I am interested in how within-host processes affect between-host disease transmission. This is summarised by the diagram below (adapted from Handel and Rohani 2015 Phil. Trans.). I’m working a bit on both (i) and (ii) in figure 1, and how they interact.
How within-host processes affect host infectiousness
Recently, I’ve used the guppy-gyrodactylid host-parasite system to show that within host processes affect host infectiousness. One main result of this work is that if a host has transmitted successfully before, it transmits more worms on its second attempt (figure 2a). Intriguingly, worms that transmit from an experienced ‘donor’ seem to be less fit than those from inexperienced donors (figure 2b). I’m not sure why this happens, but I’ll hopefully work it out at some point. It could mean that while ‘superspreaders’ (the infected hosts in a population that transmit infection to disproportionately large numbers of uninfected hosts) do infect more hosts, these infections aren’t as severe as those from ‘normal spreaders’.
Fig 2. Panel (a) shows that donor guppies who had previously successfully transmitted an infection transmitted more parasites on their second attempt than donors on their first attempt. Panel (b) shows that the worm populations transmitted by these experienced donors had an equal probability of growing or shrinking (dashed line shows growth rate of 0), but those from inexperienced donors exclusively grew.
Another cool result from this experiment is that more resistant donors transmit more parasites – it’s as though the parasites are jumping ship from hosts that can effectively fight the infection (figure 3).
Fig 3. In these plots, ‘donor infection load’ is the number of parasites on the donor at the point of transmission, ‘donor infection integral’ is a measure of resistance, and is the area under the curve of infection load over time. This means that donors that have large infection loads for long periods (i.e. they are unable to limit parasite growth) have the largest infection integral. Panel (a) shows the raw data – donors that transmitted the largest number of worms are those that had heavy infection loads, but low infection integral (so they were able to effectively fight the infection). Panel (b) shows the data laid over the predictions from a model. This clearly shows that the hosts with the largest infection integrals (i.e. those that can’t limit the infection at all) don’t really transmit many worms, regardless of how heavy their infection load is.