Veterinaria Italiana (Journal)
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P8-07 Brucella canis in Great Britain: Cases, Case Definitions, Management and Control
No full textCanine brucellosis is commonly characterised by reproductive disturbances and discospondylitis in dogs. It is mainly caused by Brucella canis (B. canis), a zoonotic bacteria which is primarily transmitted through sexual contact between dogs and contact with infectious abortion material. Contact with other fluids have also been reported to transmit the bacteria, however, these are less infectious. Prior to 2017 no cases of canine brucellosis had been bacteriologically confirmed in Great Britain (GB) and serological evidence of infection was also exceptionally rare. In 2017 B. canis was isolated from two dogs (separate cases) imported from Eastern Europe, followed by a third bacteriologically confirmed case in 2018 and then a fourth larger case in 2020, also bacteriologically confirmed. Between January 2020-April 2022 there have been 58 cases in GB as determined primarily based on serology and epidemiology. Investigations have resulted in the testing of 171 dogs and 100 of these were serologically positive and, in combination with the epidemiological information, considered infected. Twelve were confirmed positive by bacteriology. Cases have been associated with dogs that have originated from Romania, Macedonia, Bosnia, Hungary, Afghanistan, South Africa, and Greece. GB have adopted a risk-based approach to determine the qualitative probability that a dog is infected and the likelihood of onward transmission of infection. The assigned probability alongside individual factors and wider implications informs the level of investigation required and the approach to controlling the spread of disease. To aid detection of cases in GB, from February 2021 positive tests for B. canis were made officially Reportable. So far, no domestic onward transmission of B. canis has been observed in GB dogs apart from one case in 2020 and one case in 2022. There is one confirmed case of human brucellosisdue to infection with B. canis (at the time of writing). Teams at the Animal and Plant Health Agency continue to work closely with colleagues from GB Public Health Agencies and specialist clinicians from the Brucella Reference Unit at Royal Liverpool & Broadgreen Hospital to control the disease and protect human and animal health
O1-1 The Global Spread of the Most Famous Brucella Species
No full textThe past decade has seen an explosion of genomic sequencing for Brucella, with over 1,110 genomes now available. However, the large majority of these genomes come from just two species, Brucella abortus and B. melitensis, which is no coincidence due to the ubiquity of these two Brucella and their pervasive impacts on livestock, wildlife, and humans worldwide. Phylogenomics can be used on contemporary isolates, as well as from ancient DNA from fossils, to understand the timing of spread and their evolution. The primary finding is that the current distribution of B. abortus and B. melitensis is intimately tied to human movement of livestock across the globe-as livestock get moved so too do their pathogens. Both B. abortus and B. melitensis have striking similarities to each other, linked to human colonization patterns but also have key, but unexplained differences. Brucella abortus has one successful lineage that is found throughout the world, but also contains considerable diversity of numerous and divergent lineages, especially in Africa and Asia. Brucella melitensis in contrast has three successful lineages but relatively little diversity outside of these three groups. This talk will compare and contrast Brucella genomes to help explain how human movement has shaped these two important Brucella species over the past few thousand years and continuing to today
P5-06 Development of inactivated Brucella abortus vaccines from Brucella abortus biovar 3
No full textBovine brucellosis caused by B. abortus is endemic in cattle in Bangladesh. It is a top priority zoonotic disease in Bangladesh. There is an urgent need to control brucellosis in livestock of Bangladesh. Although vaccination is employed in many countries to control bovine brucellosis but Brucella vaccines are not available to use in livestock in Bangladesh. The objective of this study was to develop inactivated B. abortus vaccines using B. abortus biovar 3 isolated from cattle in Bangladesh. Two inactivated B. abortus vaccine: B. abortus vaccine was prepared. Preclinical efficacy trail of the vaccines were conducted in mice. BALB/c mice at 6-8 weeks of age were immunized subcutaneously with B. abortus alum and oil adjuvant vaccines. Booster vaccine was administered at 28 days post vaccination (DPV). Challenge infection of vaccinated and control mice was given at 42 DPV with virulent B. abortus biovar 3. Sera were collected from five randomly selected mice at 7, 14, 21, 28, 35 and 42 DPV for detection of antibody response by rose Bengal plate test (RBPT), Indirect ELISA. Bacterial load in the spleen of mice were determined at 7 days post challenge. Cell mediated immune response (CMI) in vaccinated mice was measured by delayed type hypersensitivity (DTH) reaction. B. abortus specific antibody response was detected in 80% vaccinated mice by RBPT. The ELISA OD value of sera of alum and oil adjuvant vaccinated mice were (0.152±0.06 and 0.244±0.02),(0.155±0.02 and 0.252±0.003),(0.45±0.02 and 0.546±0.030), (0.65±0.01 and 0.575±0.009),(0.69±0.11 and0.696±0.005), (0.626±0.08 and 0.702±0.061) and (0.616±0.08) and 0.782±0.083) at 0, 7, 14, 21, 28, 35 and 42 DPV, respectively (p<0.05). Bacterial load of alum and oil adjuvant vaccinated mice (log105.64±0.43 cfu/g and and log105.35±0.50 cfu/g ) was significantly reduced as compared to unvaccinated control (log106.45±0.78 cfu/g) (p<0.05). Swelling of footpad of mice was observed (1.16±0.13 mm, 1.14±0.16 mm and 0.96± 0.10 mm at 24hr, 48hr and 72hr, respectively). Data of this study indicates that inactivated B. abortus vaccine induces both humoral and CMI response and confer protection in mice against virulent challenge infection. Field trail of the inactivated vaccines in dairy cattle is under progress
R10.3 Modelling transmission of Avian Influenza in wild birds using a spatiotemporal cellular automata model
No full textWithin the last 10 years, Denmark has faced an increasing number of Avian Influenza cases in wild birds and outbreaks on poultry farms, emphasizing the need to update national avian influenza prevention and control strategies. Highly Pathogenic Avian Influenza (HPAI) is transmitted over long distances by migratory wild birds, and wild birds can further spread the disease locally via their aggregation in suitable areas. With a coastline of more than 8,000 km, Denmark is an important stopover for migratory birds. Bird species belonging to the order Anseriformes have been the most commonly reported Avian Influenza virus positive species in recent years in Denmark.
This study aims to improve the understanding of HPAI transmission in migratory wild birds by developing a stochastic spatiotemporal epidemiological model. The model will predict HPAI prevalence in selected wild bird species over one year simulated period and identify hotspots and high-risk periods of transmission.
To date we have rasterized Denmark into 10 by 10 km grid cells. We have then combined 5 years of national and citizen science weekly count data on bird populations for five common bird species (two swan species, two geese species and one duck species) in each grid cell and extrapolated to grid cells with unknown counts using geographical and temporal variables and generalized linear mixed model regression. Following this, we built a mechanistic simulation model including three weekly steps; temporal migration of birds, a susceptible-infectious-removed (SIR) model with environmental transmission, and disease transmission due to bird dispersal between grid cells. The model will be parameterized using published data, expert opinions and literature estimates. Calibration and sensitivity analysis of main parameters, such as the infectious period and virus shedding rate of different bird species, will be implemented once the model is complete.
Preliminary results were obtained using model simulations for one iteration. The model outputs identified high-prevalence areas and periods, and the changes in simulated prevalence for the study period was compared to reported HPAI incidence in passively surveyed wild birds. We intend to use the spatio-temporal model to evaluate the risk of HPAI virus transmission and help Danish farmers and veterinary authorities to allocate resources to prevent potential outbreaks
R03.1 Contribution of climate change to the emergence of West Nile virus in Europe
No full textWest Nile virus (WNV) is an important mosquito-borne pathogen in Europe and although the causal relationship between climate change and its emergence on the continent has been reported, it has not been formally evaluated. Here, we examine whether WNV establishment in Europe can be attributed to climate change. For this purpose, we train and project ecological niche models for WNV considering historical, future, and counterfactual climate data, the latter corresponding to a hypothetical climate in a world without climate change. We show an increase in the ecologically suitable area for WNV under the historical climate evolution, whereas this area remains largely unchanged throughout the last century in a no-climate-change counterfactual. Our analyses therefore point towards climate change as one of the major drivers of the increased risk of WNV circulation in Europe, and further allows discussing potential scenarios for the future evolution of the areas at risk
R01.2 Poultry intensification and emergence of Highly Pathogenic Avian Influenza
No full textThe global spread of Highly Pathogenic Avian Influenza (HPAI) following the emergence of the Goose/Guangdong H5N1 subtype in 1996 in China has raised concerns regarding its mechanisms and ecological niches. In that context, our study investigates the impact of poultry intensification on HPAI incidence, an aspect that has so far received limited attention (Gilbert et al., 2018). Specifically, we aimed to analyze the impact of global intensification of poultry production in the occurrence of Low Pathogenic Avian Influenza (LPAI) to Highly Pathogenic (HPAI) conversions and to predict the probability of conversion events at the country level.
We compiled a dataset of HPAI conversions from 1959 to 2022 (Dhingra et al., 2017), focusing on primary emergence reports while excluding secondary spread within epidemics. Poultry distribution data was obtained from the Gridded Livestock of the World (GLW). Generalized linear mixed models (GLMM) and Integrated Nested Laplace Approximation (INLA) were used to predict conversion events based on proxy variables for poultry intensification: poultry density, output/input ratio (animal production efficiency), and the total stock of poultry.
Our preliminary results show that the large majority of the detected conversion events took place in high-income countries (with highly intensified poultry production systems). Europe remained the center of conversions with n=18 followed by USA with n=9. In Europe, the UK, Germany, The Netherlands, and Italy depict the highest probability of having at least one conversion event. Finally, the output/input ratio showed to be the best predictor of conversion events.
This study highlights the overlooked relationship between poultry intensification and the emergence of HPAI. The concentration of conversion events in high-income countries with intensified poultry production systems suggests their susceptibility to HPAI. Further research will be needed to comprehensively examine the poultry intensification pressures on avian influenza emergence and develop effective intervention measures. These findings might provide valuable insights for policymakers, public health officials, and the poultry industry to mitigate the risks associated with intensified poultry production and safeguard global public health and poultry industries
P02.2 The development and impact of an online bovine TB system for GB - information bovine TB (ibTB)
No full textwww.ibTB.co.uk plots the location of all cattle herds in England and Wales affected by Bovine Tuberculosis (bTB) in the last 10 years. It was developed as a tool to inform farmers about the bTB risks in their area and help them take proportionate steps to reduce the threat to their herds.
Prior to its launch in 2015, information on bTB incidents was viewed as personal, confidential and not to be shared. There was therefore limited information available to farmers about local bTB risks and to support livestock purchasing decisions. However, in 2015 Defra and the Welsh Government (WG) in consultation with the farming industry decided that releasing bTB data was integral to their long-term strategies for the eradication of bTB and in line with their open data policy (#OpenDefra).
To enable the sharing of bTB data, both Defra and the WG needed to change legislation (their respective TB Orders) to allow the publishing of information on bTB affected herds. Once these legislative hurdles were overcome, the decision was made to create a spatial mapping system - Defra and WG had seen the benefits of various internal Geographical Information Systems (GIS) already in use. The specification for ibTB was underpinned by two key principles. a) The data published should be accurate, timely and contain no personal information and b) The system should be simple to use, and should be searchable by the farm identifier (County Parish Holding) and postcode.
In 2018 the development team held a series of meetings with farming groups across England and Wales to better understand their requirements for ibTB and in particular to assess the system’s suitability as a portal for information to support Informed Responsible Trading (IRT). As well as confirming that ibTB was an appropriate tool for the display of IRT information, the survey identified distinct requirements for several subsets of users, such as farmers in high and low bTB risk areas, veterinarians and TB advisors. These requirements have been distilled into a series of staged system improvements, which were released in tranches up to October 2021.
The impacts of ibTB are difficult to gauge, because as an open access site, there is currently no way of tracking users and linking to their other bTB data to see if it is affecting their behaviours and reducing their herd’s risk of contracting bTB. Usage of the system has steadily increased over time and now stands at around 800 hits/day. The link to ibTB via a major cattle trading app provides about half the traffic, which shows that the system is being used to inform farmer trading.
P06.1 Production of risk maps for ASF at a local level through the analysis of relevant epidemiological data
No full textAfrican swine fever (ASF) poses a significant threat to the global pig industry, with the disease having gradually expanded over the past decade worldwide. Once introduced to the wild boar population, the virus can establish itself, making it challenging to control it across extensive geographical areas. To facilitate the implementation of effective control measures, it is advantageous to classify administrative units based on the risk of ASF virus introduction and transmission. However, it should be noted that a key limitation in implementing control actions involving wildlife is the lack of detailed data on wild populations.
In this study, we classified the municipalities of Lombardy and Emilia-Romagna regions (Northern Italy) by evaluating the following parameters: i) the risk of ASF spread in the pig sector (low, medium, high), determined as a combination of pig density (number of holdings and heads) and pig movements (Tamba et al., 2020); ii) a habitat suitability index (HSI) for wild boar (ranging from 0 to 10), calculated as the geometric mean of suitability values assigned to land cover, elevation and slope (Qin et al., 2015); iii) the density of hunted wild boar per km2; iv) the presence of protected natural areas. The HSI and wild boar density were categorized into three classes, as the risk of ASF spread, so that the three parameters can be summed. The low risk class was assigned to HSI values ≤2 and to densities ≤1; the medium risk class to HSI values between 2 and 6, and densities between 1 and 4; the high risk class to HSI values >6 and densities ≥4. To the three classes were assigned increasing score of 0 (low), 0.5 (medium) and 1 (high). The sum of these scores at Municipality level was multiplied by 1.5, if a protected natural area is present.
The final score ranged between 0 and 4.5, and the corresponding risk classes were defined as follows: low (score ≤1), medium (score ≤2), and high (score is >2). The 1836 municipalities included in this study were classified as follows in terms of risk: 161 (9%) were classified as high risk, 248 (14%) as medium and 1427 (78%) as low. We noted that for Emilia-Romagna, the municipalities (330) were relatively evenly distributed across the three risk classes (about 33% in each class). Municipalities with higher or medium risk were concentrated in the hilly part of the region, with some exceptions in the lowlands due to a high presence of pig holdings.
This classification system appears to be useful for prioritizing intervention measures to control the wild boar population and/or improve biosecurity and surveillance in pig holdings
R10.5 Assessing the risk of arbovirus outbreaks in non-endemic regions
No full textThe threat posed by mosquito-borne viruses (arboviruses) causing Dengue (DENV), Zika (ZIKV), Chikungunya (CHIKV), Yellow Fever (YFV), among other widespread viral infections, represent a global public health concern. In European countries, like Spain, Italy, or France, factors such as global warming, increased human mobility (locally and globally across different latitudes where such diseases are endemic), the presence and spreading of invasive mosquitoes (such as Aedes albopictus), and the existence of confirmed non-autochthonous viremic cases have the potential to cause significant disease outbreaks in disease free regions, as it was reported in France where autochthonous Dengue cases have been recently identified.
Here, we introduce a quantitative method for risk assessment of outbreaks of diseases susceptible to transmission by Aedes mosquitoes in a non-endemic area. Our proposed method is built on the basis of a mathematical model we developed: a modified version of the standard SIRUV compartmental model (that couples the human and mosquito dynamics), adapted to meet the specific features of non-endemic areas. By using only the latest entomological data (related to the vector abundance), epidemiological data (confirmed imported and autochthonous cases) and population statistics (population density census), the risk can be estimated and different epidemiological scenarios can be evaluated. Finally, a GIS dashboard has been implemented (using data from the Basque Country, Spain), envisioned as a prototype tool to inform and guide the decision-making by the public health authorities
R10.1 Disentangling the role of wild bird species in Avian Influenza transmission to poultry
No full textMigratory waterfowl are widely acknowledged as the primary source of avian influenza (AI) virus introduction into poultry. However, recent studies have challenged the assumption of direct interactions between waterfowl and poultry, revealing a more complex interface (Shriner&Root, 2020; Verhagen et al., 2021). While waterfowl are crucial for maintaining and amplifying AI viruses in nature, other species may function as the actual bridges for introducing AI into the poultry sector (Caron et al., 2015). However, the nature of this wild-domestic interface remains elusive, leaving gaps in understanding which species play the bridging role.
An ornithocoenosis study was conducted in northern Italy between January and December 2019, in the area with the highest occurrence of Highly Pathogenic AI (HPAI) outbreaks during the 2017-2018 H5N8 epidemic. The study focused on ten poultry farms: five fattening turkey, four laying hen, and one duck premises. Three census transects were established within one kilometre from each farm, and visited biweekly, while two camera-traps per holding were installed adjacent to the sheds. A Bayesian Adaptive Regression Trees (BART) approach was adopted to define a series of Species Distribution Models (SDM) to predict the favourability of species detected by camera-trapping. These results were then input as geographical raster layers into further BART-SDMs to produce risk maps for AI and determine which wild bird species significantly contributed to the occurrence of the 2017-2018 H5N8 HPAI outbreaks in northern Italy.
The transect survey revealed a marked diversity despite the environmental and climatic homogeneity, with approximately 150 species detected. However, only 41 of these were also observed by camera-trapping in proximity to the farms, suggesting a fragmented community. The likelihood of observing an AI outbreak resulted positively associated with the presence of Ardea alba, Bubulcus ibis, Columba livia and Phasianus colchicus, and negatively with the Falco peregrinus, Phoenicurus phoenicurus and Picus viridis. In particular, the contribution of pheasants to the probability of observing AI outbreaks was likely due to the release of birds for repopulation or hunting, which might create bridges between wild and domestic populations. The tendency of released game birds to seek out anthropized areas, such as poultry farms, in search of food, further corroborates the hypothesis.
The study shed light on the intricate interface between wild birds and poultry in the dynamics of AI spread. Our results stressed the need to account for the role of both aquatic and non-aquatic bird species in the introduction and/or inter-farm spread of AIVs, emphasising the potential risks associated with wetland proximity and the impact of human activities, such as releasing game birds, on the risk of disease spread (Shriner&Root, 2020). These findings may be used to inform targeted surveillance activities and prevention strategies to mitigate the AI threat in domestic birds