Understanding hobby beekeepers’ perception of risks affecting bee health and mortality is essential to analyse the reasons for adopting or rejecting good management practices. A perception survey on how beekeepers perceive and manage risks related to climate change, Varroa infestation, management practices, and pesticide exposure was designed and launched online. This unpreceded sociological survey involved 355 beekeepers spread all over Belgium. A two-sample t-test with unequal variances comparing beekeepers with colony mortality rates below or exceeding the acceptable level, i.e. <10% and ≥10%, indicates that beekeepers (N=213), with colony mortality rates <10% generally have greater levels of perceived risk and the benefits of action that lead to increased motivation to act in better ways. The results of this survey highlight the importance of taking socio-economic determinants into account in any risk mitigation strategy associated with bee mortality when dealing with hobby beekeepers.
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 carnivore domestic 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 experts (N = 33) to: (i) allocate a score to each driver, (ii) weight the drivers scores within each domain and (iii) 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.