As the world grapples with the devastating impact of COVID-19, many are wondering – when will the next pandemic hit, and what virus will cause it?
The SARS-CoV-2 virus was transmitted from animals to humans, but it’s not the only one to do so. Zoonotic viruses have always played a role in human history; the plague is a zoonotic disease transmitted by fleas from rodents to other animals. Rabies is another example, transmitted when an infected animal (most commonly a bat) bites or scratches another.
As humans increasingly encroach on animal habitats, zoonotic diseases are being given more frequent opportunities to cross the species barrier. Scientists recognise that it’s more important than ever to discover and understand them to prepare for future pandemics.
Many studies are now attempting to assess and even rank the risk of different zoonotic diseases to humans – but an essay recently published in the journal PLOS Biology warns that most of these risk assessments are based on limited or biased data.
Cosmos spoke with the essay’s lead author Michelle Wille, a researcher from the Marie Bashir Institute for Infectious Diseases and Biosecurity at the University of Sydney, about why it’s difficult to accurately determine the risks of zoonotic viruses.
How much do we currently know about zoonotic viruses and where are the gaps in our knowledge?
We know a lot about some zoonotic viruses, and very little about others. For example, influenza A virus regularly spills over from animals to humans, and as a result there have been a number of influenza pandemics in the last 100 years (the most recent being the H1N1 pandemic in 2009). There is a global framework to do research and surveillance of influenza viruses in people, birds and pigs and as a result we know a lot about this virus.
Arguably, for viruses that infect people rarely, or are found in limited geographic areas, far less is known. There are likely many viruses that are zoonotic that have not been identified. Given we have described less than 0.001% of viruses out there, we will likely continue to learn a lot about viruses, including zoonotic viruses.
What methods are used to discover new viruses? Have techniques improved in recent years?
Virus discovery is rapidly accelerating due to advances in sequencing tools and technology, specifically “metagenomics” and “metatranscriptomics”. These are sequencing-based methods that allow for the analysis of all genetic material in a sample. In terms of viruses, this means we are no longer limited to traditional identification methods (eg, virus culture – not all viruses are culturable using existing methods).
The pace of virus discovery since these tools have become more accessible is staggering. For example, a single paper described over 1400 viruses in invertebrates, the same authors subsequently described 214 novel viruses from fishes and amphibians, and more viruses are described every year.
Are virus discoveries outstripping our ability to classify or study them?
Following descriptions of novel viruses in the literature, they are evaluated and if they meet certain requirements are classified by the International Committee on Taxonomy of Viruses (ICTV). Because not all viruses meet these requirements and updates are released at discrete intervals, these data are inherently out-of-date and include a fraction of viruses described.
Why don’t all viruses meet the classification requirements?
This has to do with the amount of information we have about the virus; for consideration, a virus must have its full genome sequenced. For some viruses only one gene or domain may be sequenced.
Is the data from the ICTV the same data relied upon for pandemic risk assessment? Is this the only source of such data out there?
Yes, some studies undertaking zoonotic risk assessment utilise virus data from the ICTV only. Others may use datasets comprising both ICTV data and viruses identified in the literature.
So how exactly do scientists assess the risk of an emerging disease? Is this a recent field of research?
Arguably the first scientific article to attempt zoonotic risk assessment (rather than simply compiling lists of emerging viruses) was published in 2008. Since then, a number of articles have come out attempting to do zoonotic risk assessment. Beyond scientific articles, a number of tools have been developed for ranking the pandemic and/or zoonotic risk of viruses.
There are several different approaches being used in different studies or in different contexts. For example, a tool recently published ranks features of the host (epidemiology, ecology, and genetics), the environment, and the virus (genetics, epidemiology, virology, and ecology), with risk scores calculated using both data analysis and expert opinion.
Theoretically, the goal of risk assessment is to tell policy makers where to direct their limited resources – which animals to screen for which viruses.
How accurate are our current estimates of the risk?
Pandemic risk assessment is only as good as the data in hand, and due to severe limitations and biases in the underlying data we argue that current zoonotic risk assessments are likely inaccurate.
Not only is our sampling of the virosphere extremely limited, but it is also strongly biased towards viruses of socioeconomic impact: those that impact human health, those in species we eat or keep as companions, and those that cause noticeable and major mortality events in domestic animals and wildlife. Pangolins, for example, have never been included in zoonotic risk assessment as no viruses had been described in these animals prior to 2020.
How could we better assess this risk?
We argue that a different approach is needed, involving the extensive sampling of animals and humans at places where they interact – the animal-human interface.
Some examples of this interface are food production – for example, piggeries, poultry sheds, abattoirs, live animal markets, animal hunting and slaughter for bush meat. Another example may be people living in and around wildlife congregations such as bat roosts. Critically, we encourage the sampling of both animals and humans at this interface. I would refer readers to this article that elaborates on practical aspects of how this could be done.
This will enable novel viruses to be detected as soon as they appear in humans and allow us to quantify how often viruses cross this interface.
New viruses are constantly evolving, so we will have to continue sampling to detect new viruses and/or viruses that have changed (eg increased transmissibility, virulence etc).