Improving the Utility of Voluntary Ovine Fallen Stock Collection and Laboratory Diagnostic Submission Data for Animal Health Surveillance Purposes: A Development Cycle

Abstract

There are calls from policy-makers and industry to use existing data sources to contribute to livestock surveillance systems, especially for syndromic surveillance. However, the practical implications of attempting to use such data sources are challenging; development often requires incremental steps in an iterative cycle. In this study the utility of business operational data from a voluntary fallen stock collection service was investigated, to determine if they could be used as a proxy for the mortality experienced by the British sheep population. Retrospectively, Scottish ovine fallen stock collection data (2011-2014) were transformed into meaningful units for analysis, temporal and spatial patterns were described, time-series methods and a temporal aberration detection algorithm applied. Distinct annual and spatial trends plus seasonal patterns were observed in the three age groups investigated. The algorithm produced an alarm at the point of an historic known departure from normal (April 2013) for two age groups, across Scotland as a whole and in specific postcode areas. The analysis was then extended. Initially, to determine if similar methods could be applied to ovine fallen stock collections from England and Wales for the same time period. Additionally, Scottish contemporaneous laboratory diagnostic submission data were analyzed to see if they could provide further insight for interpretation of statistical alarms. Collaboration was required between the primary data holders, those with industry sector knowledge, plus veterinary, epidemiological and statistical expertise, in order to turn data and analytical outcomes into potentially useful information. A number of limitations were identified and recommendations were made as to how some could be addressed in order to facilitate use of these data as surveillance "intelligence." e.g., improvements to data collection and provision. A recent update of the fallen stock collections data has enabled a longer temporal period to be analyzed, with evidence of changes made in line with the recommendations. Further development will be required before a functional system can be implemented. However, there is potential for use of these data as: a proxy measure for mortality in the sheep population; complementary components in a future surveillance system, and to inform the design of additional surveillance system components.

Bovine mortality: the utility of two data sources for the provision of population-level surveillance intelligence

“…This is because of the format in which the data was available. From experience with the equivalent sheep fallen stock collections data ( 31 ), even if this could be addressed, an appropriate denominator would be difficult to determine.…”

The Use of Sheep Movement Data to Inform Design and Interpretation of Slaughterhouse-Based Surveillance Activities

“…It is reassuring that the outputs from this analysis, and the overall sheep numbers and movements, correspond to known aspects of the sheep calendar year, management activities and events. For example, the low level of within Scotland non-slaughter moves in the second quarter corresponds to the lambing and post-lambing season, while the decline in the spring peak in March in 2018, and the subsequent population fall at the June 2018 Agricultural Census are indicative of the extreme, adverse, weather conditions (known as "the Beast from the East") during March 2018 when sheep couldn't move and a substantial number died (31).…”

Exploiting Scanning Surveillance Data to Inform Future Strategies for the Control of Endemic Diseases: The Example of Sheep Scab

“…Even so, the original Farrington proved to be a suitable algorithm for the particular challenges of this type of surveillance data, such as adjusting for any unknown past outbreaks, not requiring a long baseline period, and the ability to account for any seasonal effect in the data if present (as sheep scab is well established as a highly seasonal disease) (12,31). In addition, the original Farrington method has been previously (and successfully) applied to other data extracts from the VIDA database (15).…”

“…An important concept for monitoring the true prevalence of a disease also includes knowing the proportion of disease within the population at risk. However, utilising diagnostic datasets from the voluntary submission of samples by farmers seeking a diagnosis through their veterinarian such as the VIDA database often lacks appropriate denominator (animal population) data, which can be a limitation for their interpretation by veterinarians and other stakeholders (15).…”