Lumpy Skin Disease: A Systematic Review of Mode of Transmission, Risk of Emergence and Risk Entry Pathway.

The spread of lumpy skin disease (LSD) to free countries over the last 10 years, particularly countries in Europe, Central and South East Asia, has highlighted the threat of emergence in new areas or re-emergence in countries that achieved eradication. This review aimed to identify studies on LSD epidemiology. A focus was made on hosts, modes of transmission and spread, risks of outbreaks and emergence in new areas. In order to summarize the research progress regarding the epidemiological characteristics of LSD virus over the last 40 years, the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement guidelines were followed, via two databases, i.e., PubMed (biomedical literature) and Scopus (peer-reviewed literature including scientific journals, books, and conference proceedings). A total of 86 scientific articles were considered and classified according to the type of epidemiological study, i.e., experimental versus observational. The main findings and limitations of the retrieved articles were summarized: buffaloes are the main non-cattle hosts, the main transmission mode is mechanical, i.e., via blood-sucking vectors, and stable flies are the most competent vectors. Vectors are mainly responsible for a short-distance spread, while cattle trade spread the virus over long distances. Furthermore, vaccine-recombinant strains have emerged. In conclusion, controlling animal trade and insects in animal transport trucks are the most appropriate measures to limit or prevent LSD (re)emergence.

First Expert Elicitation of Knowledge on Drivers of Emergence of Bovine Besnoitiosis in Europe.

Bovine besnoitiosis (BB) is a chronic and debilitating parasitic disease in cattle caused by the protozoan parasite Besnoitia besnoiti. South European countries are affected and have reported clinical cases of BB. However, BB is considered as emerging in other countries/regions of central, eastern and northern Europe. Yet, data on drivers of emergence of BB in Europe are scarce. In this study, fifty possible drivers of emergence of BB in cattle were identified. A scoring system was developed per driver. Then, the scoring was elicited from eleven recognized European experts to: (i) allocate a score to each driver, (ii) weight the score of drivers within each domain and (iii) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order of importance. Regression tree analysis was used to group drivers with comparable likelihoods to play a role in the emergence of BB in cattle in Europe. Finally, robustness testing of expert elicitation was performed for the seven drivers having the highest probability to play a key role in the emergence of BB: i.e., (i) legal/illegal movements of live animals from neighbouring/European Union member states or (ii) from third countries, (iii) risk of showing no clinical sign and silent spread during infection and post infection, (iv) as a consequence, difficulty to detect the emergence, (v) existence of vectors and their potential spread, (vi) European geographical proximity of the pathogen/disease to the country, and (vii) animal density of farms. Provided the limited scientific knowledge on the topic, expert elicitation of knowledge, multi-criteria decision analysis, cluster and sensitivity analyses are very important to prioritize future studies, e.g., the need for quantitative import risk assessment and estimation of the burden of BB to evidence and influence policymaking towards changing (or not) its status as a reportable disease, with prevention and control activities targeting, firstly, the top seven drivers. The present methodology could be applied to other emerging animal diseases.

Assessing the use of animal health platforms: User's needs, preferences and constraints.

Animal health information systems or risk analysis tools are indispensable not only for animal health surveillance, but also to observe the evolution and risk of disease incursion into a disease-free area. Given the various information that can be derived from these both animal information systems and risk analysis tools, different international and national organizations have customized or created their own systems/tools to provide specific information for use by the respective countries. Moreover, with the increase of technology and data storage, they have become more accessible and widely used by professionals in animal and human health sciences. This study aimed to establish user's preferences, needs and constraints in respect of these animal information systems and risk analysis tools. An online survey was conducted and answered by 213 respondents from 132 countries. The respondents were animal health or public health professionals in different employment sectors (mostly in government, research and university institutions) and various fields of competency (highest for animal and public health). The majority of respondents used the animal health information systems frequently and on a weekly basis, with prevention measures of diseases being regarded as the most useful information. Descriptive epidemiology was more used/needed than analytical epidemiology. Risk analysis was performed by the majority of the respondents (70%), using a qualitative approach more than a quantitative or semi-qualitative. The primary objectives were to produce risk assessment and preparedness in areas involving origin and spread of animal diseases. The features most sought after in risk analysis tools were pathways of introduction and spread assessment. The level of satisfaction was higher for the platform which is most used by the respondents. Overall, these results could be taken into consideration when improving an already available platform, or when creating a new efficient tool.

First expert elicitation of knowledge on drivers of emergence of the COVID-19 in pets.

Infection with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) induces the coronavirus infectious disease 19 (COVID-19). Its pandemic form in human population and its probable animal origin, along with recent case reports in pets, make drivers of emergence crucial in domestic carnivore pets, especially cats, dogs and ferrets. Few data are available in these species; we first listed forty-six possible drivers of emergence of COVID-19 in pets, regrouped in eight domains (i.e. pathogen/disease characteristics, spatial-temporal distance of outbreaks, ability to monitor, disease treatment and control, characteristics of pets, changes in climate conditions, wildlife interface, human activity, and economic and trade activities). Secondly, we developed a scoring system per driver, then elicited scientific experts (N = 33) to: (a) allocate a score to each driver, (b) weight the drivers scores within each domain and (c) weight the different domains between them. Thirdly, an overall weighted score per driver was calculated; drivers were ranked in decreasing order. Fourthly, a regression tree analysis was used to group drivers with comparable likelihood to play a role in the emergence of COVID-19 in pets. Finally, the robustness of the expert elicitation was verified. Five drivers were ranked with the highest probability to play a key role in the emergence of COVID-19 in pets: availability and quality of diagnostic tools, human density close to pets, ability of preventive/control measures to avoid the disease introduction or spread in a country (except treatment, vaccination and reservoir(s) control), current species specificity of the disease-causing agent and current knowledge on the pathogen. As scientific knowledge on the topic is scarce and still uncertain, expert elicitation of knowledge, in addition with clustering and sensitivity analyses, is of prime importance to prioritize future studies, starting from the top five drivers. The present methodology is applicable to other emerging pet diseases.

First expert elicitation of knowledge on drivers of emergence of influenza D in Europe.

The influenza D virus (IDV) was first identified and characterized in 2011. Considering the virus' zoonotic potential, its genome nature (segmented RNA virus), its worldwide circulation in livestock and its role in bovine respiratory disease, an increased interest is given to IDV. However, few data are available on drivers of emergence of IDV. We first listed fifty possible drivers of emergence of IDV in ruminants and swine. As recently carried out for COVID-19 in pets (Transboundary and Emerging Diseases, 2020), a scoring system was developed per driver and scientific experts (N = 28) were elicited to (a) allocate a score to each driver, (b) weight the drivers' scores within each domain and (c) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order. Drivers with comparable likelihoods to play a role in the emergence of IDV in ruminants and swine in Europe were grouped using a regression tree analysis. Finally, the robustness of the expert elicitation was verified. Eight drivers were ranked with the highest probability to play a key role in the emergence of IDV: current species specificity of the causing agent of the disease; influence of (il)legal movements of live animals (ruminants, swine) from neighbouring/European Union member states and from third countries for the disease to (re-)emerge in a given country; detection of emergence; current knowledge of the pathogen; vaccine availability; animal density; and transport vehicles of live animals. As there is still limited scientific knowledge on the topic, expert elicitation of knowledge and multi-criteria decision analysis, in addition to clustering and sensitivity analyses, are very important to prioritize future studies, starting from the top eight drivers. The present methodology could be applied to other emerging animal diseases.

Improving laboratory diagnostic capacities of emerging diseases using knowledge mapping.

Over the last decade, European countries faced several emerging and re-emerging animal diseases as well as zoonotic diseases. During these episodes, the laboratory diagnostic capabilities were a key factor to rapidly control and/or eradicate them. Because of the associated socio-economic and health consequences, it is crucial to react rapidly and efficiently, not only during crisis but also in peacetime (i.e. preparedness). However, to date, there is no published method to identify diseases with diagnostic gaps and to prioritize assays to be implemented. This study was conducted based on the outcome of a prioritization exercise in which 29 epizootic and exotic diseases with high risk of emergence or re-emergence in Belgium (Bianchini et al., [2020] Transboundary and Emerging Diseases, 67(1), 344-376) were listed. Knowledge mapping was used to visualize and identify gaps in the diagnostic procedures for different epidemiological scenarios at national level. To fill these gaps, an overview of diagnostic capabilities at national and international level (laboratories and kits providers or manufacturers) as well as the published assays in the scientific literature and the prescribed assays by international institutions and kits providers was carried out. The outcome of this study revealed the usefulness of knowledge mapping as a tool to identify gaps and ultimately gain insight on alternatives for better preparedness and responsiveness. While this exercise was limited to Belgium, we believe this exercise can benefit other countries and thereby enhancing knowledge sharing and collaboration to increase diagnostic capabilities for a common list of (re-) emerging diseases in crisis situation.

Prioritization of livestock transboundary diseases in Belgium using a multicriteria decision analysis tool based on drivers of emergence.

During the past decade, livestock diseases have (re-)emerged in areas where they had been previously eradicated or never been recorded before. Drivers (i.e. factors of (re-)emergence) have been identified. Livestock diseases spread irrespective of borders, and therefore, reliable methods are required to help decision-makers to identify potential threats and try stopping their (re-)emergence. Ranking methods and multicriteria approaches are cost-effective tools for such purpose and were applied to prioritize a list of selected diseases (N = 29 including 6 zoonoses) based on the opinion of 62 experts in accordance with 50 drivers-related criteria. Diseases appearing in the upper ranking were porcine epidemic diarrhoea, foot-and-mouth disease, low pathogenic avian influenza, African horse sickness and highly pathogenic avian influenza. The tool proposed uses a multicriteria decision analysis approach to prioritize pathogens according to drivers and can be applied to other countries or diseases.

Evaluation of Immunofluorescence Antibody Test Used for the Diagnosis of Canine Leishmaniasis in the Mediterranean Basin: A Systematic Review and Meta-Analysis.

With an expected sensitivity (Se) of 96% and specificity (Sp) of 98%, the immunofluorescence antibody test (IFAT) is frequently used as a reference test to validate new diagnostic methods and estimate the canine leihmaniasis (CanL) true prevalence in the Mediterranean basin. To review the diagnostic accuracy of IFAT to diagnose CanL in this area with reference to its Se and Sp and elucidate the potential causes of their variations, a systematic review was conducted (31 studies for the 26-year period). Three IFAT validation methods stood out: the classical contingency table method, methods based on statistical models and those based on experimental studies. A variation in the IFAT Se and Sp values and cut-off values was observed. For the classical validation method based on a meta-analysis, the Se of IFAT was estimated in this area as 89.86% and 31.25% in symptomatic and asymptomatic dogs, respectively. The Sp of IFAT was estimated in non-endemic and endemic areas as 98.12% and 96.57%, respectively. IFAT can be considered as a good standard test in non-endemic areas for CanL, but its accuracy declines in endemic areas due to the complexity of the disease. Indeed, the accuracy of IFAT is due to the negative results obtained in non-infected dogs from non-endemic areas and to the positive results obtained in sera of symptomatic dogs living in endemic areas. But IFAT results are not unequivocal when it comes to determining CanL infection on asymptomatic dogs living in endemic areas. Statistical methods might be a solution to overcome the lack of gold standard, to better categorize groups of animals investigated, to assess optimal cut-off values and to allow a better estimate of the true prevalence aiming information on preventive/control measures for CanL.

The impact of the genotype on the prevalence of classical scrapie at population level.

Total number and genotypes of animals in holdings selected for the genotype & cull option in the Compulsory Scrapie Flock Scheme (CSFS) in Great Britain were extracted from the National Scrapie Plan data warehouse. The association between various genotype-related measures and scrapie prevalence infection was tested using zero-inflated negative binomial models with the counts of positive cases as dependent variable, and country, number of flocks in the scheme, flock size, surveillance source and the following genotype-related measurements: the centered-log ratios (clr) of the 15 genotypes, of the proportions of the 5 alleles at codons 136, 154 and 171, of the proportions of the 5 NSP types, and two flock-susceptibility risk indicators, as explanatory variables. A total of 319341 genotyped animals from 168 holdings were included in the analysis. An increased proportion of the ARR/ARR genotype corresponded to a decrease in the number of scrapie cases. ARR/AHQ, AHQ/VRQ, ARH/VRQ and ARQ/VRQ genotypes, NSP type V, ARH, ARQ, AHQ and VRQ alleles and the low and high-susceptibility risk indicators are all associated with an increase risk in the number of scrapie cases.Regardless the management practices; the increased susceptibility that the non-ARR alleles confer on an individual could be extrapolated at the population level. Increasing prevalence of ARR allele reduces the overall risk of scrapie at population level. At genotype level, the VRQ/VRQ genotype, present a very low frequency in the study population, seems to play a residual effect in the overall risk of scrapie in a flock.