Are All Hosts Created Equal? Partitioning Host Species Contributions to Parasite Persistence in Multihost Communities
Building on our previous paper studying the different mechanisms through which different host species can arise as “key hosts” for parasite transmission, this new paper with Andy Fenton, Owen Petchy and Amy Pedersen creates a quantitative framework for partitioning R0 among many host species. This is a really exciting advance because we’re able to assess how robust estimates are to uncertainty in rates of cross-species versus within-species transmission and everything is estimated from fairly standard parasitological data. Applying this framework to my undergraduate dataset on gut parasites in small mammals confirms the existence of key hosts even for outwardly multi-host parasites (cryptic specialization) and shows in a hypothetical way, how different control measures could be more or less effective when targeting based on species specific values of R0.
Data for the paper are available here: http://dx.doi.org/10.5061/dryad.972mv
Abstract: Many parasites circulate endemically within communities of multiple host species. To understand disease persistence within these communities, it is essential to know the contribution each host species makes to parasite transmission and maintenance. However, quantifying those contributions is challenging. We present a conceptual framework for classifying multihost sharing, based on key thresholds for parasite persistence. We then develop a generalized technique to quantify each species’ contribution to parasite persistence, allowing natural systems to be located within the framework. We illustrate this approach using data on gastrointestinal parasites circulating within rodent communities and show that, although many parasites infect several host species, parasite persistence is often driven by just one host species. In some cases, however, parasites require multiple host species for maintenance. Our approach provides a quantitative method for differentiating these cases using minimal reliance on system-specific parameters, enabling informed decisions about parasite management within poorly understood multihost communities.