Significant features of the epidemiology of equine influenza in New South Wales, Australia, 2007

Horse populations are severely underestimated in a region at risk of Hendra virus spillover

OBJECTIVE

To identify the size and distribution of the horse population in the Northern Rivers Region of NSW, including changes from 2007 to 2021, to better understand populations at risk of Hendra virus transmission.

METHODS

Census data from the 2007 Equine Influenza (EI) outbreak were compared with data collected annually by New South Wales Local Land Services (LLS) (2011-2021), and with field observations via road line transects (2021).

RESULTS

The horse populations reported to LLS in 2011 (3000 horses; 0.77 horses/km2) was 145% larger than that reported during the EI outbreak in 2007 (1225 horses; 0.32 horses/km2). This was inconsistent with the 6% increase in horses recorded from 2011 to 2020 within the longitudinal LLS dataset. Linear modelling suggested the true horse population of this region in 2007 was at least double that reported at the time. Distance sampling in 2021 estimated the region's population at 10,185 horses (3.89 per km2; 95% CI = 4854-21,372). Field sampling and modelling identified higher horse densities in rural cropland, with the percentage of conservation land, modified grazing, and rural residential land identified as the best predictors of horse densities.

CONCLUSIONS

Data from the 2007 EI outbreak no longer correlates to the current horse population in size or distribution and was likely not a true representation at the time. Current LLS data also likely underestimates horse populations. Ongoing efforts to further quantify and map horse populations in Australia are important for estimating and managing the risk of equine zoonoses.

One health in our backyard: Design and evaluation of an experiential learning experience for veterinary medical students

Background

New educational approaches are needed to improve student understanding of the wider sociological and ecological determinants of health as well as professional responsibilities in related areas. Field trips allow students to observe interaction between plant, animal and human communities, making them an ideal tool for teaching One Health concepts.

Methods

Veterinary medical students participated in a field trip to a local parklands area, frequented by humans, dogs, horses, and wildlife. Students rotated through 5 learning activities (‘stations’) that focused on: (1) response to exotic animal disease incursion (equine influenza); (2) impact of cultures and belief systems on professional practice; (3) management of dangerous dogs; (4) land use change, biodiversity and emerging infectious disease; and (5) management of environmentally-acquired zoonoses (botulism). Intended learning outcomes were for students to: evaluate the various roles and responsibilities of veterinarians in society; compare the benefits and risks associated with human-animal and animal-animal interactions; and evaluate the contributions made by various professionals in safeguarding the health and welfare of animals, humans and the environment. Following the field trip, students participated in a debrief exercise and completed an online survey on their experiences.

Results

Feedback from students collected in 2016/2017 (n = 211) was overwhelmingly positive. The learning experience at each station was rated as 4 (‘Good’) or 5 (‘Very Good’) out of 5 by 82–96% of students. Responses to closed- and open-ended questions − as well as outputs generated in the debrief session − indicated that students achieved the learning outcomes. Overall, 94% of students agreed or strongly agreed that they had a better understanding of One Health because of the field trip.

Conclusions

Field trips to local parklands are effective in promoting learning about One Health and can be incorporated into the core curriculum to maximize student exposure at relatively low cost.

The influence of meteorology on the spread of influenza: survival analysis of an equine influenza (A/H3N8) outbreak

The influences of relative humidity and ambient temperature on the transmission of influenza A viruses have recently been established under controlled laboratory conditions. The interplay of meteorological factors during an actual influenza epidemic is less clear, and research into the contribution of wind to epidemic spread is scarce. By applying geostatistics and survival analysis to data from a large outbreak of equine influenza (A/H3N8), we quantified the association between hazard of infection and air temperature, relative humidity, rainfall, and wind velocity, whilst controlling for premises-level covariates. The pattern of disease spread in space and time was described using extraction mapping and instantaneous hazard curves. Meteorological conditions at each premises location were estimated by kriging daily meteorological data and analysed as time-lagged time-varying predictors using generalised Cox regression. Meteorological covariates time-lagged by three days were strongly associated with hazard of influenza infection, corresponding closely with the incubation period of equine influenza. Hazard of equine influenza infection was higher when relative humidity was <60% and lowest on days when daily maximum air temperature was 20–25°C. Wind speeds >30 km hour⁻¹ from the direction of nearby infected premises were associated with increased hazard of infection. Through combining detailed influenza outbreak and meteorological data, we provide empirical evidence for the underlying environmental mechanisms that influenced the local spread of an outbreak of influenza A. Our analysis supports, and extends, the findings of studies into influenza A transmission conducted under laboratory conditions. The relationships described are of direct importance for managing disease risk during influenza outbreaks in horses, and more generally, advance our understanding of the transmission of influenza A viruses under field conditions.

Quantitative analysis of the risk of spread of equine influenza associated with movements of vaccinated horses from infected areas during the Australian outbreak

Simulation models were developed to quantify the likelihood of equine influenza virus infection entering pre-movement isolation, persisting through pre- and post-movement isolation periods without being detected by scheduled laboratory testing, and escaping to infect susceptible horses at a destination. The mean probability of escape ranged from 1 in 1,200,000 to 1 in 600,000 depending on lot size. For 95% of iterations the probability of escape was less than 1 in 200,000, regardless of lot size. For a large group of 600 horses processed as multiple separate lots, the mean probability of escape ranged from 1 in 10,000 to 1 in 56,000 depending on lot size. As a result of this analysis, a modified protocol, with two tests during pre-movement isolation and an additional test during post-movement isolation at the Chief Veterinary Officer's discretion, was implemented.