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.

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.

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.

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.

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.

Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors.

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north-south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches.

Skin disease in captive bats: results of an online survey of zoos and rehabilitators in Europe, North America and Australasia.

BACKGROUND: Bats may be held captive in zoos and breeding programmes, and for rehabilitation due to illness, abandonment or injury. OBJECTIVES: To describe the frequency and characteristics of skin disease in captive bats. METHODS: Zoos (n = 164) in Europe, North America, Australia and New Zealand, Wildlife Disease Association members and rehabilitators were invited to complete online questionnaires on skin lesions and housing. Associations between lesion type and site, frequency, species, age, suspected cause and season, and their association with housing in zoos were tested using chi-squared and two-sample z-tests. RESULTS: Skin lesions were seen by 38.5% (15 of 39) of responding zoos and more frequently by rehabilitators (66.7%, 18 of 27; P = 0.024). Of the total of 153 lesions of any type reported by zoos and rehabilitators, almost two thirds occurred on the pinnae (49 of 153, 32%) or wing membranes (45 of 153, 29%). Amongst pinnal lesions, crusting (27%), swelling and redness (25%) and necrosis (20%) were most frequent. In zoos, pinnal (P = 0.001) and wing lesions (P = 0.045) were associated with "season", being more common in winter. Pruritus was rare but more often reported from rehabilitation centres (12 of 77 observed lesions) than from zoos (1 of 76) (P = 0.0015). Lesions most often affected adult and geriatric bats in zoos, and juveniles and adults in rehabilitation. Eight respondents reported that skin disease necessitated euthanasia in individual bats. There was no significant association between type of housing and lesions. CONCLUSION: Pinnal and wing lesions were common in captive bats, often with necrosis. Further research into the causes is needed to improve health and welfare of captive bats.

Spatial Heterogeneity of Habitat Suitability for Rift Valley Fever Occurrence in Tanzania: An Ecological Niche Modelling Approach.

BACKGROUND: Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. MATERIALS AND METHODS: Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. PRINCIPAL FINDINGS: Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). CONCLUSION/SIGNIFICANCE: The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics.

Spatial and temporal epidemiological analysis in the Big Data era.

Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle large datasets faster than classical regression approaches, are now also used to analyse spatial and spatio-temporal data. Multi-criteria decision analysis methods have gained greater acceptance, due in part, to the need to increasingly combine data from diverse sources including published scientific information and expert opinion in an attempt to fill important knowledge gaps. The opportunities for more effective prevention, detection and control of animal health threats arising from these developments are immense, but not without risks given the different types, and much higher frequency, of biases associated with these data.

Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems.

During the last 30years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS, the collection of georeferenced disease data has moved beyond the use of handheld GPS devices and there now exist numerous sources of crowdsourced georeferenced disease data such as that available from georeferencing of Google search queries or Twitter messages. In addition, cartography has moved beyond the realm of professionals to crowdsourced mapping projects that play a crucial role in disease control and surveillance of outbreaks such as the 2014 West Africa Ebola epidemic. This paper provides a comprehensive review of a range of innovative sources of spatial animal and human health data including data warehouses, mHealth, Google Earth, volunteered geographic information and mining of internet-based big data sources such as Google and Twitter. We discuss the advantages, limitations and applications of each, and highlight studies where they have been used effectively.

Modeling habitat suitability for occurrence of highly pathogenic avian influenza virus H5N1 in domestic poultry in Asia: a spatial multicriteria decision analysis approach.

Risk maps are one of several sources used to inform risk-based disease surveillance and control systems, but their production can be hampered by lack of access to suitable disease data. In such situations, knowledge-driven spatial modeling methods are an alternative to data-driven approaches. This study used multicriteria decision analysis (MCDA) to identify areas in Asia suitable for the occurrence of highly pathogenic avian influenza virus (HPAIV) H5N1 in domestic poultry. Areas most suitable for H5N1 occurrence included Bangladesh, the southern tip and eastern coast of Vietnam, parts of north-central Thailand and large parts of eastern China. The predictive accuracy of the final model, as determined by the area under the receiver operating characteristic curve (ROC AUC), was 0.670 (95% CI 0.667-0.673) suggesting that, in data-scarce environments, MCDA provides a reasonable alternative to the data-driven approaches usually used to inform risk-based disease surveillance and control strategies.

Spatial modelling of disease using data- and knowledge-driven approaches.

The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution.

Malassezia pachydermatis and M nana predominate amongst the cutaneous mycobiota of Sphynx cats.

Carriage of Malassezia species yeasts in healthy Sphynx cats was compared with that in Devon Rex cats (DRC), Cornish Rex cats (CRC) and domestic shorthair (DSH) cats. Swab samples from the external ear, anus and claw folds, and contact plate samples from the axillae and groins, were incubated on modified Dixon's agar at 32°C for 7 days. Malassezia species were isolated from all 18 Sphynx cats; M pachydermatis accounted for 118/140 isolates. Of 20 isolates of M nana, 16 were recovered from the ear canal. M slooffiae was isolated from the claw fold of one cat and the left groin of another. The high counts of M pachydermatis obtained from the axillae, groins and claw folds of the Sphynx cats exceeded those of healthy DSH, CRC and DRC; axillary populations were comparable to those of seborrhoeic DRC. These data support recent reports of high Malassezia species colonisation in Sphynx cats.

Classical sheep scrapie in Great Britain: spatial analysis and identification of environmental and farm-related risk factors.

BACKGROUND: Previous studies suggest that the spatial distribution of classical sheep scrapie in Great Britain is uneven and that certain flock characteristics may be associated with occurrence of the disease. However, the existence of areas of high and low disease-risk may also result from differences in the spatial distribution of environmental characteristics. In this study we explored the spatial pattern of classical scrapie in Great Britain between 2002 and 2005 and investigated the association between disease occurrence and various environmental and farm-related risk factors. RESULTS: Exploratory spatial analysis: South Wales was found to have a higher density of scrapie-positive farms than the rest of Great Britain. In addition, a small cluster of high-risk farms was identified in the center of this region in which clustering of scrapie-positive farms occurred up to a distance of approximately 40 km. SPATIAL MODELLING: A mixed-effects regression model identified flock-size and soil drainage to be significantly associated with the occurrence of scrapie in England and Wales (area under the curve (AUC) 0.71 +/- 0.01, 95% CI 0.68 - 0.74). The predictive risk map based on the estimated association between these factors and disease occurrence showed most of Wales to be at risk of being confirmed positive for scrapie with areas of highest risk in central and south Wales. In England, areas with the highest risk occurred mainly in the north and the midlands. CONCLUSION: The observed distribution of scrapie in Great Britain exhibited a definite spatial pattern with south Wales identified as an area of high occurrence. In addition both flock (flock size) and environmental variables (soil drainage) were found to be significantly associated with the occurrence of the disease. However, the model's AUC indicated unexplained variation remaining in the model and the source of this variation may lie in farm-level characteristics rather than spatially-varying ones such as environmental factors.

Prevalence of methicillin-resistant Staphylococcus aureus among staff and pets in a small animal referral hospital in the UK.

OBJECTIVES: The occurrence of methicillin-resistant Staphylococcus aureus (MRSA) and the possible relatedness between human and animal isolates were investigated among veterinary staff and hospitalized animals in a referral small animal hospital in the UK. METHODS: A total of 300 swab samples were taken from nasal and oral mucosae of 78 veterinary staff, 45 dogs, 12 cats and from 30 environmental surfaces. Staphylococci were isolated by selective enrichment and characterized by biochemical tests and antimicrobial disc susceptibility testing. MRSA isolates were genotypically confirmed by PCR and typed by PFGE. RESULTS: MRSA was isolated from 14 staff (17.9%), four dogs (9%), and three environmental sites (10%) yielding a total of 28 MRSA isolates. PFGE analysis revealed that most MRSA isolates were indistinguishable (56%) or closely related (26%) to EMRSA-15, one of the two epidemic MRSA strains dominant in UK hospitals. Like EMRSA-15, the predominant strain isolated from staff, dogs and environmental sites was resistant to fluoroquinolones in addition to all beta-lactams. CONCLUSIONS: The study provides evidence of EMRSA-15 mucosal carriage in veterinary staff and hospitalized dogs, with the risk of MRSA carriage in veterinary staff being significantly higher than reported for the UK healthy community. EMRSA-15 was predominant in the hospital environment, including humans, dogs, and inanimate objects, but the mode by which the strain was introduced and spread remains uncertain.