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Bovine viral diarrhoea virus (BVDV) is a disease of global importance, affecting the production and welfare of cattle enterprises through poor reproductive performance and calf mortality. In Australia, the prevention of BVDV introduction and spread is primarily achieved with on-farm biosecurity; however, the use of these practices can vary amongst producers. Economic utility is commonly identified as a contributor to the uptake of on-farm biosecurity, but other factors such as animal welfare, producer priorities and introduction risk also influence farmer behaviour. This study uses an individual-based, stochastic simulation model to examine the economic and non-economic value of 23 on-farm biosecurity combinations for the control of BVDV in Australian beef farms without (N0) and with (N1) a neighbouring population of persistently infected (PI) cattle. Combinations of quarantine of purchased bulls (Q), hygiene during herd health events (H), double-fencing adjacent boundaries with neighbouring farms (F) and vaccination against BVDV (V) were tested. This study is the first to simulate the use of strategic PI exposure (PI) as an alternative to V, a contentious practice performed by some Australian beef farmers. Introduction of BVDV into a naïve 300-breeder self-replacing beef herd was achieved through the purchase of PI bulls (N0 and N1 herds) and over-the-fence contact with neighbouring PI animals (N1 herds only). The predicted median cumulative loss due to BVDV over a 15-year period was AUD$172/breeder and AUD$453/breeder for an N0 and N1 herd, respectively. Early establishment of BVDV in the simulation period was found to be the primary factor contributing to economic loss. Consequently, the Q and QF combinations resulted in the highest predicted average annual cost-benefit for BVDV-free N0 and N1 herds. In the five years following establishment of BVDV, use of QP (N0 herds) and V (N1 herds) combinations were most cost-effective. Combinations that involved V and P

Bovine viral diarrhea virus (BVDV) is an economically important disease in Australian beef farming. The disease typically results in low-level production losses that can be difficult to detect for several years. Simulation modeling can be used to support the decision to control BVDV; however, current BVDV simulation models do not adequately reflect the extensive farming environment of Australian beef production. Therefore, the objective of this study was to develop a disease simulation model to explore the impact of BVDV on beef cattle production in south-east Australia. A dynamic, individual-based, stochastic, discrete-time simulation model was created to simulate within-herd transmission of BVDV in a seasonal, self-replacing beef herd. We used the model to simulate the effect of herd size and BVDV introduction time on disease transmission and assessed the short- and long-term impact of BVDV on production outputs that influence the economic performance of beef farms. We found that BVDV can become established in a herd after a single PI introduction in 60% of cases, most frequently associated with the breeding period. The initial impact of BVDV will be more severe in smaller herds, although self-elimination is more likely in small herds than in larger herds, in which there is a 23% chance that the virus can persist for >15 years following a single incursion in a herd with 800 breeders. The number and weight of steers sold was reduced in the presence of BVDV and the results demonstrated that repeat incursions exacerbate long-term production losses, even when annual losses appear marginal. This model reflects the short- and long-term production losses attributed to BVDV in beef herds in southeast Australia and provides a foundation from which the influence and economic utility of BVDV prevention in Australian beef herds can be assessed.

The COVID-19 pandemic, a singular disruptive event in recent human history, has required rapid, innovative, coordinated and collaborative approaches to manage and ameliorate its worst impacts. However, the threat remains, and learning from initial efforts may benefit the response management in the future. One Health approaches to managing health challenges through multi-stakeholder engagement are underscored by an enabling environment. Here we describe three case studies from state (New South Wales, Australia), national (Ireland), and international (sub-Saharan Africa) scales which illustrate different aspects of One Health in action in response to the COVID-19 pandemic. In Ireland, a One Health team was assembled to help parameterise complex mathematical and resource models. In New South Wales, state authorities engaged collaboratively with animal health veterinarians and epidemiologists to leverage disease outbreak knowledge, expertise and technical and support structures for application to the COVID-19 emergency. The African One Health University Network linked members from health institutions and universities from eight countries to provide a virtual platform knowledge exchange on COVID-19 to support the response. Themes common to successful experiences included a shared resource base, interdisciplinary engagement, communication network strategies, and looking global to address local need. The One Health approaches used, particularly shared responsibility and knowledge integration, are benefiting the management of this pandemic and future One Health global challenges.