Predicting virus emergence amid evolutionary noise

Abstract

The study of virus disease emergence, whether it can be predicted and how it might be prevented, has become a major research topic in biomedicine. Here we show that efforts to predict disease emergence commonly conflate fundamentally different evolutionary and epidemiological time scales, and are likely to fail because of the enormous number of unsampled viruses that could conceivably emerge in humans. Although we know much about the patterns and processes of virus evolution on evolutionary time scales as depicted in family-scale phylogenetic trees, these data have little predictive power to reveal the short-term microevolutionary processes that underpin cross-species transmission and emergence. Truly understanding disease emergence therefore requires a new mechanistic and integrated view of the factors that allow or prevent viruses spreading in novel hosts. We present such a view, suggesting that both ecological and genetic aspects of virus emergence can be placed within a simple population genetic framework, which in turn highlights the importance of host population size and density in determining whether emergence will be successful. Despite this framework, we conclude that a more practical solution to preventing and containing the successful emergence of new diseases entails ongoing virological surveillance at the human-animal interface and regions of ecological disturbance.

Keywords: emergence; evolution; phylogeny; spill-over; virosphere; virus.

Figure 1.

Illustration of the relative size of the potentially unknown virosphere. The estimates shown are based on the assumption that approximately 10 viruses might be capable of infecting each of the estimated 8.7 million eukaryotic species on earth [26]. Currently, the ICTV recognizes 4404 virus species in both eukaryotes and prokaryotes (although many others are awaiting classification), which means that 99.9949379% of the virosphere remains undiscovered or unclassified.

Figure 2.

Possible effects of host biodiversity on the probability of viral emergence. The red arrows at the bottom depict instances of increased emergence risk. Wildlife host species richness has been proposed as an important predictor of disease emergence. Likewise, host populations of low biodiversity might harbour fewer viruses and a decreased risk of emergence. Conversely, high host biodiversity has also been linked to a decrease in disease risk through the ‘dilution effect’.

Figure 3.

Phylogenetic analyses of a virus family, seemingly showing many instances of cross-species transmission over evolutionary time scales (i.e. virus macroevolution). Critically, however, the adaptive processes (i.e. mutation and selection) that lead to virus ‘spill-overs’ and possible emergence in a new host are more informative when considering a shorter, microevolutionary time scale.

Figure 4.

Exemplifying the human–animal interface as the fault-line of disease emergence. Following a cross-species transmission event, a virus might cause a dead end ‘spill-over’ or it might be genetically adapted to be transmissible between members of the new host species. Even for emergent viruses of high fitness the probability of emergence and the size of the outbreak relies on a large and dense host population, as well as a variety of other ecological factors that can be thought of as comprising the ‘effective susceptible population size’ (x-axis, right-hand panel).