Avian influenza risk assessment for the Australian commercial chicken industry

The rapid expansion of commercial free range chicken farms in Australia has caused concern among industry experts that contact between wildlife and commercial chicken flocks will increase, therefore leading to increased exposure to low pathogenic AI (LPAI) virus from wild birds and subsequent mutation within the chicken flocks to high pathogenic avian influenza (HPAI). The probabilities involved with chickens being exposed to LPAI virus, the occurrence of subsequent spread of both LPAI and HPAI, as well as features or practices on farm that could mitigate the risks were largely unknown. This thesis describes the conduct of a farm survey and wildlife camera trapping to describe features related to farm design, management practices, biosecurity practices and wildlife visits on Australian commercial chicken farms, specifically; 15 non-free range meat chicken farms, 15 free range meat chicken farms, nine cage layer farms, nine barn layer farms and 25 free range layer farms in the Sydney basin bioregion and South East Queensland. It then describes the development, evaluation and sensitivity analysis of exposure and partial consequence risk assessment models using inputs from the farm survey, scientific literature and expert opinion to assess the risk of exposure and spread of LPAI and HPAI among these commercial chicken farm types in the Australian context. The exposure risk assessment model investigated the pathways of exposure of Australian commercial chicken farms to LPAI virus from Australian wild birds and estimated the probability of exposure occurring using scenario trees and a stochastic modelling approach. The partial consequence assessment following the exposure risk assessment model investigated the likelihood of spread of LPAI and HPAI without quantifying the impact of the consequences of spread within and between Australian commercial chicken farms

Comparisons of management practices and farm design on Australian commercial layer and meat chicken farms: Cage, barn and free range

There are few published studies describing the unique management practices, farm design and housing characteristics of commercial meat chicken and layer farms in Australia. In particular, there has been a large expansion of free range poultry production in Australia in recent years, but limited information about this enterprise exists. This study aimed to describe features of Australian commercial chicken farms, with particular interest in free range farms, by conducting on-farm interviews of 25 free range layer farms, nine cage layer farms, nine barn layer farms, six free range meat chicken farms and 15 barn meat chicken farms in the Sydney basin bioregion and South East Queensland. Comparisons between the different enterprises (cage, barn and free range) were explored, including stocking densities, depopulation procedures, environmental control methods and sources of information for farmers. Additional information collected for free range farms include range size, range characteristics and range access. The median number of chickens per shed was greatest in free range meat chicken farms (31,058), followed by barn meat chicken (20,817), free range layer (10,713), barn layer (9,300) and cage layer farms (9,000). Sheds had cooling pads and tunnel ventilation in just over half of both barn and free range meat chicken farms (53%, n = 8) and was least common in free range layer farms (16%, n = 4). Range access in free range meat chicken farms was from sunrise to dark in the majority (93%, n = 14) of free range meat chicken farms. Over half of free range layer farms (56%, n = 14) granted range access at a set time each morning; most commonly between 9:00 to 10.00am (86%, n = 12), and chickens were placed back inside sheds when it was dusk.This study was supported by Poultry Cooperative Research Centre (CRC), http://www. poultrycrc.com.au/about-us/. The Poultry CRC provided the majority of funding for this project included post-doc activities and a stipend for the PhD student. This study was also supported by Woolworths Limited, https://www.woolworths com.au/. Woolworths provided extra financial support for this project when needed. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscri

Low- and high-pathogenic avian influenza H5 and H7 spread risk assessment within and between Australian commercial chicken farms

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5–95%, 0.0058–0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10−5; 5–95%, 1.47 × 10−6–0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available.This study was funded by the Poultry Cooperative Research Centre (CRC) (Sub-project number 1.5.7) and by Woolworths Limited

Modelling high pathogenic avian influenza outbreaks in the commercial poultry industry

Highly pathogenic avian influenza (HPAI) outbreaks are devastating to poultry industries and pose a risk to human health. There is concern that demand for free-range poultry products could increase the number of HPAI outbreaks by increasing the potential for low pathogenic avian influenza (LPAI) introduction to commercial flocks.This project was supported financially by the Poultry CRC, Australia. We also thank the journal editor and reviewers for their insights and suggestions

Modelling the impact of biosecurity practices on the risk of high pathogenic avian influenza outbreaks in Australian commercial chicken farms

As of 2018, Australia has experienced seven outbreaks of highly pathogenic avian influenza (HPAI) in poultry since 1976, all of which involved chickens. There is concern that increases in free-range farming could heighten HPAI outbreak risk due to the potential for greater contact between chickens and wild birds that are known to carry low pathogenic avian influenza (LPAI).This project received financial support from the Poultry Cooperative Research Centre

Biosecurity practices on Australian commercial layer and meat chicken farms: Performance and perceptions of farmers.

This paper describes the level of adoption of biosecurity practices performed on Australian commercial chicken meat and layer farms and farmer-perceived importance of these practices. On-farm interviews were conducted on 25 free range layer farms, nine cage layer farms, nine barn layer farms, six free range meat chicken farms and 15 barn meat chicken farms in the Sydney basin bioregion and South East Queensland. There was a high level of treatment of drinking water across all farm types; town water was the most common source. In general, meat chicken farms had a higher level of adoption of biosecurity practices than layer farms. Cage layer farms had the shortest median distance between sheds (7.75m) and between sheds and waterbodies (30m). Equipment sharing between sheds was performed on 43% of free range meat chicken farms compared to 92% of free range layer farms. There was little disinfection of this shared equipment across all farm types. Footbaths and visitor recording books were used by the majority of farms for all farm types except cage layer farms (25%). Wild birds in sheds were most commonly reported in free range meat chicken farms (73%). Dogs and cats were kept across all farm types, from 56% of barn layer farms to 89% of cage layer farms, and they had access to the sheds in the majority (67%) of cage layer farms and on the range in some free range layer farms (44%). Most biosecurity practices were rated on average as 'very important' by farmers. A logistic regression analysis revealed that for most biosecurity practices, performing a practice was significantly associated with higher perceived farmer importance of that biosecurity practice. These findings help identify farm types and certain biosecurity practices with low adoption levels. This information can aid decision-making on efforts used to improve adoption levels

Low Pathogenic Avian Influenza Exposure Risk Assessment in Australian Commercial Chicken Farms

This study investigated the pathways of exposure to low pathogenic avian influenza (LPAI) virus among Australian commercial chicken farms and estimated the likelihood of this exposure occurring using scenario trees and a stochastic modeling approach following the World Organization for Animal Health methodology for risk assessment. Input values for the models were sourced from scientific literature and an on-farm survey conducted during 2015 and 2016 among Australian commercial chicken farms located in New South Wales and Queensland. Outputs from the models revealed that the probability of a first LPAI virus exposure to a chicken in an Australian commercial chicken farms from one wild bird at any point in time is extremely low. A comparative assessment revealed that across the five farm types (non-free-range meat chicken, free-range meat chicken, cage layer, barn layer, and free range layer farms), free-range layer farms had the highest probability of exposure (7.5 × 10−4; 5% and 95%, 5.7 × 10−4—0.001). The results indicate that the presence of a large number of wild birds on farm is required for exposure to occur across all farm types. The median probability of direct exposure was highest in free-range farm types (5.6 × 10−4 and 1.6 × 10−4 for free-range layer and free-range meat chicken farms, respectively) and indirect exposure was highest in non-free-range farm types (2.7 × 10−4, 2.0 × 10−4, and 1.9 × 10−4 for non-free-range meat chicken, cage layer, and barn layer farms, respectively). The probability of exposure was found to be lowest in summer for all farm types. Sensitivity analysis revealed that the proportion of waterfowl among wild birds on the farm, the presence of waterfowl in the range and feed storage areas, and the prevalence of LPAI in wild birds are the most influential parameters for the probability of Australian commercial chicken farms being exposed to avian influenza (AI) virus. These results highlight the importance of ensuring good biosecurity on farms to minimize the risk of exposure to AI virus and the importance of continuous surveillance of LPAI prevalence including subtypes in wild bird populations

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5–95%, 0.0058–0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10−5; 5–95%, 1.47 × 10−6–0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available

Comparisons of management practices and farm design on Australian commercial layer and meat chicken farms: Cage, barn and free range

<div><p>There are few published studies describing the unique management practices, farm design and housing characteristics of commercial meat chicken and layer farms in Australia. In particular, there has been a large expansion of free range poultry production in Australia in recent years, but limited information about this enterprise exists. This study aimed to describe features of Australian commercial chicken farms, with particular interest in free range farms, by conducting on-farm interviews of 25 free range layer farms, nine cage layer farms, nine barn layer farms, six free range meat chicken farms and 15 barn meat chicken farms in the Sydney basin bioregion and South East Queensland. Comparisons between the different enterprises (cage, barn and free range) were explored, including stocking densities, depopulation procedures, environmental control methods and sources of information for farmers. Additional information collected for free range farms include range size, range characteristics and range access. The median number of chickens per shed was greatest in free range meat chicken farms (31,058), followed by barn meat chicken (20,817), free range layer (10,713), barn layer (9,300) and cage layer farms (9,000). Sheds had cooling pads and tunnel ventilation in just over half of both barn and free range meat chicken farms (53%, n = 8) and was least common in free range layer farms (16%, n = 4). Range access in free range meat chicken farms was from sunrise to dark in the majority (93%, n = 14) of free range meat chicken farms. Over half of free range layer farms (56%, n = 14) granted range access at a set time each morning; most commonly between 9:00 to 10.00am (86%, n = 12), and chickens were placed back inside sheds when it was dusk.</p></div

Assessing the probability of introduction and spread of avian influenza (AI) virus in commercial Australian poultry operations using an expert opinion elicitation

<div><p>The objective of this study was to elicit experts’ opinions and gather estimates on the perceived probability of introduction and spread of avian influenza (AI) virus in the Australian broiler and layer industry. Using a modified Delphi method and a 4-step elicitation process, 11 experts were asked to give initial individual estimates for the various pathways and practices in the presented scenarios using a questionnaire. Following this, a workshop was conducted to present group averages of estimates and discussion was facilitated to obtain final individual estimates. For each question, estimates for all experts were combined using a discrete distribution, with weights allocated representing the level of expertise. Indirect contact with wild birds either via a contaminated water source or fomites was considered the most likely pathway of introduction of low pathogenic avian influenza (LPAI) on poultry farms. Presence of a water body near the poultry farm was considered a potential pathway for introduction only when the operation type was free range and the water body was within 500m distance from the shed. The probability that LPAI will mutate to highly pathogenic avian influenza (HPAI) was considered to be higher in layer farms. Shared personnel, equipment and aerosol dispersion were the most likely pathways of shed to shed spread of the virus. For LPAI and HPAI spread from farm to farm, shared pick-up trucks for broiler and shared egg trays and egg pallets for layer farms were considered the most likely pathways. Findings from this study provide an insight on most influential practices on the introduction and spread of AI virus among commercial poultry farms in Australia, as elicited from opinions of experts. These findings will be used to support parameterization of a modelling study assessing the risk of AI introduction and spread among commercial poultry farms in Australia.</p></div