SUMMARY Influenza A virus in swine is of significant importance to human and veterinary public health. Environmental sampling techniques that prove practical would enhance surveillance for influenza viruses in swine. The primary objective of this study was to demonstrate the feasibility of bioaerosol and surface sampling for the detection of influenza virus in swine barns with a secondary objective of piloting a mobile application for data collection. Sampling was conducted at a large swine operation between July 2016 and August 2017. Swine oral fluids and surface swabs were collected from multiple rooms. Room‐level air samples were collected using four bioaerosol samplers: a low volume polytetrafluoroethylene (PTFE) filter sampler, the National Institute for Occupational Safety and Health's low volume cyclone sampler, a 2‐stage Andersen impactor and/or one high volume cyclonic sampler. Samples were analysed using quantitative RT‐PCR. Data and results were reported using a mobile data application. Eighty‐nine composite oral fluid samples, 70 surface swabs and 122 bioaerosol samples were analysed. Detection rates for influenza virus RNA in swine barn samples were 71.1% for oral fluids, 70.8% for surface swabs and 71.1% for the PTFE sampler. Analysis revealed a statistically significant relationship between the results of the PTFE sampler and the surface swabs with oral fluid results (p < 0.001 and p < 0.01 respectively). In addition, both the PTFE sampler (p < 0.01) and surface swabs (p = 0.03) significantly correlated with, and predicted oral fluid results. Bioaerosol sampling using PTFE samplers is an effective hands‐off approach for detecting influenza virus activity among swine. Further study is required for the implementation of this approach for surveillance and risk assessment of circulating influenza viruses of swine origin. In addition, mobile data collection stands to be an invaluable tool in the field by allowing secure, real‐time reporting of sample collection and results.
Appropriate emergency disaster preparedness is a key priority for agricultural agencies to allow effective response to serious avian disease outbreaks. There is a need to develop rapid, humane, and safe depopulation techniques for poultry that are widely applicable across a range of farm settings. Whole barn depopulation with carbon dioxide (CO(2)) has been investigated as a humane and efficient means of killing large numbers of birds in the event of a reportable disease outbreak. It has also been considered as a method for depopulating barns containing end-of-lay hens, particularly when there is limited local slaughter and rendering capacity. Determining the best method of humanely killing large flocks of birds remains problematic and is being investigated by a coordinated international effort. While whole barn depopulation using CO(2) inhalation has been explored, physiologic responses of chickens have not been characterized in field settings and assessment of animal welfare is hampered without this information. In this study, 12 cull laying hens were surgically instrumented with telemetry transmitters to record electroencephalographs, electrocardiographs, body temperature, and activity during 2 large-scale field CO(2) euthanasia trials of end-of-lay hens. The day following surgery, instrumented hens were placed in barns with other birds, barns were sealed, and animals were killed by CO(2) inhalation delivered via a specially designed liquid CO(2) manifold. Instrumented birds were monitored by infrared thermography, and ambient temperature, CO(2), and O(2) concentrations were recorded. Results from these studies indicate that instrumented hens lost consciousness within 2 min of CO(2) levels reaching 18 to 20%. Mild to moderate head shaking, gasping, and 1 to 2 clonic muscle contractions were noted in hens before unconsciousness; however, brain death followed rapidly (<5 min). Evaluation of welfare costs and benefits suggest clear advantages over catching and transporting cull hens for slaughter. The financial costs with this method are greater, however, than those estimated for traditional slaughter techniques. Results of these studies are being used to develop national protocols for whole barn depopulation of hens by CO(2) inhalation.
There are many benefits that derive from real-time knowledge of the health status of the national livestock population. Effective animal disease surveillance is a requirement for countries that trade in live animals and their products in order to comply with the World Organization for Animal Health (OIE) guidelines. Rapid identification of introduced and emerging disease allows rapid response and mitigation of the economic consequences. Connections between animal and human disease caused by a common pathogen can be recognized and control measures implemented, thereby protecting public health and maintaining public confidence in the food supply. Production-limiting diseases can be monitored, and control programmes be evaluated with benefits accruing from decreased economic losses associated with disease as well as reducing the welfare concerns associated with diseased animals. Establishing a surveillance programme across a wide area with diverse ecosystems and political administrations as Canada is a complex challenge. When funding became available from a government programme to enable early detection of a bio-terrorist attack on livestock, the Canadian Animal Health Surveillance Network (CAHSN) became officially established. An existing web-based information platform that supports intelligence exchange, surveillance and response for public health issues in Canada was adapted to link the network animal health laboratories. A minimum data set was developed that facilitated sharing of results between participating laboratories and jurisdictions as the first step in creating the capacity for national disease trend analysis. In each of the network laboratories, similar quality assurance and bio-containment systems have been funded and supported, and diagnostic staff have been trained and certified on a suite of diagnostic tests for foreign animal diseases. This ensures that national standards are maintained throughout all of the diagnostic laboratories. This paper describes the genesis of CAHSN, its current capability and governance, and potential for future development.
A minimum data set consisting of 15 data elements originating from laboratory submissions and results was formulated by a national committee of epidemiologists in Canada for the purposes of disease reporting, disease detection and analysis. The data set consists of both data that are filled out on the submission form as well as the results of the laboratory testing. The elements in the data set are unique identifier, premises identification, date submitted, geographic location, species, farm type, group type, total population of tested species on the farm, number sick, number dead, test(s) performed, disease agent, test result, disease classification by submitter and final laboratory diagnosis. The data set was designed to be concise while allowing for domestic and international disease reporting, effective analysis, including geographic, temporal and prevalence outputs, and syndromic surveillance to enable disease detection. The selected data elements do not identify the producer as specific geographic and nominal information is not included in the data set. The data elements selected, thus, allow for voluntary collaboration and data sharing by avoiding issues associated with privacy legislation.
Objectives: To introduce the Canadian Network for Public Health Intelligence's new Knowledge Integration using Web-based Intelligence (KIWI) technology, and to pefrom preliminary evaluation of the KIWI technology using a case study. The purpose of this new technology is to support surveillance activities by monitoring unstructured data sources for the early detection and awareness of potential public health threats.Methods: A prototype of the KIWI technology, adapted for zoonotic and emerging diseases, was piloted by end-users with expertise in the field of public health and zoonotic/emerging disease surveillance. The technology was assessed using variables such as geographic coverage, user participation, and others; categorized by high-level attributes from evaluation guidelines for internet based surveillance systems. Special attention was given to the evaluation of the system's automated sense-making algorithm, which used variables such as sensitivity, specificity, and predictive values. Event-based surveillance evaluation was not applied to its full capacity as such an evaluation is beyond the scope of this paper.Results: KIWI was piloted with user participation = 85.0% and geographic coverage within monitored sources = 83.9% of countries. The pilots, which focused on zoonotic and emerging diseases, lasted a combined total of 65 days and resulted in the collection of 3243 individual information pieces (IIP) and 2 community reported events (CRE) for processing. Ten sources were monitored during the second phase of the pilot, which resulted in 545 anticipatory intelligence signals (AIS). KIWI's automated sense-making algorithm (SMA) had sensitivity = 63.9% (95% CI: 60.2-67.5%), specificity = 88.6% (95% CI: 87.3-89.8%), positive predictive value = 59.8% (95% CI: 56.1-63.4%), and negative predictive value = 90.3% (95% CI: 89.0-91.4%).Discussion: Literature suggests the need for internet based monitoring and surveillance systems that are customizable, integrated into collaborative networks of public health professionals, and incorporated into national surveillance activities. Results show that the KIWI technology is well posied to address some of the suggested challenges. A limitation of this study is that sample size for pilot participation was small for capturing overall readiness of integrating KIWI into regular surveillance activities.Conclusions: KIWI is a customizable technology developed within an already thriving collaborative platform used by public health professionals, and performs well as a tool for discipline-specific event monitoring and early warning signal detection.
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