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.

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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.

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.

Around a decade ago, a new virus was isolated from pigs with influenza-like illness in Oklahoma, the USA (Hause et al., 2014;Hause et al., 2013). This enveloped virus, named influenza D virus (IDV) with a segmented single-stranded negative sense ribonucleic acid (RNA) genome, now belongs to the new Deltainfluenzavirus genus of the Orthomyxoviridae family (https://talk.ictvo nline.org/ictv-repor ts/ictv_online_repor t/). Since then, IDV was detected in a large range of hosts worldwide, that is cattle, small ruminants, swine, camelids and equines (only antibody detection for these last two species) in America,