EuFMD

Dataset visualization has now become the most popular and user-friendly tool for enabling audiences to capture data easily in a visual context. There are varied tools available for data intelligence and analytics which use an interactive environment to explore datasets. Digitalization of animal disease outbreak data using interactive visualization tools allows end-users to gain insights into vast amounts of data by clear display of disease patterns, including spatial and temporal trends, and provides direction for interventions needed to enhance disease prevention and control. This paper focuses on the interactive presentation of FMD datasets collected from SEACFMD Members and visualized using Microsoft Power Business Intelligence (BI). FMD outbreak data were mined from various available resources, then analyzed by location, the species affected, FMDV subtypes detected during 2019-2021, and visualized using figures such as graphs and maps in an interactive tool.

Following an important outbreak of Lumpy Skin Disease in Israel, a question raised concerning the possible use of drones for the disease surveillance. The idea of using drones to assist in finding affected herds in the field and surveil affected herds seemed logical and useful. A pilot study has been done to evaluate the pros and cons to this thought.

Sensors have become ubiquitous in our current world and the livestock farming sector offers multiple research avenues for the application of sensor technology, from early disease detection to virtual fencing. Animal health surveillance in Scotland currently relies on post-mortem examinations of animals and on data derived from laboratory submitted samples. Sensor-derived syndromic surveillance of livestock has been identified as a gap in Scotland’s current animal health surveillance capabilities. Real-time data from on-farm herds has the potential to underpin improved production and endemic disease detection and the earlier identification and investigation of potential outbreaks. Using the data journeys approach, the aim of this project is to elucidate the conceptual journey of thermal imagery and drone-derived data from farm to policy. This approach aims to situate data across interconnected sites of practice, highlighting the movement of data in and between sites and exposing areas of potential ‘data friction’. The term ‘data friction’ is used to describe the complex factors (political, ethical, legal, social and economic) that come together to slow down and restrict data generation, movement and use.

Environmental sampling, in particular taking swabs of any surfaces likely to have been contaminated by infected animals, presents an opportunity for non-invasive sample collection, enabling cost-effective FMD surveillance beyond regular investigation of clinical cases. Linking the results of environmental sampling with those of other surveillance methods (e.g. oral swabs or serum samples) allows a comparison of the methods and shows how the results of different sampling methods are correlated.

Seven serotypes of foot-and-mouth disease virus (FMDV) (O, A, C, SAT (1, 2, 3), and Asia 1) occur across seven regional virus pools. In each pool, the specific serotypes that circulate in the susceptible populations varies. Since 2004 there has been a noticeable absence of serotype C from recorded outbreak data. This serotype historically occurred across European countries, however the most recent cases (2004) occurred in pool 4 (Eastern Africa) and pool 7 (South America). Detailed reports from these outbreaks suggest the outbreak in pool 4 resulted from vaccine escape, while in pool 7 the outbreak resulted from natural infection in an isolated cattle population. Following these outbreaks, response measures were taken to address the vaccine quality and coverage in isolated populations. Now, with continued lack of serotype C detection, we are evaluating whether the available data and knowledge about FMD epidemiology can substantiate a claim of serotype C extinction.

Spatial Qualitative Risk Analysis (SQRA) is a collaborative method and tool developed by Cirad and partners for sharing the knowledge of a college of academic and field experts in veterinary epidemiology and animal health about the relative risks of introduction and dissemination of an animal or zoonotic infectious disease within a territory. SQRA is of particular interest when historical records about the disease in question are scarce or inexistent (exotic, or new emerging disease). It is also very useful to target high-risk areas and / or time periods, and to prioritize disease surveillance and control activities. Although the collegial procedure might help reducing subjective biases, the accuracy of the outcome is necessarily limited by the quality and amount of information available to the experts and to the analyst. Therefore, a validation step is proposed to assess the predictive performance of the SQRA maps, based on either observed disease outbreaks or planned surveillance data such as a serological survey on a representative sample of the target population. Rather than adopting a binary mindset of either accepting or rejecting an SQRA map, this analysis should be regarded as an assessment of prior knowledge embodied in the map. It provides an opportunity to identify gaps in the epidemiological knowledge to update the collective perception of disease risk in a progressive process of learning by accumulating evidence.

Foot and Mouth Disease (FMD) is a notifiable disease to the World Animal Health Organization (OIE). FMD is one of the most contagious zoonotic diseases, with important economic losses. FMD causes a low mortality rate in adult animals but often causes a high mortality rate in young animals due to myocarditis. United Arab Emirates (UAE) intensifies the effort in line with the Progressive Control Pathway for Foot-and-Mouth Disease (PCP-FMD) developed by FAO and EuFMD and further endorsed by the OIE, guiding endemic countries through a series of incremental steps to manage FMD risks better. This study aims to assess the impact of control strategies, including early detection, movement control, surveillance, and vaccination. The benefit of this study is to inform the policy maker on required actions for making progress towards eradicating FMD from the UAE.

Data-driven innovations to inform disease control and prevention - A. Delgado by European Commission for the Control of FMD

The early detection of foot-and-mouth disease (FMD) incursion in an FMD-free country is of critical importance for timely control and eradication. The objective of this study was to assess the epidemiological and economic impacts of different ‘times to detection (TTD)’ of a potential FMD outbreak using a multi-country version of the EuFMDiS model.

Rift Valley fever (RVF) is a major emerging, zoonotic and arboviral haemorrhagic fever that greatly affects public and animal health, primarily in Africa. The ability of RVF virus to persist within distinct environments has raised questions over its potential to spread and persist within currently disease-free settings. Viral persistence requires suitable meteorological factors for vector competence and breeding alongside sufficiently susceptible local host communities. Prior to our work, no study had formally estimated the importance of these persistence mechanisms from field data, preventing any formal assessment of disease control strategies in a real-world setting.