Improving Animal Disease Detection Through an Enhanced Passive Surveillance Platform

Abstract

The ability to rapidly detect and report infectious diseases of domestic animals and wildlife is paramount to reducing the size and duration of an outbreak. There is currently a need in the United States livestock industry for a centralized animal disease surveillance platform, capable of collecting, integrating, and analyzing multiple data streams with dissemination to end-users. Such a system would be disease agnostic and establish baseline information on animal health and disease prevalence; it would alert health officials to anomalies potentially indicative of emerging and/or transboundary disease outbreaks, changes in the status of endemic disease, or detection of other causative agents (eg, toxins). As a part of its mission to accelerate and develop countermeasures against the introduction of emerging and/or transboundary animal diseases into the United States, the Department of Homeland Security is leading and investing in the development of an enhanced passive surveillance platform capable of establishing animal health baselines over time and alerting health officials to potential infectious disease outbreaks or other health anomalies earlier, allowing for more rapid response, improved animal health, and increased economic security.

The use of animals as a surveillance tool for monitoring environmental health hazards, human health hazards and bioterrorism

“…However, because it relies heavily on reports from veterinarians who receive little incentive for reporting, the data reported is frequently incomplete and delayed. Underreporting of disease suspicions is also known to be a major cause of disease control failure (FAO, 2011) and multiple studies have been conducted to better comprehend the decisionmaking processes behind underreporting so as to develop recommendations for improved passive surveillance (Bronner et al, 2014;Delabouglise et al, 2016;Paul et al, 2013;Sawford et al, 2012;Thompson et al, 2016). In contrast, active surveillance demands more time and resources and is thus less commonly employed.…”

Technologies for capturing and analysing animal health data in near real time

“…It is at this point that the data can be manually or automatically transmitted and submitted. This allows for data collection in remote areas to occur with the knowledge that, once a network connection is established, the data will be automatically submitted and added to the database for analysis (29,30). Another advantage of smartphones is their ability to collect locational data using the device' s global positioning system (GPS) (7).…”

“…In other cases, mobile apps have been custom-developed for specific projects or organisations. The decision to do so is typically based upon the scope of the project requirements being beyond the use of a tool solely for remote data collection, such as integration within a broader surveillance information technology system (see the eHealth section below), and/ or preference that data are not transmitted by, or stored with, outside/commercial entities (29,36). For example, the Food and Agriculture Organization of the United Nations (FAO) developed an Android mobile app called Event Mobile Application (EMA) that integrates disease information collected in the field with FAO' s Global Animal Disease Information System (EMPRES-i; http://empres-i.…”

“…Like SMS, mobile apps on smartphones can communicate in the form of alerts from a central authority, such as from government animal health authorties, to all or a subset of users. Additionally, mobile apps can further support bidirectional information flow through the use of within-app messaging between users in the field, and animal health experts and/or authorities (27,29). These capabilities overcome the challenges of current surveillance systems characterised by hierarchical data flows resulting in slow data collection, analysis and sharing of information (5,28).…”

“…The degree of data integration within the technological system can vary, from allowing these data sources to be accessible as additional data layers to display on maps, to the data being fully incorporated as parameter inputs into analytical tools developed within the technology system that allow for data queries, visualisations and analysis across all integrated data sources. To achieve real-time data monitoring and analysis, these systems use innovative technological methods for automated data cleaning, integration, storage/processing, visualisation and analysis (29,65,66).…”