OBJECTIVES:To analyse longitudinal change in motor neuron disease (MND) mortality in Australia from 1986 to 2023. DESIGN:Australian population-based study of MND mortality. SETTING:All MND mortality and Australian population data from 1 January 1986 to 31 December 2023 were obtained from the Australian Bureau of Statistics. MAIN OUTCOME MEASURES:MND mortality records were analysed, and certified deaths were summarised by year of registration. MND mortality rates, 95% confidence intervals (CIs) and Joinpoint regression trends were calculated. Data were further subset by demographic and geographical categories to report Australian MND mortality by age group, sex, state/territory location and remoteness areas classification. RESULTS:In Australia, the total number of MND deaths more than tripled over the past 37 years, from 238 in 1986 to 781 in 2023. The unadjusted mortality rate in 1986 was 1.49 (95% CI, 1.30-1.69) per 100,000 population and increased to 2.93 (95% CI, 2.73-3.14) per 100,000 population by 2023. After age standardisation, the annual percentage change across 1986-2023 was determined to be 0.47% (95% confidence limit, 0.16-0.86). Joinpoint modelling suggests a more recent reduction in adjusted mortality rates. In 2023, MND accounted for 0.43% of all-cause deaths in Australia, increasing from 0.21% in 1986. The number of MND deaths in Australia peaked at age 70-79 years. MND mortality was higher among men than women (rate ratio, 1.41; 95% CI, 1.33-1.51). MND mortality rates were similar among New South Wales, Victoria and Queensland (2.93, 3.08 and 2.85 per 100,000 population, respectively), with higher rates in South Australia and Tasmania (3.44 and 4.12 per 100,000 population, respectively). MND mortality rates were higher in inner and outer regional areas (3.90 and 3.24 per 100,000 population, respectively) compared with major cities (2.79 per 100,000 population). CONCLUSIONS:Adjusted MND mortality rates in Australia increased over 37 years.

To measure access to social services (primary health care, early childhood care/education, and public transport), we created two social service access indexes (SSPT and SSI) for Australian capital cities. We show that only two cities, Melbourne and Sydney, have some limited characteristics of a compact or 15-minute city, but only in the city centres and inner city areas where population densities are highest and have less low density housing types. In the outer suburban and peri-urban areas, as well as across all of the remaining cities, proximity to social services is poor and residents suffer the consequences of spatial inequity.

Background Globally, rapid urbanisation occurs alongside stalled progress on transport-related Sustainable Development Goals. While urban form's impact on population health is documented, its specific effects on mobility and road safety in developing-country cities are largely absent from the literature. The spatial and socioeconomic diversity of Global South cities complicates safety analyses based solely on micro (segments) or macro (aggregate) scales. Consequently, the influence of meso-level urban fabric on road safety remains poorly understood. Methods Two sets of stratified Generalised Linear Models at the meso level (districts and neighbourhoods) are developed; collision-prone zones are mapped, and a multilevel analysis is performed by integration with micro and macro level analysis from previous research. Results and discussion Road network spatial arrangement best predicted zonal risk, outperforming demographic, land use, and travel demand patterns. Four urban form types were identified, revealing both expected (riskier low-mixture areas) and counter-intuitive (riskier planned areas, indicating car-centric planning) results. Moreover, meso-level analysis identified areas missed by micro and macro approaches, revealing new intervention opportunities through urban redevelopment and land use policies. Overall, the findings indicate urban design drives road risk and emphasise the importance of the analysis level. This approach integrates road safety into urban planning research and practice and informs urban mobility governance.

Real-time assessment of drivers' cognitive states is critical for improving road safety, especially in freight transport, where long-haul truck drivers frequently encounter prolonged fatigue and diverse traffic interactions. Current methods for cognitive state prediction predominantly rely on subjective surveys or unimodal physiological data, which are invasive, limited in scalability, and insufficient to capture the dynamic interplay between driver behavior, vehicle dynamics, and environmental context. To address this gap, this paper proposes a multimodal attention neural network (MMANN) framework that integrates three asynchronous data streams: vehicle kinematics, driver facial states captured via low-frequency imaging, and driving environment videos. The proposed model utilizes interpretable attention mechanisms to fuse multimodal data, facilitating the classification of cognitive states into low-activity (characterized by distraction or fatigue), normal-activity, or high-activity (indicative of stress or aggressive driving). Trained on an extensive 180-day naturalistic dataset, MMANN achieves an impressive recognition accuracy of 82.4%-a notable improvement of 8.6% over single-modal baselines. This research pioneers the development of adaptive cognitive models, specifically tailored to the unique operational patterns and environmental constraints of truck driving, thereby enabling real-time safety interventions such as adaptive warning strategies and prioritized hazard alerts.

BACKGROUND:Rapid declines in city mobility during the early stages of the COVID-19 pandemic in 2020 resulted in reductions in citizens' exposure to transport-related air pollution and associated health risks as many cities introduced non-pharmaceutical interventions designed to curb the spread of COVID-19. However, these benefits soon reversed during the pandemic's recovery phase (ie, from September, 2020, onwards), especially in cities with designs that afforded mode shifts away from public and active transport in favour of private motor vehicles. The aim of this study was to understand the association between global city designs, transport mode choices, and population-level risk exposure during 2020. METHODS:In this retrospective observational analysis, we assembled and analysed spatial datasets (including historical and predicted pollution levels, mobility indicators, and measures of individual disease transmission) and clustered 507 global cities using a graph neural network approach based on measures of the structural dimensions of each individual city's design and network structures of urban transportation systems. We compared city types on the basis of transportation mode shifts, air pollution levels, and associated health outcomes (ie, cardiovascular disease, ischaemic heart disease, respiratory disease, asthma, and reported COVID-19 cases) throughout 2020. We estimated risk reductions for these health outcomes across four phases of the pandemic, which we defined as the pre-pandemic, entry, mid-crisis, and recovery phases. We also identified city designs showing sustained reductions at the end of 2020 in transport-related air pollution (fine particulate matter [PM2·5] and nitrogen dioxide [NO2]) associated with reduced estimated risk of acute and chronic disease outcomes (ie, all-cause mortality, ischaemic heart disease mortality, cardiovascular disease, respiratory disease, and asthma). FINDINGS:The mean estimated reduction of global NO2 concentrations across the observed cities from the beginning of the entry phase until the mid-crisis phase was 3·76 parts per billion (ppb), calculated as the difference between observed 2020 mean levels of 12·63 ppb and predicted mean levels (if the pandemic and mobility restrictions had not occurred) of 16·39 ppb. The mean estimated reduction of global PM2·5 concentrations across the observed cities was 9·76 μg/m3 (the difference between observed 2020 mean levels [29·03 μg/m3] and predicted mean levels [38·79 μg/m3]). If maintained over the long term, the estimated NO2 reduction could have a substantial effect on reducing health risks for both acute and chronic disease, equating to an estimated overall reduction in all-cause mortality risk of 1·5% (95% CI 2·2-3·0), a reduction in cardiovascular mortality risk of 4·1% (2·6-6·0), and a reduction in respiratory disease mortality risk of 1·9% (0·8-3·0). If the reduction in PM2·5 concentration estimated in this period was maintained over the long term, all-cause mortality risk reductions of 18·9% (95% CI 13·2-25·0), asthma risk reductions of 46·8% (18·7-65·5), and ischaemic heart disease morbidity risk reductions of 0·25% (0·2-0·3) could be achieved. In the later stages of 2020, city designs (primarily in the Americas and Oceania) that afforded a mode shift away from public transit to private motor vehicles during the pandemic's recovery phase tended to show the poorest outcomes across all air pollution and health measures, even increasing risk levels above pre-pandemic baselines in some cases. By contrast, cities located in Japan and South Korea showed little change in pre-crisis and post-crisis transport mode choice, maintaining comparatively low levels of air pollution and associated disease risk, and reduced rates of infectious disease transmission throughout the 2020 observation period. Contrasting experiences of road injury in the post-pandemic phase (ie, post 2020) were also observed between these locations. INTERPRETATION:Our results highlight the transient environmental and health benefits observed during the early stages of the COVID-19 pandemic, driven by substantial reductions in transport-related air pollution and associated health risks due to imposed non-pharmaceutical public health interventions. City design appears to have played a crucial role in observed pollution and health risk differences between cities, with those that afforded a shift away from public and active transport towards private vehicles witnessing a rapid erosion of pollution-related health benefits gained in the entry to mid-crisis phases of the pandemic. These negative effects appear to have also transferred through to increased rates of road trauma in these cities, with a resurgence in road injury above pre-pandemic levels, particularly within countries reliant on private motorised transport. Conversely, cities in Japan, South Korea, and some European regions, which did not experience modal shifts towards cars, sustained their reductions in air pollution and have continued along a trend of declining road transport injuries. These findings underscore city design as a key factor in navigating pandemic-related challenges and suggest that city designs with higher levels of public and mass transit show greater levels of resilience when confronted with infectious disease threats. FUNDING:Australian National Health and Medical Research Council, Australian Research Council, National Institute for Health and Care Research Global Health Research Centre for Non-Communicable Diseases and Environmental Change, UK Prevention Research Partnership, and Economic and Social Research Council.

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021, 2022 and 2023. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the seventh report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. We also examine selected indicators of trends in health and climate change in New Zealand. Our analyses show the exposure to heatwaves is growing in Australia, increasing the risk of heat stress and other health threats such as bushfires and drought. Our analyses also highlight continuing deficiencies in Australia's response to the health and climate change threat. A key component of Australia's capacity to respond to bushfires, its number of firefighting volunteers, is in decline, dropping by 38 442 people (17%) in just seven years. Australia's total energy supply remains dominated by fossil fuels (coal, oil and natural gas), and although energy from coal decreased from 2021 to 2023, energy from oil increased, and transport energy from petrol grew substantially in 2021-22 (the most recent year for which data are available). Greenhouse gas emissions from Australia's health care sector in 2021 rose to their highest level since 2010. In other areas some progress is being made. The Australian Government completed the first pass of the National Climate Risk Assessment, which included health and social support as one of the eleven priority risks, based in part on the assessed severity of impact. Renewable sources such as wind and solar now provide almost 40% of Australia's electricity, with growth in both large-scale and small-scale (eg, household) renewable generation and battery storage systems. The sale of electric vehicles reached an all-time high in 2023 of 98 436, accounting for 8.47% of all new vehicle sales. Although Australia had a reprieve from major catastrophic climate events in 2023, New Zealand experienced cyclone Gabrielle and unprecedented floods, which contributed to the highest displacement of people and insured economic losses over the period of our analyses (ie, since the year 2010 and 2000 respectively). Nationally, regionally and globally, the next five years are pivotal in reducing greenhouse gas emissions and transitioning energy production to renewables. Australia is now making progress in this direction. This progress must continue and accelerate, and the remaining deficiencies in Australia's response to the health and climate change threat must be addressed. There are strong signs that Australians are increasingly engaged and acting on health and climate change, and our new indicator on health and climate change litigation in Australia demonstrates the legal system is active on this issue in this country. Our 2022 and 2023 reports signalled our intentions to introduce indicators on Aboriginal and Torres Strait Islander health and climate change, and mental health and climate change in Australia. Although the development of appropriate indicators is challenging, these are key areas and we expect our reporting on them will commence in our next report.

This study employed Bayesian latent class analyses to estimate the diagnostic accuracy of faecal egg count (FEC), milk spot detection and the ELISA for detection of Ascaris suum using matched samples from individual pigs in Australia. A total of 251 blood, faecal and liver samples were collected from finisher pigs from four Victorian pig farms. Matched samples (n = 189) were used to compare the three diagnostic tests. The ELISA detected a higher proportion of positive samples (56 %; 95 % CI 48-62 %) compared to milk spot detection (42 %; 95 % CI 35-49 %) and FEC (17 %; 95 % CI 12-23 %). Only the ELISA detected A. suum infections on two of the four farms, with 14 % and 41 % within-farm prevalence estimates. Agreement between diagnostic tests was moderate for FEC and milk spot detection (Cohen's kappa 0.42; 95 % CI 0.30-0.53) and ELISA and milk spot detection (0.52; 0.41-0.64), while fair agreement was observed between FEC and ELISA (0.28; 0.19-0.37). Our latent class analyses identified a higher diagnostic sensitivity for the ELISA (0.92; 95 % CrI [credible interval] 0.86-0.96) than FEC (0.43; 0.34-0.53) and milk spot detection (0.86; 0.79-0.92). A strong association was observed between ELISA outcomes (optical density [OD] and OD ratio [ODr]) and milk spot grades (low, medium, high), with higher OD and ODr values corresponding to an increased number of milk spots on the liver. This study highlights the limitations of conventional A. suum detection methods. Quantitative estimates of the diagnostic sensitivity of the ELISA facilitate its use as a tool for assessing A. suum exposure in pig herds.

Bike-riding GPS data offers detailed insights and individual-level mobility information which are critical for understanding bike-riding travel behaviour, enhancing transportation safety and equity, and developing models to estimate bike route choice and volumes at high spatio-temporal resolution. Yet, large-scale bicycling-specific GPS data collection studies are infrequent, with many existing studies lacking robust spatial and/or temporal coverage, or have been influenced by sampling biases leading to these data lacking representativeness. Additionally, accurately detecting bike-riding trips from continuously collected raw GPS data without human intervention remains a challenge. This study presents a novel GPS data collection approach by leveraging the combination of a smartphone application with a Bluetooth beacon attached to a participant's bike. Aided by minimal heuristic post-processing, our method limits data collection to trips taken by bike without the need for participant intervention, carefully optimising between survey participation, privacy challenges, participant workload, and robust bike-riding trip detection. Our method is applied to collect 19,782 bike trips from 673 adults spanning eight months and three seasons in Greater Melbourne, Australia. The collected dataset is shown to represent the underlying adult bike-riding population in terms of demographics (sex, occupation and employment type), temporal and spatial patterns. The average trip length (median = 4.8 km), duration (median = 20.9 min), and frequency of bicycling trips (median = 2.7 trips/week) were greater among men, middle-aged and older adults. The 'Interested but Concerned' riders (classified using Geller typology) rode more frequently, while the 'Strong and Fearless' and 'Enthused and Confident' groups rode greater distances and for longer. Participants rode on roads/streets without bike infrastructure for more than half of their trips by distance, while spending 24% and 17% on off-road paths and bike lanes respectively. This populationrepresentative dataset will be key in the context of urban planning and policymaking.

A factor constraining the elimination of dog-mediated human rabies is limited information on the size and spatial distribution of free-roaming dog populations (FRDPs). The aim of this study was to develop a statistical model to predict the size of free-roaming dog populations and the spatial distribution of free-roaming dogs in urban areas of Nepal, based on real-world dog census data from the Himalayan Animal Rescue Trust (HART) and Animal Nepal. Candidate explanatory variables included proximity to roads, building density, specific building types, human population density and normalised difference vegetation index (NDVI). A multivariable Poisson point process model was developed to estimate dog population size in four study locations in urban Nepal, with building density and distance from nearest retail food establishment or lodgings as explanatory variables. The proposed model accurately predicted, within a 95% confidence interval, the surveyed FRDP size and spatial distribution for all four study locations. This model is proposed for further testing and refinement in other locations as a decision-support tool alongside observational dog population size estimates, to inform dog health and public health initiatives including rabies elimination efforts to support the ‘zero by 30’ global mission.

The need for strengthening national capacities for disease prevention, preparedness, and response is increasingly becoming urgent. Central to this is strengthening existing systems and workforce capacity for disease surveillance and disease outbreak response. This study aimed to evaluate the national capacity and needs of veterinary services in Vietnam in animal disease surveillance and outbreak investigation skills. A cross-sectional, convergent, mixed-methods study was conducted between November 2020 and April 2021. An online questionnaire was administered to government field veterinarians, followed by descriptive and multivariable analyses to understand field capacity, specifically levels of experience in outbreak investigation and animal health surveillance. Semi-structured interviews were conducted with various stakeholders in veterinary services and interview transcripts were coded and thematically analyzed. Qualitative results were used to contextualize quantitative findings from the survey. Overall, 178 field veterinary staff completed the online survey, and 25 stakeholders were interviewed. Eighty percent of respondents reported a high priority for further training in both animal disease surveillance and outbreak investigation. Training and competence were more limited at the district and commune levels, highlighting a gap in capacity at the subnational level. Reasons included a lack of in-depth training opportunities, limited access to resources and high staff turnover. Respondents who completed postgraduate qualifications in epidemiology or Field Epidemiology Training Programs were more likely to have higher levels of experience in animal health surveillance and outbreak investigation. This study identified gaps in knowledge and adoption of practices most often related to local-level or less experienced veterinary staff with limited training opportunities in epidemiology. Findings inform the prioritization of training and planning activities to further enhance the national capacity of veterinary services in Vietnam. Underlying explanations for existing gaps in capacity include inequities in skill development and training opportunities across levels of veterinary staff, gaps in the chain of command and unequal funding across provinces.

Coxiella burnetii, the causative agent of Q fever, is a zoonotic bacteria of global public health significance. The organism has a complex, diverse, and relatively poorly understood animal reservoir but there is increasing evidence that macropods play some part in the epidemiology of Q fever in Australia. The aim of this cross-sectional survey was to estimate the animal- and tissue-level prevalence of coxiellosis amongst eastern grey (Macropus giganteus) and red (Osphranter rufus) kangaroos co-grazing with domestic cattle in a Q fever endemic area in Queensland. Serum, faeces and tissue samples from a range of organs were collected from 50 kangaroos. A total of 537 tissue samples were tested by real-time PCR, of which 99 specimens from 42 kangaroos (84% of animals, 95% confidence interval [CI], 71% to 93%) were positive for the C. burnetii IS1111 gene when tested in duplicate. Twenty of these specimens from 16 kangaroos (32%, 95% CI 20% to 47%) were also positive for the com1 or htpAB genes. Serum antibodies were present in 24 (57%, 95% CI 41% to 72%) of the PCR positive animals. There was no statistically significant difference in PCR positivity between organs and no single sample type consistently identified C. burnetii positive kangaroos. The results from this study identify a high apparent prevalence of C. burnetii amongst macropods in the study area, albeit seemingly with an inconsistent distribution within tissues and in relatively small quantities, often verging on the limits of detection. We recommend Q fever surveillance in macropods should involve a combination of serosurveys and molecular testing to increase chances of detection in a population, noting that a range of tissues would likely need to be sampled to confirm the diagnosis in a suspect positive animal.

Over the past two decades, there has been exponential growth in the daily use of big data across the globe; facilitated in part by ever-increasing sophistication in data processing. Innovations in big data collection and analysis allow governments to not only monitor their own technology and deployments, for example, but to rapidly enhance existing transport systems. Industry and government alike are using innovations in big data technology to restructure transport systems, thereby enhancing the sustainability of urban mobility along with integrating new and alternative modes. Discussed in the chapter are notable examples of recent big data applications including in-vehicle telematics, Mobility-as-a-Service, on-demand transport, and electric micro-mobility. As the mobility industry and governments increasingly become key players in shaping cities, we will continue to see ongoing innovation and unprecedented change in how transport systems unfold.

Infectious bronchitis virus (IBV), an avian coronavirus, can be isolated and cultured in tracheal organ cultures (TOCs), embryonated eggs and cell cultures, the first two of which are commonly used for viral isolation. Previous studies have suggested that foetal bovine serum (FBS) can inhibit coronavirus replication in cell cultures. In this study, the replication of IBV in chicken embryo kidney (CEK) cell cultures and the Leghorn hepatocellular carcinoma (LMH) cell line was assessed using two different cell culture media containing FBS or yeast extract (YE) and two different IBV strains. The highest concentrations of viral genomes were observed when the cell culture medium (CEK) contained YE. Similar results were observed in LMH cells. Examination of the infectivity by titration demonstrated that the cell lysate from CEK cell cultures in a medium including YE contained a higher median embryo infectious dose than that from CEK cell cultures in a medium containing FBS. These results indicate that improved replication of IBV in cell cultures can be achieved by replacing FBS with YE in the cell culture medium.

Infectious disease forecasting has become increasingly important in public health, as demonstrated during the COVID-19 pandemic. However, forecasting tools for emergency animal diseases, particularly those offering real-time decision support when parameters governing disease dynamics are unknown, remain limited. We introduce a generalised modelling framework for near-real-time forecasting of the temporal and spatial spread of infectious livestock diseases using data from the early stages of an outbreak. We applied the framework to the 2007 equine influenza outbreak in Australia, generating prediction targets at three timepoints across four regional clusters. Our targets included future daily case counts, outbreak size, peak timing and duration, and spatial distributions of future spread. We evaluated how well the forecasts predicted daily cases and the spatial distribution of case counts, using skill scores as a benchmark for future model improvements. Forecast accuracy, certainty, and skill improved significantly after the outbreak's peak, while early predictions were more variable, suggesting that pre-peak forecasts should be interpreted with caution. Spatial forecasts maintained positive skill throughout the outbreak, supporting their use in guiding response priorities. This framework provides a tool for real-time decision-making during livestock disease outbreaks and establishes a foundation for future refinements and applications to other animal diseases. ### Competing Interest Statement The authors have declared no competing interest.

Q fever is an important zoonotic disease with a worldwide distribution. Outbreaks of Q fever are unpredictable and can affect many people, resulting in a significant burden on public health. The epidemiology of the disease is complex and substantial efforts are required to understand and control Q fever outbreaks. The purpose of this study was to systematically review previous investigations of outbreaks and summarise important epidemiological features. This will improve knowledge of the factors driving the occurrence of Q fever outbreaks and assist decision makers in implementing mitigation strategies. A search of four electronic databases identified 94 eligible articles published in English between 1990 and 2022 that related to 81 unique human Q fever outbreaks. Outbreaks were reported across 27 countries and mostly in industrialised nations. Documented Q fever outbreaks varied in size (2 to 4107 cases) and duration (4 to 1722 days). Most outbreaks (43/81) occurred in communities outside of traditional at-risk occupational settings and were frequently associated with living in proximity to livestock holdings (21/43). Indirect transmission via environmental contamination, windborne spread or fomites was the most common route of infection, particularly for large community outbreaks. Exposure to ruminants and/or their products were confirmed as the principal risk factors for infection, with sheep (28/81) as the most common source followed by goats (12/81) and cattle (7/81). Cooperation and data sharing between human and animal health authorities is valuable for outbreak investigation and control using public health and veterinary measures, but this multisectoral approach was seldom applied (14/81). Increased awareness of Q fever among health professionals and the public may facilitate the early detection of emerging outbreaks that are due to non-occupational, environmental exposures in the community.

Brucella suis infection of dogs is an emerging issue worldwide requiring specific management to address zoonotic risks and animal welfare concerns. Diagnosis in dogs is routinely based on serological testing, but to date these tests have only been validated for use in production animal species and humans. This study aimed to assess the diagnostic performance of three commonly used serological tests in dogs. Canine sera (n = 989) were tested with the Rose Bengal rapid plate agglutination test (RBRPT), the complement fixation test (CFT) and a competitive ELISA (C-ELISA). Diagnostic test performance was evaluated using a three test, two population Bayesian latent class analysis accounting for conditional dependence between the three tests. Positive and negative predictive values (PPV, NPV) were calculated for a range of expected prevalence estimates for the individual tests and test combinations interpreted in series and parallel. The RBRPT showed the highest individual Se of 0.902 (95 % posterior credible interval [PCI] 0.759-0.978) and the CFT the highest individual diagnostic specificity (Sp) of 0.914 (95 % PCI 0.886-0.946). The C-ELISA had marginally the best overall diagnostic performance (Youden's index = 0.807). The CFT and the C-ELISA interpreted in parallel returned the highest combined Se and Sp (0.988 and 0.885, respectively). All tests returned NPVs of > 0.982 in 2-8 % prevalence settings. Series interpretation of the three-test combination as well as the two-test combinations of the RBRPT and the C-ELISA and the CFT and the C-ELISA produced a PPV of 0.502 when the estimated prevalence was 8 %. While all tests are suitable for the detection of B. suis antibodies in dogs, they should not be interpreted in isolation as their diagnostic value is dependent on the pre-test probability of the disease. As such they are useful tools for the diagnosis of B. suis in dogs when exposure, history and clinical presentation indicate a risk of brucellosis.

This study assessed worm control practices used by Australian Thoroughbred farm managers with an online questionnaire survey. The questionnaire comprised 52 questions (close-ended: 44; open-ended: 8) about farm demography and general husbandry practices, farm managers' knowledge of gastrointestinal nematodes (GIN) and their importance, diagnosis, worm control strategies and anthelmintics, anthelmintic resistance (AR) and grazing management. Following the pilot survey, the link for the questionnaire survey was sent to all (n = 657) registered members of the Thoroughbred Breeders Australia on 12th April 2020. The response rate for the questionnaire was 18.5% (122 of 675). The farm managers reported a good understanding of GIN and their importance in different age groups of horses as most respondents (70% of 122) perceived worm-related illness to be more important in young (i.e., foals, weanlings and yearlings) than adult (> 3 years old) horses. Although most respondents (93%, 113 of 122) used anthelmintics prophylactically to control GIN, only 15% (18 of 122) observed worm-related illness in their horses. Just under 40% of respondents were performing faecal egg counts, with less than 20% using the results of faecal egg counts to guide deworming decisions. The interval-based deworming strategy was the most common method (>= 55% of 122 respondents) to control GIN in all age groups of horses. Macrocyclic lactones were the first choice of anthelmintics for all age groups of horses. Although the majority of respondents (88%, 107 of 122) perceived resistance in GIN against commonly used anthelmintics as an important issue in managing worms in horses, only 29% assessed the efficacy of anthelmintics and 91% (111 of 122) were unaware of AR on their properties. Grazing management practices, such as manure removal, were more frequently performed on smaller paddocks (<0.20 ha: 58%) than on larger paddocks (>0.20 ha: 18%). Multiple correspondence analyses showed that the likelihood of suboptimal worm control practices on small farms (n = <= 50 horses) was greater than that of medium (n = 51-100) and large (n = >100) farms. This study provides insights into the demography of Thoroughbred farms in Australia, husbandry practices used by stud managers and their knowledge about worms, control options and AR concerns, thereby paving the way for taking any initiatives to address the problem of AR in GIN of Australian Thoroughbred horses.

Introduction:Feline respiratory tract infection poses a serious challenge in animal shelters. Potential risk factors include pathogens introduced through animals entering the shelter. We aimed to determine the proportion of animals shedding feline upper respiratory tract (URT) pathogens at the time of entry and to assess how this contributed to the burden of clinical disease and final outcomes. Methods:Oropharyngeal and conjunctival swabs were collected from incoming cats over 11 months and tested using real-time PCR. The prevalence and distribution of pathogens were reported; causal associations with clinical disease and shelter outcomes were assessed using Bayesian generalised regression models. Results:On admission, 43% (n = 86) cats were shedding one or more pathogens (feline herpes virus, feline calici virus, Mycoplasma felis, Chlamydia felis and Bordetella bronchiseptica). Shedding was somewhat associated with subsequent clinical disease but not with risk of euthanasia. Animals placed into foster care were less likely (odds ratio [OR] 0.27, Bayesian credible interval [CI] 0.09‒0.78) and those enrolled into behavioural rehabilitation programmes were more likely to develop disease (OR 5, CI 2.4‒11). Kittens had a delayed time to onset of disease (daily hazard 0.39, CI 0.13‒1.2). Geriatric animals (OR 4.1, CI 1.8‒10) and those with comorbidities (OR 8.8, CI 3.5‒25) were most likely to be euthanased. Conclusions:While a substantial proportion of animals were shedding pathogens on entry, animal characteristics (age and behaviour) and shelter operations (foster care) were more important in impacting the shelter's burden of clinical feline URT disease.