Juana Bianchini

and 6 more

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 their essential function in animal disease prevention, different international and national organizations have created their own aforementioned systems/tools. 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 their preferences, needs and constraints in respect of these tools. An online survey was conducted and answered by 213 respondents from 132 countries. The respondents were animal 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 is 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 was to produce risk assessment and preparedness in areas involving origin and spread of animal diseases. The features most sought after in risk assessment tools were pathways of introduction and spread assessment. The level of satisfaction was higher for the platform which is most used by the respondents. Thus, the platform choice is most likely influenced by its efficiency and functionality. Overall, these results could be taken into consideration when improving an already available platform, or when creating a new efficient tool.

Sarah Welby

and 2 more

Introduction: Despite eradication and control measures applied across Europe, bovine tuberculosis (bTB) remains a constant threat. In Belgium, after several years of bTB disease freedom status, routine movement testing, as currently practiced, revealed itself inadequate to detect some sporadic breakdown herds. The aim of this study was to strike the balance between cost and effectiveness of different surveillance system components to identify sustainable alternatives for early detection and substantiation of freedom of bTB while maintaining acceptance of these amongst the different animal health stakeholders. Methods: Stochastic iteration model was built to simulate, first, the expected current surveillance system performance in terms of sensitivity and specificity of detection. These results were then descriptively compared to observed field results. Secondly, the cost and effectiveness of simulated alternative surveillance components were quantified. To measure impact of key assumptions (i.e. regarding diagnostic tests and true prevalence), sensitivity analysis was performed. Results: Discrepancies between the predicted and observed performance of bTB surveillance in Belgium were observed. Secondly, simulated alternatives revealed that targeted IFN-γ as well serological testing with Antibody ELISA towards risk herds would enable increasing the overall cost and effectiveness of the Belgian bTB surveillance system. Sensitivity analysis showed that results remained constant despite modification of some key assumptions. Discussion: Performance of current bTB surveillance system performance in Belgium was questionable. This exercise highlighted that not only sensitivity, but specificity is a key driver for surveillance performance. The quantitative and participative conceptual framework revealed itself a useful tool to allow evidence-based decision making regarding future tuberculosis surveillance in Belgium, as required by the international standards.

Claude Saegerman

and 4 more

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.