Features that matter: Evolutionary signatures can predict viral transmission routes.

Routes of virus transmission between hosts are key to understanding viral epidemiology. Different routes have large effects on viral ecology, and likelihood and rate of transmission; for example, respiratory and vector-borne viruses together encompass the majority of rapid outbreaks and high-consequence animal and plant epidemics. However, determining the specific transmission route(s) can take months to years, delaying mitigation efforts.

Identifying life-history patterns along the fast-slow continuum of mammalian viral carriers.

Life-history traits have been identified as major indicators of mammals' susceptibility and exposure to viruses due to evolutionary constraints that link life-history speed with species' ecology and immunity. Nonetheless, it is unclear where along the fast-slow continuum of mammalian life-history lies the greatest diversity of host species. Consequently, life-history patterns that govern host-virus associations remain largely unknown.

One hundred years of zoonoses research in the Horn of Africa: A scoping review.

Background: One Health is particularly relevant to the Horn of Africa where many people's livelihoods are highly dependent on livestock and their shared environment. In this context, zoonoses may have a dramatic impact on both human and animal health, but also on country economies. This scoping review aimed to characterise and evaluate the nature of zoonotic disease research in the Horn region.

Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations.

Our knowledge of viral host ranges remains limited. Completing this picture by identifying unknown hosts of known viruses is an important research aim that can help identify and mitigate zoonotic and animal-disease risks, such as spill-over from animal reservoirs into human populations. To address this knowledge-gap we apply a divide-and-conquer approach which separates viral, mammalian and network features into three unique perspectives, each predicting associations independently to enhance predictive power.

Predicting mammalian hosts in which novel coronaviruses can be generated.

Novel pathogenic coronaviruses - such as SARS-CoV and probably SARS-CoV-2 - arise by homologous recombination between co-infecting viruses in a single cell. Identifying possible sources of novel coronaviruses therefore requires identifying hosts of multiple coronaviruses; however, most coronavirus-host interactions remain unknown. Here, by deploying a meta-ensemble of similarity learners from three complementary perspectives (viral, mammalian and network), we predict which mammals are hosts of multiple coronaviruses.

Distinct spread of DNA and RNA viruses among mammals amid prominent role of domestic species.

Aim: Emerging infectious diseases arising from pathogen spillover from mammals to humans constitute a substantial health threat. Tracing virus origin and predicting the most likely host species for future spillover events are major objectives in One Health disciplines.We assessed patterns of virus sharing among a large diversity of mammals, including humans and domestic species.

Integration of shared-pathogen networks and machine learning reveals the key aspects of zoonoses and predicts mammalian reservoirs.

Diseases that spread to humans from animals, zoonoses, pose major threats to human health. Identifying animal reservoirs of zoonoses and predicting future outbreaks are increasingly important to human health and well-being and economic stability, particularly where research and resources are limited. Here, we integrate complex networks and machine learning approaches to develop a new approach to identifying reservoirs.

Small animal disease surveillance: GI disease and salmonellosis.

Presentation for gastrointestinal (GI) disease comprised 2.2 per cent of cat, 3.2 per cent of dog and 2.

Co-occurrence of viruses and mosquitoes at the vectors' optimal climate range: An underestimated risk to temperate regions?

Mosquito-borne viruses have been estimated to cause over 100 million cases of human disease annually. Many methodologies have been developed to help identify areas most at risk from transmission of these viruses. However, generally, these methodologies focus predominantly on the effects of climate on either the vectors or the pathogens they spread, and do not consider the dynamic interaction between the optimal conditions for both vector and virus.

Small animal disease surveillance: pruritus, and coagulase-positive staphylococci.

Presentation for pruritus comprised 6.5 per cent, 3.6 per cent and 2.

Small animal disease surveillance: respiratory disease.

Presentation for respiratory disease comprised 1.7 per cent, 2.3 per cent and 2.

Using the H-index to assess disease priorities for salmon aquaculture.

Atlantic salmon's (Salmo salar) annual aquaculture production exceeds 2M tonnes globally, and for the UK forms the largest single food export. However, aquaculture production is negatively affected by a range of different diseases and parasites. Effort to control pathogens should be focused on those which are most "important" to aquaculture.

Small animal disease surveillance.

This is the first UK small animal disease surveillance report from SAVSNET. Future reports will expand to other syndromes and diseases. As data are collected for longer, the estimates of changes in disease burden will become more refined, allowing more targeted local and perhaps national interventions.

Database of host-pathogen and related species interactions, and their global distribution.

Interactions between species, particularly where one is likely to be a pathogen of the other, as well as the geographical distribution of species, have been systematically extracted from various web-based, free-access sources, and assembled with the accompanying evidence into a single database. The database attempts to answer questions such as what are all the pathogens of a host, and what are all the hosts of a pathogen, what are all the countries where a pathogen was found, and what are all the pathogens found in a country. Two datasets were extracted from the database, focussing on species interactions and species distribution, based on evidence published between 1950-2012.