Seroconversion to avian influenza virus in free-range chickens in the Riverland region of Victoria

Quantification of visits of wild fauna to a commercial free-range layer farm in the Netherlands located in an avian influenza hot-spot area assessed by video-camera monitoring

Free-range poultry farms have a high risk of introduction of avian influenza viruses (AIV), and it is presumed that wild (water) birds are the source of introduction. There is very scarce quantitative data on wild fauna visiting free-range poultry farms. We quantified visits of wild fauna to a free-range area of a layer farm, situated in an AIV hot-spot area, assessed by video-camera monitoring. A total of 5,016 hr (209 days) of video recordings, covering all 12 months of a year, were analysed. A total of 16 families of wild birds and five families of mammals visited the free-range area of the layer farm. Wild birds, except for the dabbling ducks, visited the free-range area almost exclusively in the period between sunrise and the moment the chickens entered the free-range area. Known carriers of AIV visited the outdoor facility regularly: species of gulls almost daily in the period January-August; dabbling ducks only in the night in the period November-May, with a distinct peak in the period December-February. Only a small fraction of visits of wild fauna had overlap with the presence of chickens at the same time in the free-range area. No direct contact between chickens and wild birds was observed. It is hypothesized that AIV transmission to poultry on free-range poultry farms will predominantly take place via indirect contact: taking up AIV by chickens via wild-bird-faeces-contaminated water or soil in the free-range area. The free-range poultry farmer has several possibilities to potentially lower the attractiveness of the free-range area for wild (bird) fauna: daily inspection of the free-range area and removal of carcasses and eggs; prevention of forming of water pools in the free-range facility. Furthermore, there are ways to scare-off wild birds, for example use of laser equipment or trained dogs.

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.

Longitudinal Study of Avian Influenza and Newcastle Disease in Village Poultry, Mali, 2009-2011

Newcastle disease (ND) is endemic in West Africa, which has also experienced outbreaks of highly pathogenic avian influenza (AI) H5N1 since 2006. We aimed to estimate the prevalence and incidence of AI and ND in village poultry in Mali and to identify associated risk factors. A longitudinal serologic study was conducted between November 2009 and February 2011 using ELISA commercial kits to detect antibodies. Sera (5963) were collected from 4890 different poultry. AI was rare, with a seroprevalence of 2.9% (95% confidence interval [CI] 2.3-3.5) and a seroincidence rate of 0.7 birds per 100 bird-months at risk (95% CI 0.4-1.0). AI antibodies were short lived, with a seroreversion rate of 25.4 birds per 100 bird-months at risk (95% CI 19.0-31.7). Risk factors for AI were limited: temporal variation occurred, but proximity to a water body was a risk factor only when large populations of wild waterbirds were present. ND was very common, with seroprevalence of 68.9% (95% CI 61.9-76.0) and a seroincidence rate of 15.9 birds per 100 bird-months at risk (95% CI 11.9-19.8). ND seroreversion rate was 6.2 birds per 100 bird-months at risk (95% CI 3.6-8.9). Regarding risk factors for ND, temporal variations occurred, and ND was more likely to be present in the Sudanian agro-ecological zone than in the Sahelian zone, in chickens than in other species, in flocks with higher numbers of Guinea fowl, and in flocks that had access to a waterbody. Control efforts would benefit from further increasing the ND vaccination coverage of village poultry, although this was already quite high (54.9%) for an African country. Seroconversion seemed satisfactory in vaccinated poultry, since 90.0% (95% CI 87.6-92.4) of these had ND antibodies. Further research should investigate the apparent lack of an epidemiologic role of domestic ducks for AI in Mali (unlike in Southeast Asia) and the potential role of Guinea fowl as a reservoir for ND.