (ESC)-resistant (ESC-R) Escherichia coli was selectively cultured from 975 healthy livestock faecal swabs, and hand swabs from in-contact humans. Antimicrobial susceptibility testing (AST) was performed on all ESC-R E. coli. For isolates showing a multi-drug resistance (MDR) phenotype (n = 196), quantitative real-time PCR (qPCR) was performed for confirmation of extended-spectrum ß-lactamase (ESBL) and carbapenemase genes. Whole-genome sequencing (WGS) was performed on a subset (n = 157) for detailed molecular characterisation. The results showed ESC-R E. coli was present in 41.2% of samples, with AST results indicating 48.8% of isolates were phenotypically MDR. qPCR confirmed presence of ESBL genes, with bla CTX-M present in all but others in a subset [bla TEM (62.8%) and bla SHV (0.5%)] of isolates; none harboured transferable carbapenemase genes. Multi-locus sequence typing identified 34 Sequence Types (ST) distributed among different sampling levels; ST196 carrying bla CTX-M-55 was predominant in chickens. Large numbers of single nucleotide polymorphisms (SNPs) in the core genome of isolates, even within the same clade by phylogenetic analysis, indicated high genetic diversity. AMR genotyping indicated the predominant bla CTX-M variant was bla CTX-M-15 (87.9%), although bla CTX-M-55, bla CTX-M-64, and bla CTX-M-65 were present; it was notable that bla CTX-M-1, common in livestock, was absent. Other predominant AMR genes included: sul2, qnrS1, strB, bla TEM-1b, tetA-v2, and dfrA14, with prevalence varying according to host livestock species. A bla CTX-M-15 harbouring plasmid from livestock isolates in Ebonyi showed high sequence identity to one from river/sewage water in India, indicating this ESBL plasmid to be globally disseminated, being present beyond the river environment. In conclusion, ESC-R E. coli was widespread in livestock and in-contact humans from Southeast Nigeria. WGS data indicated the isolates were genetically highly diverse, probably representing true diversity of wild type E. coli; they were likely to be MDR with several harbouring bla CTX-M-15. Surprisingly, human isolates had highest numbers of AMR genes and pigs the least.

Pandemic Puppies: Demographic Characteristics, Health and Early Life Experiences of Puppies Acquired during the 2020 Phase of the COVID-19 Pandemic in the UK.

The UK recorded sharp rises in puppy purchasing during the 2020 phase of the COVID-19 pandemic, with many first-time dog owners purchasing puppies to improve their mental health during this challenging period. Government restrictions on movement and social interaction during the pandemic led to animal welfare concerns over puppies' reduced time-sensitive exposures to key environmental and social stimuli during their critical developmental period. This study aimed to compare demographics, health and early-life experiences of puppies purchased and brought home < 16 weeks of age between 23 March−31 December 2020 ("Pandemic Puppies"), with dogs purchased and brought home < 16 weeks during the same date period in 2019 ("2019 puppies"). An online survey of UK-based puppy owners was conducted between 10 November and 31 December 2020 with valid responses representing 5517 puppies (Pandemic Puppies: n = 4369; 2019 puppies: n = 1148). Multivariable logistic regression modelling revealed that Pandemic Puppies were less likely to have attended puppy training classes (67.9% 2019 vs. 28.9% 2020; p < 0.001) or had visitors to their home (94.5% 2019 vs. 81.8% 2020; p < 0.001) aged < 16 weeks compared with 2019 puppies. Fewer Pandemic Puppies underwent veterinary checks prior to purchase than 2019 puppies (2019: 91.3% vs. 2020: 87.4%; p < 0.001), but more were sold with a passport (2019: 4.1% vs. 2020: 7.1%; p < 0.001). Pandemic Puppies were significantly more likely to be 'Designer Crossbreeds' (2019: 18.8% vs. 2020: 26.1%; p < 0.001) and less likely to be Kennel Club registered than 2019 puppies (2019: 58.2% vs. 2020: 46.2%; p < 0.001). Greater support from veterinary and animal behavioural professionals is likely needed to ameliorate the health and behavioural impacts of growing up in a pandemic upon this vulnerable population.

Spatial distribution and risk factors for human cysticercosis in Colombia.

BACKGROUND: Cysticercosis is a zoonotic neglected tropical disease (NTD) that affects humans and pigs following the ingestion of Taenia solium eggs. Human cysticercosis poses a substantial public health burden in endemic countries. The World Health Organization (WHO) aims to target high-endemicity settings with enhanced interventions in 17 countries by 2030. Between 2008 and 2010, Colombia undertook a national baseline serosurvey of unprecedented scale, which led to an estimated seroprevalence of T. solium cysticercus antibodies among the general population of 8.6%. Here, we use contemporary geostatistical approaches to analyse this unique dataset with the aim of understanding the spatial distribution and risk factors associated with human cysticercosis in Colombia to inform how best to target intervention strategies. METHODS: We used a geostatistical model to estimate individual and household risk factors associated with seropositivity to T. solium cysticercus antibodies from 29,253 people from 133 municipalities in Colombia. We used both independent and spatially structured random effects at neighbourhood/village and municipality levels to account for potential clustering of exposure to T. solium. We present estimates of the distribution and residual correlation of seropositivity at the municipality level. RESULTS: High seroprevalence was identified in municipalities located in the north and south of Colombia, with spatial correlation in seropositivity estimated up to approximately 140 km. Statistically significant risk factors associated with seropositivity to T. solium cysticercus were related to age, sex, educational level, socioeconomic status, use of rainwater, consumption of partially cooked/raw pork meat and possession of dogs. CONCLUSIONS: In Colombia, the distribution of human cysticercosis is influenced by socioeconomic considerations, education and environmental factors related to the spread of T. solium eggs. This information can be used to tailor national intervention strategies, such as targeting spatial hotspots and more highly exposed groups, including displaced people and women. Large-scale seroprevalence surveys accompanied by geospatial mapping are an essential step towards reaching the WHO's 2021‒2030 NTD roadmap targets.

Pandemic Puppies: Characterising Motivations and Behaviours of UK Owners Who Purchased Puppies during the 2020 COVID-19 Pandemic.

Widespread media reports suggest that unusually high numbers of the public purchased, or sought to purchase, puppies following the first 'lockdown' phase of the COVID-19 pandemic in the UK, dubbed "Pandemic Puppies". This study aimed to explore this phenomenon by comparing pre-purchase motivations and behaviours, and purchase behaviours of UK owners purchasing puppies aged < 16 weeks from 23 March 2020-31 December 2020 with those of owners who purchased puppies during the same date-period in 2019. An online survey was conducted during November-December 2020, from which 5517 valid responses were analysed (2019 puppies: n = 1148; 2020 'Pandemic Puppies': n = 4369). Over 1 in 10 Pandemic Puppy owners had not considered purchasing a puppy before the pandemic, and 2 in 5 felt their decision to purchase a puppy had been influenced by the pandemic, most commonly by having more time to care for a dog (86.7%). Multivariable logistic regression models revealed that Pandemic Puppy owners were more likely to be first-time dog owners and have children in their household, were less likely to seek out a breeder that performed health testing on their breeding dog(s) or view their puppy in-person, and were more likely to pay a deposit without seeing their puppy. At purchase, Pandemic Puppies were more likely to be younger, delivered or collected from outside their breeders' property, seen without their littermates, and cost > £2000 compared with 2019 puppies. Changes in puppy purchasing during the pandemic raise welfare concerns for this unique population, including relinquishment, behavioural problems and poor health.

Household and animal factors associated with sheeppox and goatpox sero-prevalence and identification of high-risk areas in selected States of northern Nigeria.

Sheeppox and goatpox (SGP) are transboundary, highly contagious diseases affecting sheep and goats with characteristic clinical signs. SGP affect populations of small ruminants in Africa, Asia and the Middle East and, as a result, threaten farmers' livelihoods. Despite their importance, studies looking at factors that increase the risk of sheeppox-virus (SPPV) and goatpox-virus (GTPV) exposure and infection are limited. A cross-sectional study was conducted in three states of Northern Nigeria (Bauchi, Kaduna and Plateau) to determine the sero-prevalence and spatial patterns of SGP, and identify risk factors for SPPV/GTPV exposure at animal and household level. Sera samples were collected from 1,800 small ruminants from 300 households. Data on putative risk factors were collected using a standardised questionnaire. Twenty-nine small ruminants were sero-positive to SGP - apparent weighted sero-prevalence 2.0 %; 95 % C.I. 1.1-.3.0 %. Sero-positive animals came from 19 (6.3 %) households. Analysis of the questionnaire showed that a fifth (20.3 %) of farmers claimed to have experienced SGP outbreaks previously in their flocks, with 33 (1.8 %) of the individual animals sampled in this study reported to have had clinical signs. At animal level, the odds of being sero-positive were higher in older animals (>24months; OR = 8.0, p = 0.008 vs ≤24 months) and small ruminants with a history of clinical SGP (OR = 16.9, p = 0.01). Bringing new small ruminants into the household and having a history of SGP in the flock were the main factors identified at household level. Households were less likely to be sero-positive if the time between bringing animals into the household and sampling was over a year (PR = 0.31, p = 0.05), while households with a history of SGP were more likely to be sero-positive regardless of the timeframe. Important spatial heterogeneity was found. The Bayes smooth rate ranged from 0.06 to 4.10 % across local government areas (LGA), with LGA in the north-east or north-west of the study area identified as hot-spots for SGP exposure. Results from this study shed new light on the understanding of SGP epidemiology and provide key inputs to design risk-based surveillance and intervention programmes in the area.

A comparison of the value of two machine learning predictive models to support bovine tuberculosis disease control in England.

Nearly a decade into Defra's current eradication strategy, bovine tuberculosis (bTB) remains a serious animal health problem in England, with c.30,000 cattle slaughtered annually in the fight against this insidious disease. There is an urgent need to improve our understanding of bTB risk in order to enhance the current disease control policy. Machine learning approaches applied to big datasets offer a potential way to do this. Regularized regression and random forest machine learning methodologies were implemented using 2016 herd-level data to generate the best possible predictive models for a bTB incident in England and its three surveillance risk areas (High-risk area [HRA], Edge area [EA] and Low-risk area [LRA]). Their predictive performance was compared and the best models in each area were used to characterize herds according to risk. While all models provided excellent discrimination, random forest models achieved the highest balanced accuracy (i.e. average of sensitivity and specificity) in England, HRA and LRA, whereas the regularized regression LASSO model did so in the EA. The time since the last confirmed incident was resolved was the only variable in the top-ten ranking in all areas according to both types of models, which highlights the importance of bTB history as a predictor of a new incident. Risk categorisation based on Receiver Operating Characteristic (ROC) analysis was carried out using the best predictive models in each area setting a 99 % threshold value for sensitivity and specificity (97 % in the LRA). Thirteen percent of herds in the whole of England as well as in its HRA, 14 % in its EA and 31 % in its LRA were classified as high-risk. These could be selected for the deployment of additional disease control measures at national or area level. In this way, low-risk herds within the area considered would not be penalised unnecessarily by blanket control measures and limited resources be used more efficiently. The methodology presented in this paper demonstrates a way to accurately identify high-risk farms to inform a targeted disease control and prevention strategy in England that supplements existing population strategies.

Foraging in a dynamic environment: Response of four sympatric sub-Antarctic albatross species to interannual environmental variability.

Seasonal and annual climate variations are linked to fluctuations in the abundance and distribution of resources, posing a significant challenge to animals that need to adjust their foraging behavior accordingly. Particularly during adverse conditions, and while energetically constrained when breeding, animals ideally need to be flexible in their foraging behavior. Such behavioral plasticity may separate "winners" from "losers" in light of rapid environmental changes due to climate change. Here, the foraging behavior of four sub-Antarctic albatross species was investigated from 2015/16 to 2017/18, a period characterized by pronounced environmental variability. Over three breeding seasons on Marion Island, Prince Edward Archipelago, incubating wandering (WA, Diomedea exulans; n = 45), grey-headed (GHA, Thalassarche chrysostoma; n = 26), sooty (SA, Phoebetria fusca; n = 23), and light-mantled (LMSA, P. palpebrata; n = 22) albatrosses were tracked with GPS loggers. The response of birds to environmental variability was investigated by quantifying interannual changes in their foraging behavior along two axes: spatial distribution, using kernel density analysis, and foraging habitat preference, using generalized additive mixed models and Bayesian mixed models. All four species were shown to respond behaviorally to environmental variability, but with substantial differences in their foraging strategies. WA was most general in its habitat use defined by sea surface height, eddy kinetic energy, wind speed, ocean floor slope, and sea-level anomaly, with individuals foraging in a range of habitats. In contrast, the three smaller albatrosses exploited two main foraging habitats, with habitat use varying between years. Generalist habitat use by WA and interannually variable use of habitats by GHA, SA, and LMSA would likely offer these species some resilience to predicted changes in climate such as warming seas and strengthening of westerly winds. However, future investigations need to consider other life-history stages coupled with demographic studies, to better understand the link between behavioral plasticity and population responses.

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.

Risk factor analysis for "diagnosis not reached" results from bovine samples submitted to British veterinary laboratories in 2013-2017.

Routine diagnostic data from laboratories are an important source of information for passive animal health surveillance. In Great Britain, the Veterinary Investigation Diagnosis Analysis (VIDA) database includes records of diagnostic submissions made to a nationwide network of 28 veterinary post-mortem facilities (VPFs). Data on "diagnosis not reached" (DNR), i.e. where submissions do not lead to a confirmed diagnosis, are analysed quarterly to look for unexpectedly high incidences of DNRs which could indicate the presence of a new or emerging disease in British livestock populations. The objective of the present study was to provide a better understanding about the reasons of DNR occurrence and to inform improvements of the coverage and reporting of this kind of surveillance data. A subset of the VIDA database comprising diagnostic submissions from cattle received from 2013 to 2017 (122,444 records) was analysed. A mixed-effects multivariable logistic regression model, accounting for clustering by farm and county, was used to investigate associations between potential predictors and DNR. The variables included in the model were: VPF identity, animal sex, age, production purpose, main presenting sign of the animal from which the sample was obtained, and sample submission type. The variable that showed the strongest association with DNR was the main presenting sign of the animal, followed by submission type, VPF identity, animal age, sex, and production purpose, in that order. Submissions from animals with abortion as the main clinical sign had the highest odds ratio (OR 21.6, 95 % confidence interval [CI] 19.6-23.9, with mastitis taken as the baseline). Submissions where neither carcasses (i.e. a whole dead animal provided for post-mortem examination) nor foetuses (i.e. an unborn dead animal) were provided had approximately 12 times the odds of being DNR, compared to submissions of a carcass (OR 11.6, 95 % CI 10.7-12.5). In addition, submission type and main presenting sign can be considered as important confounders in the association between the other predictors and DNR. This study has helped characterise DNR occurrence and suggests some possible improvements that could be made to the passive surveillance system investigated, such as encouraging greater carcase submission, accounting for identified issues when interpreting increased occurrence of DNR and further investigating reduced submissions or greater DNR occurrence in some geographical regions.

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds is critical for the control of this disease. Exploratory machine learning techniques can uncover complex non-linear relationships and interactions within disease causation webs, and enhance our knowledge of TB risk factors and how they are interrelated. Classification tree analysis was used to reveal associations between predictors of TB in England and each of the three surveillance risk areas (High Risk, Edge, and Low Risk) in 2016, identifying the highest risk herds. The main classifying predictor for farms in England overall related to the TB prevalence in the 100 nearest cattle herds. In the High Risk and Edge areas it was the number of slaughterhouse destinations and in the Low Risk area it was the number of cattle tested in surveillance tests. How long ago the last confirmed incident was resolved was the most frequent classifier in trees; if within two years, leading to the highest risk group of herds in the High Risk and Low Risk areas. At least two different slaughterhouse destinations led to the highest risk group of herds in England, whereas in the Edge area it was a combination of no contiguous low-risk neighbours (i.e. in a 1 km radius) and a minimum proportion of 6-23 month-old cattle in November. A threshold value of prevalence in 100 nearest neighbours increased the risk in all areas, although the value was specific to each area. Having low-risk contiguous neighbours reduced the risk in the Edge and High Risk areas, whereas high-risk ones increased the risk in England overall and in the Edge area specifically. The best classification tree models informed multivariable binomial logistic regression models in each area, adding statistical inference outputs. These two approaches showed similar predictive performance although there were some disparities regarding what constituted high-risk predictors. Decision tree machine learning approaches can identify risk factors from webs of causation: information which may then be used to inform decision making for disease control purposes.

Prevalence of and risk factors for acute laminitis in horses treated with corticosteroids.

A retrospective treated versus untreated study (study 1) and multicentre prospective cohort study (study 2) were undertaken to determine the prevalence of, and risk factors associated with, acute laminitis in horses treated with corticosteroids. All old treated with corticosteroids January-December 2014 (study 1) and January 2015-February 2017 (study 2) by two first opinion and referral hospitals in UK were included. Additionally, an untreated animal was identified for each treated animal (study one). Signalment, body condition (study 2 only), relevant medical history, primary condition, corticosteroid therapy prescribed and occurrence of acute laminitis during or within 14 days of cessation of corticosteroid treatment were recorded.For study 1, 205 cases and 205 controls were identified; two animals within each group (1 per cent) developed laminitis. In total, 1565 animals were included in study 2; laminitis period prevalence was 0.6 per cent (95 per cent CI 0.4 per cent to 1.2 per cent), with 10 cases in 1565 treated animals. There were significant associations between laminitis and breed (pony vs horse; p=0.01; univariable analysis only), the presence of a laminitis risk factor (history of laminitis or an underlying endocrinopathy; p<0.001; OR (95 per cent CI) 18.23 (5.05 to 65.87)) and body condition (overweight/obese vs not; p=0.04; OR (95 per cent CI) 4.0 (1.09 to 14.75)).

Cutaneous and Renal Glomerular Vasculopathy: What Do We Know so Far?

Cutaneous renal glomerular vasculopathy (CRGV), colloquially named "Alabama rot," is an emerging condition in the United Kingdom, previously reported from the United States and Germany. The cause of CRGV is not yet determined; no definitive link to an infectious agent has been made. Dogs diagnosed with CRGV initially develop cutaneous lesions, and a proportion of these dogs go on to manifest acute kidney injury, which may result in oligoanuric acute renal failure. Antemortem diagnosis is challenging given the lack of a specific diagnostic test, and confirmation of CRGV is therefore currently dependent on identification of thrombotic microangiopathy on renal histopathology.

Spatial modelling for low pathogenicity avian influenza virus at the interface of wild birds and backyard poultry.

Low pathogenicity avian influenza virus (LPAIV) is endemic in wild birds and poultry in Argentina, and active surveillance has been in place to prevent any eventual virus mutation into a highly pathogenic avian influenza virus (HPAIV), which is exotic in this country. Risk mapping can contribute effectively to disease surveillance and control systems, but it has proven a very challenging task in the absence of disease data. We used a combination of expert opinion elicitation, multicriteria decision analysis (MCDA) and ecological niche modelling (ENM) to identify the most suitable areas for the occurrence of LPAIV at the interface between backyard domestic poultry and wild birds in Argentina. This was achieved by calculating a spatially explicit risk index. As evidenced by the validation and sensitivity analyses, our model was successful in identifying high-risk areas for LPAIV occurrence. Also, we show that the risk for virus occurrence is significantly higher in areas closer to commercial poultry farms. Although the active surveillance systems have been successful in detecting LPAIV-positive backyard farms and wild birds in Argentina, our predictions suggest that surveillance efforts in those compartments could be improved by including high-risk areas identified by our model. Our research provides a tool to guide surveillance activities in the future, and presents a mixed methodological approach which could be implemented in areas where the disease is exotic or rare and a knowledge-driven modelling method is necessary.

Spatio-temporal and risk factor analysis of alleles related to Scrapie resistance in sheep in Great Britain before, during and after a national breeding program.

Certain genotypes of sheep have been identified to increase their susceptibility (the VRQ allele) or resistance (the ARR allele) to classical scrapie. This study's aim was to assess the spatio-temporal pattern of the ARR and VRQ alleles in Great Britain (GB) and to explore the risk factors associated to their presence. Data was collected from the GB scrapie active surveillance program, the sheep and goat inventory survey (GB census survey) and the agricultural survey for the period 2002-2015. Spatio-temporal trends of genotypes were assessed through the use of choropleth maps, spatial cluster and linear regression analyses. Multivariable mixed effect logistic regression analyses were performed to investigate the association between the resistant or susceptible genotypes, and breeds, farm purpose, animal purpose, surveillance stream, country location and herd size. The results show a significant upward trend in the frequency of most resistant ARR alleles (1.15% per year, 95%CI: 0.76-1.53) and significant downward trend of most susceptible VRQ alleles (-0.40% per year; 95%CI: -0.69 to -0.10]. The trend continues after the termination of the national scrapie plan in 2009. Breeds such as Herdwick (OR = 0,26; 95%CI: 0.14-0.46), Shetland (OR = 0.22; 95%CI: 0.13-0.39), Swaledale (OR = 0.58; 95%CI: 0.47-0.73), Scottish blackface (OR = 0.54; 95%CI: 0.41-0.71) and Welsh Montain (OR: 0.59; 95%CI: 0.44-0.79) were identified with lower odds ratios of having the resistant ARR allele, while Beulah speckled face (OR = 1.58; 95%CI: 1.04-2.41), Jacob (OR = 2.91; 95%CI: 1.33-6.40), Lleyn (OR = 2.94; 95%CI: 1.28-6.74) and Suffolk (OR = 2.19; 95%CI: 1.69-2.84) had higher odds ratios of having the ARR allele. Other risk factors associated to presence of ARR allele were finishing farms (OR = 1.15; 95%CI: 1.06-1.24) and farms in Scotland (OR = 0,78; 95%CI: 0.73-0.83) and in Lowland grazing areas (OR = 1.53; 95%CI: 1.39-1.67). Factors associated with presence the VRQ genotype were farms in Scotland (OR = 0,85; 95%CI: 0.77-0.93) and breeds such as Herdwick (OR = 2.2; 95%CI: 1.08-4.97), Shetland (OR = 4.12; 95%CI: 2.20-7.73) and Sweledale (OR = 1.51; 95%CI: 1.10-2.09). For the most resistant genotype, two significant spatial clusters were identified: a high-risk cluster in the south-west of GB (RR = 1.51, p < 0.001) and a low-risk cluster in northern GB (RR = 0.65, p < 0.001). For the most susceptible genotypes, one significant high-risk cluster was identified in Wales (RR = 2.89 and p = 0.013). Surveillance for classical scrapie could be improved with a risk-based approach by focussing on those areas and farm types identified to have higher frequency of VRQ alleles and less frequency of ARR alleles. Scrapie control strategies could focus on developing breeding programs on farms with Shetland, Herdwick and Swaledale breeds.

Spatiotemporal patterns and agroecological risk factors for cutaneous and renal glomerular vasculopathy (Alabama Rot) in dogs in the UK.

The annual outbreaks of cutaneous and renal glomerular vasculopathy (CRGV) reported in UK dogs display a distinct seasonal pattern (November to May) suggesting possible climatic drivers of the disease. The objectives of this study were to explore disease clustering and identify associations between agroecological factors and CRGV occurrence. Kernel-smoothed maps were generated to show the annual reporting distribution of CRGV, Kuldorff's space-time permutation statistic used to identify significant spatiotemporal case clusters and a boosted regression tree model developed to quantify associations between CRGV case locations and a range of agroecological factors. The majority of diagnoses (92 per cent) were reported between November and May while the number of regions reporting the disease increased between 2012 and 2017. Two significant spatiotemporal clusters were identified-one in the New Forest during February and March 2013, and one adjacent to it (April 2015 to May 2017)-showing significantly higher and lower proportions of cases than the rest of the UK, respectively, for the indicated time periods. A moderately significant high-risk cluster (P=0.087) was also identified in the Manchester area of northern England between February and April 2014. Habitat was the predictor with the highest relative contribution to CRGV distribution (20.3 per cent). Cases were generally associated with woodlands, increasing mean maximum temperatures in winter, spring and autumn, increasing mean rainfall in winter and spring and decreasing cattle and sheep density. Understanding of such factors may help develop causal models for CRGV occurrence.

Signalment risk factors for cutaneous and renal glomerular vasculopathy (Alabama rot) in dogs in the UK.

Seasonal outbreaks of cutaneous and renal glomerular vasculopathy (CRGV) have been reported annually in UK dogs since 2012, yet the aetiology of the disease remains unknown. The objectives of this study were to explore whether any breeds had an increased or decreased risk of being diagnosed with CRGV, and to report on age and sex distributions of CRGV cases occurring in the UK. Multivariable logistic regression was used to compare 101 dogs diagnosed with CRGV between November 2012 and May 2017 with a denominator population of 446,453 dogs from the VetCompass database. Two Kennel Club breed groups-hounds (odds ratio (OR) 10.68) and gun dogs (OR 9.69)-had the highest risk of being diagnosed with CRGV compared with terriers, while toy dogs were absent from among CRGV cases. Females were more likely to be diagnosed with CRGV (OR 1.51) as were neutered dogs (OR 3.36). As well as helping veterinarians develop an index of suspicion for the disease, better understanding of the signalment risk factors may assist in the development of causal models for CRGV and help identify the aetiology of the disease.