Estimating population sensitivity and confidence of freedom from highly pathogenic avian influenza in the Victorian poultry industry using passive surveillance.

Highly pathogenic avian influenza (HPAI) is a serious disease affecting multiple organ systems and resulting in high levels of mortality in domestic poultry and may also be a serious zoonotic condition. In July-August 2020, HPAI was confirmed on 3 egg-laying chicken farms in Victoria, Australia, while a further two turkey farms and one emu farm were diagnosed with low pathogenicity viruses. All six farms were depopulated and decontaminated by 26 November 2020 and Australia declared regained freedom from HPAI on 26 February 2021. As part of the follow-up surveillance in support of claiming HPAI freedom, a scenario-tree model was developed to estimate the population sensitivity of passive surveillance for the detection of HPAI in the Victorian commercial poultry industry, and to also estimate the confidence of freedom from HPAI provided by passive surveillance, predicted over a 2-year period. Risk factors included in the model were industry sector (breeder, broiler, layer and other), flock size: small commercial (50 ≤ 5000 birds) or large commercial (> 5000 birds) and housing type (cage, barn or free-range). A detection cascade was also modelled, with probabilities allocated, to estimate the flock sensitivity for flocks in each risk stratum. System sensitivity and confidence of freedom were then estimated across all flocks in the industry. Design prevalence was set at 1, 2, 5 or 10 infected flocks and prior confidence of freedom at 0.5. Other model inputs were entered as probability distributions and the model was simulated for 10,000 iterations. Outputs were expressed as median and 95% probability intervals (PI), with the time period for analysis set at 1 month. Median system sensitivity was 0.58 (95% PI: 0.47-0.69) per time period for a single infected flock, increasing to 0.81, 0.985 and 0.9998 for 2, 5 and 10 infected flocks respectively. Median confidence of freedom was > 0.7 (95% PI: 0.65-0.76) after one time period and exceeded 0.95 and 0.99 after 4 and 7 months, respectively for one infected flock and 2 and 3 months respectively for 2 infected flocks. These results support the conclusion that passive surveillance is a highly effective tool for the detection of HPAI in commercial poultry and add further weight to evidence that HPAI has been successfully eradicated from the Victorian poultry industry and that the industry has regained HPAI free status.

Use of scenario tree modelling to plan freedom from infection surveillance: Mycoplasma bovis in New Zealand.

Since mid-2018, the New Zealand (NZ) Ministry for Primary Industries (MPI) has been operating an eradication program for an incursion of Mycoplasma bovis. Although NZ is still delimiting the outbreak, consideration is being given to how freedom from M. bovis will be demonstrated. Rapid demonstration of freedom will minimise the length of the program, significantly reducing its financial burden. This collaborative research was undertaken to help inform planning of surveillance to demonstrate freedom after M. bovis is believed eradicated. Scenario tree modelling (STM) involves assimilating multiple surveillance system components to determine whether disease is absent. STM has infrequently been used to plan appropriate surveillance but this was the approach used here. A stochastic simulation model was implemented in R. The model represented the NZ commercial dairy and non-dairy cattle industries and the current surveillance components that are also planned to be used to gather evidence of absence of M. bovis once it is eradicated. Different surveillance intensities and risk based versus random surveillance were simulated and compared for probability of freedom, financial cost of sampling and testing and the time to demonstrate freedom. The results indicate that the current surveillance components will enable demonstration of freedom. Surveillance components included bulk tank milk testing, herd testing and testing at meat processing plants, predominantly using an imperfect ELISA. Several combinations of surveillance components appeared most efficient achieving >95 % confidence of freedom over 2-4 years, whilst sampling 4-7 % of the non-dairy herds and less than 25 % of dairy herds annually. The results indicate that surveillance intensity can be lower than is currently occurring to support the delimiting phase, thereby saving significant resources in the post eradication phase (proof of freedom phases). Further consideration is required to enable the assumption of 100 % herd specificity made in the model to be achieved. The ELISA used is very specific, but will yield some false positives that must be resolved to their true status. This may occur for example through modified diagnostic test interpretation (e.g. cut point optimisation at individual and herd level) or resolution of putative false positive herds with epidemiological investigation. In conclusion this research demonstrates the utility of STM for planning surveillance programs, and in this instance has highlighted efficient and effective surveillance components for demonstrating freedom from M. bovis in NZ. It also highlights the need to achieve 100 % specificity for M. bovis in herds tested during the proof of freedom phases.

Comparison of the current abattoir surveillance system for detection of paratuberculosis in Australian sheep with quantitative PCR tissue strategies using simulation modelling.

Abattoir surveillance for Johne's disease monitoring in Australia has provided valuable feedback to producers about their flock's disease status since its commencement in 1999. The current surveillance system relies on the identification of gross lesions in sheep carcases at an abattoir, followed by sampling and histopathology testing. This manual inspection system has not been adapted to meet the changing disease situation, as infection prevalence levels have declined over time due to vaccination. This simulation study compares the current system with two alternative approaches utilising a validated quantitative (q)PCR method for the detection of Mycobacterium avium subsp. paratuberculosis in tissues, with random systematic sampling either alone or in conjunction with sampling of a single carcass presenting gross lesions. Consigned sheep were randomly simulated as either infected or uninfected according to defined prevalence levels of infection, with varying histopathological lesion severity and the presence or absence of gross lesions. These sheep were then allocated into multiple 'lines' (group of sheep slaughtered together) within each consignment, with each line subjected to testing with the three sampling strategies for the estimation of line and flock (consignment) sensitivity. The line sensitivity described the proportion of infected lines that tested positive, whereas the flock sensitivity was the proportion of consignments from the simulated infected flocks that had one or more lines test positive for paratuberculosis infection. The tissue qPCR strategy with gross lesion detection achieved marginally higher line sensitivity than the current abattoir surveillance strategy. The simulation of unvaccinated infected flocks with low to moderate prevalence levels demonstrated similar flock sensitivity for all three sampling models. However, the current strategy had very low line sensitivity for the simulated vaccinated infected flocks when the infection prevalence level was <2%. There were substantial differences in flock sensitivity between the two tissue qPCR approaches and the current abattoir surveillance strategy for vaccinated infected flocks, whereas, only marginal differences in flock sensitivity were evident between the two tissue qPCR models. Our results demonstrate that the current strategy is not effective at identifying infected animals at very low infection prevalence levels. The tissue qPCR approach investigated in this study is better as it removes the reliance on meat inspectors to identify gross lesions and can also assist in identifying flocks that have subclinical infected sheep not displaying gross lesions. Therefore, the sheep industry may benefit from incorporating tissue qPCR for Johne's disease surveillance, however the logistics and costs of conducting this type of testing would need to be considered prior to implementing any changes.

Simulation modelling to estimate the herd-sensitivity of various pool sizes to test beef herds for Johne's disease in Australia.

Johne's disease is a chronic intestinal disease affecting livestock. It leads to the shedding of Mycobacterium avium subspecies paratuberculosis (MAP) in the faeces, wasting and eventually death, with animal welfare, economic, and trade implications. The Johne's Beef Assurance Scheme, used in Australia to determine the risk of Johne's disease on beef properties and facilitate trade, is based on testing a subset of the herd with pooled faecal quantitative PCR. This study aimed to model the herd-sensitivity of pooled faecal testing under different Australian farming scenarios. Animals from simulated herds were randomly sampled and allocated into their respective pools. Each tested pool was provided a test outcome, with herd-sensitivity estimated as the probability of detecting a truly infected herd. The models simulated the test performance for the 'Sample' and 'Check' tests used in the assurance schemes (recommended sample sizes of 300 and 50, respectively) for a range of herd sizes, infection prevalence and MAP faecal shedding levels for the pool sizes of 5, 10, 15 and 20. Sensitivity and specificity input values of each pool size were obtained from a previous laboratory investigation. The herd-sensitivity estimate increased with herd size and infection prevalence levels, regardless of the pool size. Higher herd-sensitivity was also achieved for testing scenarios involving larger sample sizes. A pool size of 10 achieved similar herd-sensitivity to that of the current pool size for the majority of the Sample test and Check test scenarios. This was particularly evident when pool-specificity was assumed to be perfect. The overall herd-sensitivity of the Check test was very low for all infection prevalence levels and pool sizes, but it more than doubled, when the sample size increased from 50 to 100 animals (11% versus 26% for a herd size of 500 cattle with a 2% infection prevalence). The results show that the majority of beef producers participating in the assurance scheme can benefit from using a larger pool size for the pooled faecal quantitative PCR testing of their herd, in comparison to the pool size currently used.

Determining an optimal pool size for testing beef herds for Johne's disease in Australia.

Bovine Johne's disease (JD) is a chronic debilitating disease affecting cattle breeds worldwide. Pooled faecal samples are routinely tested by culture to detect Mycobacterium avium subsp. paratuberculosis (Mptb) infection. More recently, a direct high throughput molecular test has been introduced in Australia for the detection of Mptb in faeces to circumvent the long culture times, however, the optimal pool size for beef cattle faeces is not known. This study aimed to determine the optimal pool size to achieve the highest test sensitivity and specificity for beef cattle. Individual archived faecal samples with low, medium and high quantities of Mptb (n = 30) were pooled with faecal samples from confirmed JD negative animals to create pool sizes of 5, 10, 15 and 20, to assess the diagnostic sensitivity relative to individual faecal qPCR. Samples from JD-free cattle (n = 10) were similarly evaluated for diagnostic specificity. Overall, 160 pools were created, with Mptb DNA extracted using magnetic bead isolation method prior to Mptb-specific IS900 quantitative PCR (qPCR). The pool size of 10 yielded the highest sensitivity 73% (95% CI: 54-88%), regardless of the quantity of Mptb DNA present in the faeces. There was no significant differences between the four different pool sizes for positive pool detection, however, there was statistical significance between low, medium and high quantities of Mptb. Diagnostic specificity was determined to be 100%. The increase in pool size greater than 10 increased the chances of PCR inhibition, which was successfully relieved with the process of DNA dilution. The results of this study demonstrate that the pool size of 10 performed optimally in the direct faecal qPCR. The results from this study can be applied in future simulation modelling studies to provide suggestions on the cost-effective testing for JD in beef cattle.

Field evaluation of an equine influenza ELISA used in New South Wales during the 2007 Australian outbreak response.

During the Australian epidemic of equine influenza in 2007, tens of thousands of horses were infected. From the resulting field data, 475 known infected and 1323 uninfected horses were identified to allow a post outbreak evaluation of the performance of the commonly used bELISA for influenza A under field conditions. A variety of techniques, such as ROC plots, area under the curve and hypothesis testing were used to assess the overall performance of the test. The test was deemed to be accurate (area under curve=0.993+/-0.003 standard error) and significantly informative (z=-32.0; p<0.0001). Sensitivity and specificity of the test as used in the response (cut-point percentage inhibition> or =50) were 0.992 (95% CI: 0.979-0.997) and 0.967 (95% CI: 0.957-0.976), respectively.