Assessing a pilot co-operative-based workshop-subsidy model toward improving small-scale chicken production in peri-urban Nepal.

Farmers in Nepal face many of the same global challenges associated with initiating and scaling poultry husbandry as many other developing countries. These include access to innovative approaches in finance, credit, coop design, marketing, and sales. As with most low-income countries, Nepalese poultry farmers also lack adequate training in poultry husbandry including biosecurity. In this paper, we describe a collaborative workshop-subsidy approach to addressing these challenges conducted by a partnership with the UC Davis School of Veterinary Medicine, the College of Engineering, the School of Education, and a farming co-operative based in the semi-rural area of Bhaktapur, Nepal. The program included two workshops covering aspects of poultry rearing including coop construction, chick rearing, biosecurity, and husbandry. Both workshops were a combination of lectures and hands-on learning. Following completion of the workshops, each farmer received subsidized materials for coop construction and poultry rearing. The co-operative provided training facilities and a market for selling eggs. Despite an outbreak of Highly Pathogenic Avian Influenza (HPAI), which affected the scale of program implementation, our results suggest that the workshop subsidy collaborative approach can be successful in reducing market entry barriers. Our 6-mo post-workshop survey showed that two-thirds of the workshop participants ultimately built their own coop and raised chicks. Half of these participants reported market available egg production and a doubling of egg consumption at home.

Using the California Waterfowl Tracker to Assess Proximity of Waterfowl to Commercial Poultry in the Central Valley of California.

Migratory waterfowl are the primary reservoir of avian influenza viruses (AIV), which can be spread to commercial poultry. Surveillance efforts that track the location and abundance of wild waterfowl and link those data to inform assessments of risk and sampling for AIV currently do not exist. To assist surveillance and minimize poultry exposure to AIV, here we explored the utility of Remotely Sensed Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery in combination with land-based climate measurements (e.g., temperature and precipitation) to predict waterfowl location and abundance in near real-time in the California Central Valley (CCV), where both wild waterfowl and domestic poultry are densely located. Specifically, remotely collected MODIS and climate data were integrated into a previously developed boosted regression tree (BRT) model to predict and visualize waterfowl distributions across the CCV. Daily model-based predictions are publicly available during the winter as part of the dynamic California Waterfowl Tracker (CWT) web app hosted on the University of California's Cooperative Extension webpage. In this study, we analyzed 52 days of model predictions and produced daily spatiotemporal maps of waterfowl concentrations near the 605 commercial poultry farms in the CCV during January and February of 2019. Exposure of each poultry farm to waterfowl during each day was classified as high, medium, low, or none, depending on the density of waterfowl within 4 km of a farm. Results indicated that farms were at substantially greater risk of exposure in January, when CCV waterfowl populations peak, than in February. For example, during January, 33% (199/605) of the farms were exposed for ≥1 day to high waterfowl density vs. 19% (115/605) of the farms in February. In addition to demonstrating the overall variability of waterfowl location and density, these data demonstrate how remote sensing can be used to better triage AIV surveillance and biosecurity efforts via the utilization of a functional web app-based tool. The ability to leverage remote sensing is an integral advancement toward improving AIV surveillance in waterfowl in close proximity to commercial poultry. Expansion of these types of remote sensing methods, linked to a user-friendly web tool, could be further developed across the continental United States. The BRT model incorporated into the CWT reflects a first attempt to give an accurate representation of waterfowl distribution and density relative to commercial poultry.

Las aves acuáticas migratorias son el principal reservorio de los virus de la influenza aviar (con las siglas en inglés AIV), que pueden transmitirse a la avicultura comercial. Actualmente no existen esfuerzos de vigilancia que rastrean la ubicación y densidad de poblaciones de aves acuáticas silvestres y que vinculen esos datos para informar evaluaciones de riesgo y muestreo para influenza aviar. Para ayudar a la vigilancia y minimizar la exposición de la avicultura comercial a influenza aviar se exploró la utilidad de las imágenes satelitales por espectrorradiómetro de imágenes con resolución moderada (con las siglas en inglés MODIS) y de detección remota en combinación con mediciones climáticas terrestres (por ejemplo, temperatura y precipitación) para predecir la ubicación y densidad de aves acuáticas prácticamente en tiempo real en el Valle Central de California (CCV), donde tanto las aves acuáticas silvestres como las aves domésticas están densamente ubicadas. Específicamente, los datos MODIS y climáticos recopilados de forma remota se integraron en un modelo de árbol de regresión reforzado (BRT) desarrollado previamente para predecir y visualizar la distribución de las aves acuáticas en el Valle Central de California. Las predicciones diarias basadas en modelos están disponibles públicamente durante el invierno como parte de la aplicación dinámica en el del rastreador de aves acuáticas de California (California Waterfowl Tracker, CWT) ubicada en la página de internet de Extensión Cooperativa de la Universidad de California. En este estudio, se analizaron 52 días de predicciones del modelo y se produjeron mapas espaciotemporales diarios con densidades de aves acuáticas cerca de las 605 granjas avícolas comerciales en el Valle Central de California durante enero y febrero de 2019. La exposición de cada granja avícola a las aves acuáticas durante cada día se clasificó como alta, media, baja o nula, dependiendo de la densidad de aves acuáticas dentro de los cuatro kilómetros de una granja. Los resultados indicaron que las granjas tenían un riesgo sustancialmente mayor de exposición en enero, cuando las poblaciones de aves acuáticas en el Valle Central de California alcanzan su punto máximo, en comparación con febrero. Por ejemplo, durante enero, el 33% (199/605) de las granjas estuvieron expuestas durante más de un día a una alta densidad de aves acuáticas frente a un 19% (115/605) de las granjas en febrero. Además de demostrar la variabilidad general de la ubicación y densidad de las aves acuáticas, estos datos demuestran cómo se puede utilizar la teledetección para clasificar mejor los esfuerzos de bioseguridad y vigilancia para la influenza aviar mediante la utilización de una herramienta funcional basada en una aplicación en el internet. La capacidad de aprovechar la teledetección es un avance integral hacia la mejora de la vigilancia para influenza aviar en aves acuáticas en las proximidades de la avicultura comercial. La expansión de estos tipos de métodos de teledetección, vinculados a una herramienta en el internet que es fácil de usar, podría desarrollarse aún más en los Estados Unidos continentales. El modelo de árbol de regresión reforzado incorporado en el sistema de rastreo de aves acuáticas de California refleja un primer intento de brindar una representación precisa de la distribución y densidad de las aves acuáticas en relación con las aves comerciales.

A comparison of amplification methods to detect Avian Influenza viruses in California wetlands targeted via remote sensing of waterfowl.

Migratory waterfowl, including geese and ducks, are indicated as the primary reservoir of avian influenza viruses (AIv) which can be subsequently spread to commercial poultry. The US Department of Agriculture's (USDA) surveillance efforts of waterfowl for AIv have been largely discontinued in the contiguous United States. Consequently, the use of technologies to identify areas of high waterfowl density and detect the presence of AIv in habitat such as wetlands has become imperative. Here we identified two high waterfowl density areas in California using processed NEXt generation RADar (NEXRAD) and collected water samples to test the efficacy of two tangential flow ultrafiltration methods and two nucleic acid based AIv detection assays. Whole-segment amplification and long-read sequencing yielded more positive samples than standard M-segment qPCR methods (57.6% versus 3.0%, p < .0001). We determined that this difference in positivity was due to mismatches in published primers to our samples and that these mismatches would result in failing to detect in the vast majority of currently sequenced AIv genomes in public databases. The whole segment sequences were subsequently used to provide subtype and potential host information of the AIv environmental reservoir. There was no statistically significant difference in sequencing reads recovered from the RexeedTM filtration compared to the unfiltered surface water. This overall approach combining remote sensing, filtration and sequencing provides a novel and potentially more effective, surveillance approach for AIv.