Reducing the burden of emerging and endemic infectious diseases on commercial livestock production systems will require the development of innovative technology platforms that enable information from diverse animal health resources to be collected, analyzed, and communicated in near real-time. In this paper, we review recent initiatives to leverage data routinely observed by farmers, production managers, veterinary practitioners, diagnostic laboratories, regulatory officials, and slaughterhouse inspectors for disease surveillance purposes. The most commonly identified challenges were (1) the lack of standardized systems for recording essential data elements within and between surveillance data streams, (2) the additional time required to collect data elements that are not routinely recorded by participants, (3) the concern over the sharing and use of business sensitive information with regulatory authorities and other data analysts, (4) the difficulty in developing sustainable incentives to maintain long-term program participation, and (5) the limitations in current methods for analyzing and reporting animal health information in a manner that facilitates actionable response. With the significant recent advances in information science, there are many opportunities to develop more sophisticated systems that meet national disease surveillance objectives, while still providing participants with valuable tools and feedback to manage routine animal health concerns.

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.

Background To improve early detection of emerging infectious diseases in sub-Saharan Africa (SSA), many of them zoonotic, numerous electronic animal disease-reporting systems have been piloted but not implemented because of cost, lack of user friendliness, and data insecurity. In Kenya, we developed and rolled out an open-source mobile phone-based domestic and wild animal disease reporting system and collected data over two years to investigate its robustness and ability to track disease trends. Methods The Kenya Animal Biosurveillance System (KABS) application was built on the Java® platform, freely downloadable for android compatible mobile phones, and supported by web-based account management, form editing and data monitoring. The application was integrated into the surveillance systems of Kenya’s domestic and wild animal sectors by adopting their existing data collection tools, and targeting disease syndromes prioritized by national, regional and international animal and human health agencies. Smartphone-owning government and private domestic and wild animal health officers were recruited and trained on the application, and reports received and analyzed by Kenya Directorate of Veterinary Services. The KABS application performed automatic basic analyses (frequencies, spatial distribution), which were immediately relayed to reporting officers as feedback. Results Of 697 trained domestic animal officers, 662 (95%) downloaded the application, and >72% of them started reporting using the application within three months. Introduction of the application resulted in 2- to 14-fold increase in number of disease reports when compared to the previous year (relative risk = 14, CI 13.8–14.2, p<0.001), and reports were more widely distributed. Among domestic animals, food animals (cattle, sheep, goats, camels, and chicken) accounted for >90% of the reports, with respiratory, gastrointestinal and skin diseases constituting >85% of the reports. Herbivore wildlife (zebra, buffalo, elephant, giraffe, antelopes) accounted for >60% of the wildlife disease reports, followed by carnivores (lions, cheetah, hyenas, jackals, and wild dogs). Deaths, traumatic injuries, and skin diseases were most reported in wildlife. Conclusions This open-source system was user friendly and secure, ideal for rolling out in other countries in SSA to improve disease reporting and enhance preparedness for epidemics of zoonotic diseases.

BackgroundTo improve early detection of emerging infectious diseases in sub-Saharan Africa (SSA), many of them zoonotic, numerous electronic animal disease-reporting systems have been piloted but not implemented because of cost, lack of user friendliness, and data insecurity. In Kenya, we developed and rolled out an open-source mobile phone-based domestic and wild animal disease reporting system and collected data over two years to demonstrate its robustness and ability to track disease trends.MethodsThe Kenya Animal Biosurveillance System (KABS) application was built on the Java® platform, freely downloadable for android compatible mobile phones, and supported by web-based account management, form editing and data monitoring. The application was integrated into the surveillance systems of Kenya’s domestic and wild animal sectors by adopting their existing data collection tools, and targeting disease syndromes prioritized by national, regional and international animal and human health agencies. Smartphone-owning government and private domestic and wild animal health officers were recruited and trained on the application, and reports received and analyzed by Kenya Directorate of Veterinary Services. The KABS application performed automatic basic analyses (frequencies, spatial distribution), which were immediately relayed to reporting officers as feedback.ResultsOver 95% of trained domestic animal officers downloaded the application, and >72% of them started reporting using the application within three months. Introduction of the application resulted in 2- to 10-fold increase in number of disease reports when compared the previous year (p<0.05), and reports were more spatially distributed. Among domestic animals, food animals (cattle, sheep, goats, camels, and chicken) accounted for >90% of the reports, with respiratory, gastrointestinal and skin diseases constituting >85% of the reports. Herbivore wildlife (zebra, buffalo, elephant, giraffe, antelopes) accounted for >60% of the wildlife disease reports, followed by carnivores (lions, cheetah, hyenas, jackals, and wild dogs). Deaths, traumatic injuries, and skin diseases were most reported in wildlife.ConclusionsThis open-source system was user friendly and secure, ideal for rolling out in other countries in SSA to improve disease reporting and enhance preparedness for epidemics of zoonotic diseases.Authors SummaryTaking advantage of a recently developed freely downloadable disease reporting application in the United States, we customized it for android smartphones to collect and submit domestic and wild animal disease data in real-time in Kenya. To enhance user friendliness, the Kenya Animal Biosurveillance System (KABS) was installed with disease reporting tools currently used by the animal sector and tailored to collected data on transboundary animal disease important for detecting zoonotic endemic and emerging diseases. The KABS database was housed by the government of Kenya, providing important assurance on its security. The application had a feedback module that performed basics analysis to provide feedback to the end-user in real-time. Rolling out of KABS resulted in >70% of domestic and wildlife disease surveillance officers using it to report, resulting in exponential increase in frequency and spatial distributions of reports regions. Utility of the system was demonstrated by successful detected a Rift Valley fever outbreak in livestock in 2018, resulting in early response and prevention of widespread human infections. For the wildlife sector in Eastern Africa, the application provided the first disease surveillance system developed. This open-source system is ideal for rolling out in other countries in sub-Saharan Africa to improve disease reporting and enhance preparedness for epidemics of zoonotic diseases.

T eamwork and communication are two important processes within multi-agent systems designed to act in a coherent and coordinated manner. Modeling teamwork involves interleaving steps within shared plans that will allow agents to work together towards common goals. T hese steps involve reasoning about roles, responsibilities, and joint-intentions in order to coordinate activity amongst individuals. Communication facilitates teamwork. T here are various complex forms of communication such as synchronization, coordination, and cooperation that allow for members of teams to use teamwork to their advantage. Explicitly de® ning every possible communication point within a team plan is too cumbersome and in¯exible. In this paper, we describe a method to automatically decompose a team plan into a collection of individual agent plans, inserting all of the necessary communication points needed to properly generate coordinated behavior. T his approach could be used to more accurately and easily model teamwork in multi-agent systems.