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The complexity of influenza A virus (IAV) infections in avian hosts leads to equally complex scenarios for the vaccination of poultry. Vaccination against avian influenza strains can be used to prevent infections from sources with a single strain of IAV. It has been used as a part of outbreak control strategies as well as a way to maintain production for both low and high pathogenicity outbreaks. Unlike other viral pathogens of birds, avian influenza vaccination when used against highly pathogenic avian influenza virus, is tied to international trade and thus is not freely available for use without specific permission.

Artificial insemination is a routine practice for turkeys that can introduce pathogens into breeder flocks in a variety of ways. In this manuscript, a risk analysis on the potential transmission of highly pathogenic avian influenza (HPAI) to naïve hens through artificial insemination is presented. A case of HPAI on a stud farm where the potential transmission of the virus to susceptible hens in the 2015 H5N2 HPAI outbreak in Minnesota is described along with documentation of known and potential transmission pathways from the case. The pathways by which artificial insemination might result in the spread of HPAI to susceptible hens were determined by considering which could result in the 1) entry of HPAI virus onto a premises through semen movement; and 2) exposure of susceptible hens to HPAI as a result of this movement. In the reported case, HPAI virus was detected in semen from infected toms, however, transmission of HPAI to naïve hens through semen is unclear since the in utero infectious dose is not known. This means that the early detection of infection might limit but not eliminate the risk of hen exposure. Because of the numerous potential pathways of spread and the close contact with the birds, it is highly likely that if semen from an HPAI-infected tom flock is used, there will be spread of the virus to naïve hens through insemination. If insemination occurs with semen from stud farms in an HPAI control area, receiving hen farms should have restricted movements to prevent outbreak spread in the event that they become infected.

Embryonating chicken eggs (ECEs) are among the most sensitive laboratory host systems for avian influenza virus (AIV) titration, but ECEs are expensive and require space for storage and incubation. Therefore, reducing ECE use would conserve resources. We utilized statistical modeling to evaluate the accuracy and precision of AIV titration with 3 instead of 5 ECEs for each dilution by the Reed-Muench method for 50% endpoint calculation. Beta-Poisson and exponential dose-response models were used in a simulation study to evaluate observations from actual titration data from 18 AIV isolates. The reproducibility among replicates of a titration was evaluated with one AIV isolate titrated in 3 replicates with the beta-Poisson, exponential, and Weibull dose-response models. The standard deviation (SD) of the error between input and estimated virus titers was estimated with Monte Carlo simulations using the fitted dose-response models. Good fit was observed with all models that were utilized. Reducing the number of ECEs per dilution from 5 to 3 resulted in the width of the 95% confidence interval increasing from ±0.64 to ±0.75 log 10 50% ECE infectious doses (EID 50 ) and the SD of the error increased by 0.03 log 10 EID 50 . Our study suggests that using fewer ECEs per dilution is a viable approach that will allow laboratories to reduce costs and improve efficiency.

Background: Avian influenza (AI) is an infectious viral disease that affects several species and has zoonotic potential. Due to its associated health and economic repercussions, minimizing AI outbreaks is important. However, most control measures are generic and mostly target pathways important for the conventional poultry farms producing chickens, turkeys, and eggs and may not target other pathways that may be specific to the upland game bird sector. The goal of this study is to provide evidence to support the development of novel strategies for sector-specific AI control by comparing and contrasting practices and potential pathways for spread in upland game bird farms with those for conventional poultry farms in the United States. Farm practices and processes, seasonality of activities, geographic location and inter-farm distance were analyzed across the sectors. All the identified differences were framed and discussed in the context of their associated pathways for virus introduction into the farm and subsequent between-farm spread., Results: Differences stemming from production systems and seasonality, inter-farm distance and farm densities were evident and these could influence both fomite-mediated and local-area spread risks. Upland game bird farms operate under a single, independent owner rather than being contracted with or owned by a company with other farms as is the case with conventional poultry. The seasonal marketing of upland game birds, largely driven by hunting seasons, implies that movements are seasonal and customer-vendor dynamics vary between industry groups. Farm location analysis revealed that, on average, an upland game bird premises was 15.42 km away from the nearest neighboring premises with birds compared to 3.74 km for turkey premises. Compared to turkey premises, the average poultry farm density in a radius of 10 km of an upland game bird premises was less than a half, and turkey premises were 3.8 times (43.5% compared with 11.5%) more likely to fall within a control area during the 2015 Minnesota outbreak., Conclusions: We conclude that the existing differences in the seasonality of production, isolated geographic location and epidemiological seclusion of farms influence AI spread dynamics and therefore disease control measures should be informed by these and other factors to achieve success.

Outbreaks involving avian influenza viruses are often devastating to the poultry industry economically and otherwise. Disease surveillance is critically important because it facilitates timely detection and generates confidence that infected birds are not moved during business continuity intended to mitigate associated economic losses. The possibility of using an abnormal increase in daily mortality to levels that exceed predetermined thresholds as a trigger to initiate further diagnostic investigations for highly pathogenic avian influenza (HPAI) virus infection in the flock is explored. The range of optimal mortality thresholds varies by bird species, trigger type, and mortality thresholds, and these should be considered when assessing sector-specific triggers. The study uses purposefully collected data and data from the literature to determine optimal mortality triggers for HPAI detection in commercial upland game bird flocks. Three trigger types were assessed for the ability to detect rapidly both HPAI (on the basis of disease-induced and normal mortality data) and false alarm rate (on the basis of normal mortality data); namely, 1) exceeding a set absolute threshold on one day, 2) exceeding a set absolute threshold on two consecutive days, or 3) exceeding a multiple of a seven-day moving average. The likelihood of disease detection using some of these triggers together with premovement real-time reverse transcription PCR (rRT-PCR) testing was examined. Results indicate that the performance of the two consecutive days trigger had the best metrics (i.e., rapid detection with few false alarms) in the trade-off analysis. The collected normal mortality data was zero on 66% of all days recorded, with an overall mean of 0.6 dead birds per day. In the surveillance scenario analyses, combining the default protocol that relied only on active surveillance (i.e., premovement testing of oropharyngeal swab samples from dead birds by rRT-PCR) together with either of the mortality-based triggers improved detection rates on all days postexposure before scheduled movement. For exposures occurring within 8 days of movement, the protocol that combined the default with single-day triggers had slightly more detections than that with two consecutive days triggers. However, all assessed protocol combinations were able to detect all infections that occurred more than 10 days before scheduled movement. These findings can inform risk-based decisions pertaining to continuity of business in the commercial upland game bird industry.

Background: Timely diagnosis of influenza A virus infections is critical for outbreak control. Due to their rapidity and other logistical advantages, lateral flow immunoassays can support influenza A virus surveillance programs and here, their field performance was proactively assessed. The performance of real-time polymerase chain reaction and two lateral flow immunoassay kits (FluDETECT and VetScan) in detecting low pathogenicity influenza A virus in oropharyngeal swab samples from experimentally inoculated broiler chickens was evaluated and at a flock-level, different testing scenarios were analyzed., Results: For real-time polymerase chain reaction positive individual-swabs, FluDETECT respectively detected 37% and 58% for the H5 and H7 LPAIV compared to 28% and 42% for VetScan. The mean virus titer in H7 samples was higher than for H5 samples. For real-time polymerase chain reaction positive pooled swabs (containing one positive), detections by FluDETECT were significantly higher in the combined 5- and 6-swab samples compared to 11-swab samples. FluDETECT detected 58%, 55.1% and 44.9% for the H7 subtype and 28.3%, 34.0% and 24.6% for the H5 in pools of 5, 6 and 11 respectively. In our testing scenario analysis, at low flock-level LPAIV infection prevalence, testing pools of 11 detected slightly more infections while at higher prevalence, testing pools of 5 or 6 performed better. For highly pathogenic avian influenza virus, testing pools of 11 (versus 5 or 6) detected up to 5% more infections under the assumption of similar sensitivity across pools and detected less by 3% when its sensitivity was assumed to be lower., Conclusions: Much as pooling a bigger number of swab samples increases the chances of having a positive swab included in the sample to be tested, this study's outcomes indicate that this practice may actually reduce the chances of detecting the virus since it may result into lowering the virus titer of the pooled sample. Further analysis on whether having more than one positive swab in a pooled sample would result in increased sensitivity for low pathogenicity avian influenza virus is needed.

The complexity of influenza A virus (IAV) infections in avian hosts leads to equally complex scenarios for the vaccination of poultry. Vaccination against avian influenza strains can be used to prevent infections from sources with a single strain of IAV. It has been used as a part of outbreak control strategies as well as a way to maintain production for both low and high pathogenicity outbreaks. Unlike other viral pathogens of birds, avian influenza vaccination when used against highly pathogenic avian influenza virus, is tied to international trade and thus is not freely available for use without specific permission. Vacunación de aves comerciales contra la influenza aviar. La complejidad de las infecciones por el virus de la influenza A en las aves hospedadoras conduce a escenarios igualmente complejos para la vacunación en la avicultura. La vacunación contra cepas de influenza aviar se puede utilizar para prevenir infecciones provenientes de fuentes con una sola cepa del virus de influenza. Se ha utilizado como parte de las estrategias de control de brotes, así como como una forma de mantener la producción tanto en brotes de baja como de alta patogenicidad. A diferencia de otros patógenos virales de las aves, la vacunación contra la influenza aviar, cuando se usa contra el virus de la influenza aviar altamente patógeno, está vinculada al comercio internacional y por lo tanto, no está disponible para su uso sin un permiso específico. [ABSTRACT FROM AUTHOR]

Estimates of the per-contact probability of transmission between farms of Highly Pathogenic Avian Influenza virus of H7N7 subtype during the 2003 epidemic in the Netherlands are important for the design of better control and biosecurity strategies. We used standardized data collected during the epidemic and a model to extract data for untraced contacts based on the daily number of infectious farms within a given distance of a susceptible farm. With these data, we used a maximum likelihood estimation approach to estimate the transmission probabilities by the individual contact types, both traced and untraced. The estimated conditional probabilities, conditional on the contact originating from an infectious farm, of virus transmission were: 0.000057 per infectious farm within 1 km per day, 0.000413 per infectious farm between 1 and 3 km per day, 0.0000895 per infectious farm between 3 and 10 km per day, 0.0011 per crisis organisation contact, 0.0414 per feed delivery contact, 0.308 per egg transport contact, 0.133 per other-professional contact and, 0.246 per rendering contact. We validate these outcomes against literature data on virus genetic sequences for outbreak farms. These estimates can be used to inform further studies on the role that improved biosecurity between contacts and/or contact frequency reduction can play in eliminating between-farm spread of the virus during future epidemics. The findings also highlight the need to; 1) understand the routes underlying the infections without traced contacts and, 2) to review whether the contacttracing protocol is exhaustive in relation to all the farm's day-to-day activities and practices. [ABSTRACT FROM AUTHOR]