Persistent infections support maintenance of a coronavirus in a population of Australian bats (Myotis macropus).

Understanding viral transmission dynamics within populations of reservoir hosts can facilitate greater knowledge of the spillover of emerging infectious diseases. While bat-borne viruses are of concern to public health, investigations into their dynamics have been limited by a lack of longitudinal data from individual bats. Here, we examine capture-mark-recapture (CMR) data from a species of Australian bat (Myotis macropus) infected with a putative novel Alphacoronavirus within a Bayesian framework. Then, we developed epidemic models to estimate the effect of persistently infectious individuals (which shed viruses for extensive periods) on the probability of viral maintenance within the study population. We found that the CMR data analysis supported grouping of infectious bats into persistently and transiently infectious bats. Maintenance of coronavirus within the study population was more likely in an epidemic model that included both persistently and transiently infectious bats, compared with the epidemic model with non-grouping of bats. These findings, using rare CMR data from longitudinal samples of individual bats, increase our understanding of transmission dynamics of bat viral infectious diseases.

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.