Modelling of OJD : extension of project to include economic analysis and preparation of an existing package.

Under MLA Project OJD.027, the pathogenesis, epidemiology and options for control of Johne's disease in sheep were reviewed and mathematical models developed to simulate the spread of Johne’s disease within infected flocks, and between flocks on a regional basis. The models also allow the evaluation and comparison of various control options at both flock and regional levels. These models were completed during 2002, and a final report on the project prepared for MLA. However, for these models to be effectively used as an aid to the control of OJD in Australia, it is essential that managers and advisers involved in the OJD program at State and local levels are familiar with the models and with the predicted effects of various control strategies, at both farm and regional level. At the farm level, information on the predicted effect and cost-benefit of various strategies will assist advisers in formulating effective and efficient control strategies for individual farmers. Similarly at local and State/Regional level, the output of the regional spread model and simulated control strategies will assist disease managers to make informed decisions about preferred control options for OJD

Post-outbreak African horse sickness surveillance : a scenario tree evaluation in South Africa’s controlled area

An African horse sickness (AHS) outbreak occurred in March and April 2016 in the controlled area of South Africa. This extended an existing trade suspension of live equids from South Africa to the European Union. In the post‐outbreak period ongoing passive and active surveillance, the latter in the form of monthly sentinel surveillance and a stand‐alone freedom from disease survey in March 2017, took place. We describe a stochastic scenario tree analysis of these surveillance components for 24 months, starting July 2016, in three distinct geographic areas of the controlled area. Given that AHS was not detected, the probability of being free from AHS was between 98.3% and 99.8% assuming that, if it were present, it would have a prevalence of at least one infected animal in 1% of herds. This high level of freedom probability had been attained in all three areas within the first 9 months of the 2‐year period. The primary driver of surveillance outcomes was the passive surveillance component. Active surveillance components contributed minimally (<0.2%) to the final probability of freedom. Sensitivity analysis showed that the probability of infected horses showing clinical signs was an important parameter influencing the system surveillance sensitivity. The monthly probability of disease introduction needed to be increased to 20% and greater to decrease the overall probability of freedom to below 90%. Current global standards require a 2‐year post‐incursion period of AHS freedom before re‐evaluation of free zone status. Our findings show that the length of this period could be decreased if adequately sensitive surveillance is performed. In order to comply with international standards, active surveillance will remain a component of AHS surveillance in South Africa. Passive surveillance, however, can provide substantial evidence supporting AHS freedom status declarations, and further investment in this surveillance activity would be beneficial.http://wileyonlinelibrary.com/journal/tbed2021-04-08hj2020Production Animal StudiesVeterinary Tropical Disease

Longitudinal disease studies in small-holder black tiger shrimp (Penaeus monodon) farms in Andhra Pradesh, India. I. High prevalence of WSSV infection and low incidence of disease outbreaks in BMP ponds

A longitudinal study was conducted from January to August 2005 in small-holder black tiger shrimp (Penaeus monodon) ponds in the West Godavari District of Andhra Pradesh, India (16°25′ N, 81°19′ E). The study involved 457 ponds owned by low-income farmers participating in a better management practice (BMP) programme. Disease outbreaks occurred in 16.6% of ponds. There was significant spatial clustering of disease outbreaks with 31 (40.8%) of the 76 recorded disease outbreaks occurring in a single village block. Bivariate analysis indicated a 1.6-fold higher likelihood of disease outbreaks from nursery-stocked ponds but this was not significant in multivariate analysis due to the confounding effect of pond location. There was evidence of increasing prevalence of WSSV infection during grow-out. WSSV was detected in 5.9% of 119 batches of postlarvae tested at stocking, 38.2% of 34 juvenile batches collected at the time of transfer to grow-out ponds, and 47.0% of 336 pond stock tested at normal harvest or crop failure. WSSV was detected in 43 of 59 (72.9%) disease outbreak ponds tested and 115 of 277 (41.5%) non-outbreak ponds tested. Heavy WSSV infection was detected at harvest in 116 of the 336 (34.5%) of the ponds tested, including 78 ponds for which no outbreak was recorded. Duration of crop was recorded for 431 ponds with a mean of 117.0 days and a range of 20 to 176 days. Median duration was significantly shorter for disease outbreak ponds (68.5 days) compared to nonoutbreak ponds (119.0 days). Duration of crop also varied according to WSSV detection levels at harvest, with median duration for ponds classified as heavy WSSV infection (108.5 days) significantly shorter than for ponds classified as either light WSSV infection (116.0 days) or WSSV-negative (116.5 days). The study indicated a high risk of WSSV infection during grow-out but a relatively low incidence of disease despite a high prevalence of heavy WSSV infection in non-outbreak ponds

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Surveillance and risk assessment of Ovine Johne's disease in Australia

Ovine Johne’s disease (OJD) was first diagnosed in Australia in 1980, and by January 1998, more than 200 infected flocks had been identified in New South Wales, Victoria and South Australia. In 1998, in response to the increasing number of infected flocks and industry concerns about the spread of the disease, a 6-year, AUD 40.1 million national program commenced, with the aim of controlling the disease while further research was undertaken to evaluate future control or eradication options. This research was undertaken as part of the national OJD program, to improve our understanding of the performance of existing and new diagnostic tests for the disease, to estimate disease prevalence and distribution and to develop a simple, objective system for assessing flock-risk of infection. In the first study, the sensitivities and specificities of an absorbed enzyme-linked immunosorbent assay (ELISA) and an agar-gel immuno-diffusion (AGID) test for the detection of Johne’s disease in sheep were estimated using data from six known infected and 12 assumed uninfected sheep flocks. Logistic regression analysis was used to test for significant effects of lesion score and condition score, with flock included in the model as a random effect. Estimated specificities were 95% (95% CI: 93.4, 95.6%) and 99% (98.4, 99.4%) for ELISA cut-point ratios of 2.4 and 3.6 respectively, and 100% (99.7, 100.0%) for the AGID. Estimated sensitivities were 41.5% (35.0, 48.3%), 21.9% (16.6, 27.9%) and 24.6% (19.1, 30.7%) for ELISA cut-point ratios of 2.4 and 3.6 and for AGID, respectively. ELISA and AGID sensitivities varied between flocks and between categories of lesion score and condition score. Sensitivity was highest in thin sheep and iv in sheep with multibacillary lesions. The effects of lesion type and condition score on test sensitivity were both significant in the logistic regression analysis for the AGID and ELISA at both cut-points and the flock effect was significant for the AGID but not for the ELISA at either cut-point. In the second study, the flock-level sensitivity of pooled faecal culture and serological testing using AGID were compared in 296 flocks in New South Wales during 1998. The overall flock-sensitivity of pooled faecal culture was 92% (82.4%, 97.4%) compared to 61% (50.5%, 70.9%) for serology (assuming that both tests were 100% specific). In low-prevalence flocks (estimated prevalence <2%), the flock-sensitivities of pooled faecal culture and serology were 82% (57%, 96%) and 33% (19%, 49%) respectively, compared to 96% (85%, 99.5%) and 85% (72%, 93%) respectively in higher-prevalence flocks (estimated prevalence ≥2%). In a third study, the results of abattoir surveillance for OJD carried out during 2000 were analysed to estimate the prevalence of infected flocks in three regions of New South Wales and in other States. A Bayesian approach was used to adjust apparent prevalence estimates for the assumed flock-sensitivity and flock-specificity of abattoir surveillance, and to allow for uncertainty about the true values of these measures. The 95% probability limits for flock-prevalence at 31 December 2000 were 0.04% – 1.5%, 8% – 15% and 29% – 39% for low, moderate and high prevalence regions of New South Wales respectively. The other States generally had an upper 97.5% probability limit of about 1% or less. Based on this analysis, there were probably between 2,000 and 3,700 infected flocks in Australia at 31 December 2000, with more than 80% of these in a relatively small geographic area of central and southern New South Wales. v The final part of the current research was to develop a simple quantitative model for flock-risk of OJD, based on estimated flock-prevalence and within-flock prevalence for different classes of flocks, depending on their location and status. A method is also described for modifying this risk-score for individual flocks, according to the presence and level of individual flock risk factors such as the use of vaccination, testing history and the presence and number of infected neighbours. This flock-based approach to risk assessment could be supported by varying degrees of regulatory control over sheep movements, or could be adapted to a deregulated environment, with sheep producers taking responsibility for their own risk management, rather than the State or Territory regulatory authorities

Post-outbreak African horse sickness surveillance: A scenario tree evaluation in South Africa’s controlled area

An African horse sickness (AHS) outbreak occurred in March and April 2016 in the controlled area of South Africa. This extended an existing trade suspension of live equids from South Africa to the European Union. In the post‐outbreak period ongoing passive and active surveillance, the latter in the form of monthly sentinel surveillance and a stand‐alone freedom from disease survey in March 2017, took place. We describe a stochastic scenario tree analysis of these surveillance components for 24 months, starting July 2016, in three distinct geographic areas of the controlled area. Given that AHS was not detected, the probability of being free from AHS was between 98.3% and 99.8% assuming that, if it were present, it would have a prevalence of at least one infected animal in 1% of herds. This high level of freedom probability had been attained in all three areas within the first 9 months of the 2‐year period. The primary driver of surveillance outcomes was the passive surveillance component. Active surveillance components contributed minimally (<0.2%) to the final probability of freedom. Sensitivity analysis showed that the probability of infected horses showing clinical signs was an important parameter influencing the system surveillance sensitivity. The monthly probability of disease introduction needed to be increased to 20% and greater to decrease the overall probability of freedom to below 90%. Current global standards require a 2‐year post‐incursion period of AHS freedom before re‐evaluation of free zone status. Our findings show that the length of this period could be decreased if adequately sensitive surveillance is performed. In order to comply with international standards, active surveillance will remain a component of AHS surveillance in South Africa. Passive surveillance, however, can provide substantial evidence supporting AHS freedom status declarations, and further investment in this surveillance activity would be beneficial.http://wileyonlinelibrary.com/journal/tbed2021-04-08hj2020Production Animal StudiesVeterinary Tropical Disease

Creation and validation of a tool to measure the real population risk of speeding

Abstract Speeding is a significant contributor to the road toll. The risks associated with speeding at high and low levels are well understood, as are a range of speed management programs such as speed limits and speed cameras. Speed surveys have been used to help quantify the population distribution of speeding and to evaluate the impact of road safety interventions, especially since crashes are, statistically, rare events. Crash-based evaluations necessarily take time and are subject to high levels of random variation. In contrast, speed surveys can potentially be used to demonstrate the immediate impact of road safety interventions. The results of speed surveys are available long before the associated crash data has been collected and analysed. However, the achieved changes in the distribution of vehicle speeds need to be translated into changes in the likely number and severity of crashes