Aggregation of parasites: description, causes and consequences

In a nutshell: aggregation describes the non-random (non-uniform) distribution of parasites within hosts; it is a nearly ubiquitous observation that in a parasite population, some individuals have lots of parasites while most have very few. Why does this happens (what ecological mechanisms drive the distribution of parasites among hosts)? Why does it matter?

Describing aggregation

Consider the following three distributions: Suppose we know that there are 100 parasites distributed in 10 hosts (intensity=10 parasites/host).

If there is no variation whatsoever (variance=zero, prevalence=100%), things look funny:

10 10 10 10 10 10 10 10 10 10

We can probably agree that this is "not random". It is called an even or underdispersed distribution.

We can also see when there is "too much variation" (variance=1000, variance/mean=100, prevalence=10%):

100 0 0 0 0 0 0 0 0 0

This is aggregated, or patchy, or overdispersed.

We can imagine intermediate cases:

50 50 0 0 0 0 0 0 0 0

How do we decide whether a parasite distribution is more even or less even than "random"?

The null hypothesis of randomness is that parasites exist in hosts independently (i.e. not in clumps, nor avoiding each other) and randomly (no preference for one host over another). Then we will end up with a Poisson distribution, which looks like this:
[pictures]
You can test whether a distribution of parasites is Poisson-distributed or not by measuring the variance-to-mean ratio (V/M), which is approximately 1 if the distribution is Poisson, > 1 if the distribution is overdispersed, and < 1 if the distribution is even.

The negative binomial distribution ...

Remember the importance of counting zeros! Also, note that sample size biases estimates of aggregation downwards.

Data

Shaw and Dobson:

parasite burden is log-normally distributed (does it make sense to count numbers? Perhaps in some contexts biomass, or biomass relative to host body size, would be a better measurement of parasite burden? Distinction between different ways of thinking about populations (physiology/ecology, individuals/amounts)
apparent restriction in mean burden: 90% of mean abundances between 0.1 and 100. (What might generate these limits?)
Variance/mean relationship. log var = 1.098 + 1.551 log mean (or, var=3*mean^1.551) [what does this mean in terms of distributions and processes?]. High correlation (87% of variation explained); suggestion of evolutionary/ecological processes acting? "Too aggregated" vs. "too even"? Connection to virulence (high virulence=low burdens, evenness); intermediate virulence hypothesis?
Prevalence vs mean parasite burden

[Taylor's Power Law fig.] The rest of Shaw & Dobson mostly talks about variations in mean burden by ecological type/family/etc. (not classical phylogenetic analysis, but at least takes phylogenetic associations into account at some level). I'm not going to talk about this much, but you should read this section. Some of the results are:

low burdens: 2-host systems (endoparasitic cestodes, predator-prey mediated transmission)
high burdens: 1-host systems, nematodes with passive consumption or active adult transmission stages

The analysis is interesting/suggestive, but suffers from several problems (as usual: it's easy to nitpick).

the standard problem of observational data sets: e.g., are 2-host systems special, or is it just that all of the predator-prey transmission examples included in the data set are have only 2 hosts?
how do we disentangle evolutionarily correlated suites of characters? Which came first, the chickens or the eggs (e.g. endoparasitism, predator-prey transmission, multiple hosts)? Which characters "really" drive the observed pattern, or is this a silly question?
Model selection: bootstrap confidence limits on the "binary trees" shown in the data set? How sensitive are the results to small chance events?
Relationships with parasite size/host size/relative size? (Data aren't good enough ... but ...)

S&D do offer some explanations for the variation around the mean-variance line (i.e., ecological/evolutionary correlates of aggregation), but these are mostly group-based and don't offer real ecological correlations. It's hard to say why. More work would, as usual, be necessary to make firm conclusions about why burdens are higher/lower in these groups. (Tree-based analysis of variance/mean etc.? Probably not enough information left in the residuals around the variance-mean line.)

higher aggregation in some trophically and passively transmitted nematodes of inverts
lower aggregation in dipteran parasites of cattle and reindeer (mobile adults spread around disease)
in tapeworms and in trophically transmitted parasites with invert intermediate hosts, aggregation decreases with average burden ("ceiling" on parasite burden?)

Causes

If we don't have quite enough information to mine aggregate data sets for hypotheses about causes of aggregation, can we just think about possible reasons/investigate particular cases instead? There are some very basic mechanisms that can generate or suppress aggregation.

Direct reproduction within individuals: the wormy get wormier ... increases aggregation. There are other mechanisms amplifying infection: parasite pheromones (ectoparasitic arthropods) [cf bark beetles: parasitoids of pine trees?]; changes in behavior; breakdown in immunity because of nutrition/pathology; etc..
Heterogeneity in exposure: e.g. clumped dispersal (e.g. picking up a whole batch of eggs/larvae at the same time), other kinds of variation in exposure in time and space (because of parasite prevalence, environmental conditions) ... increases aggregation. (Keymer and Anderson 1979 experimental work on spatial variability, other work on temporal variability.) This is one of the basic ideas behind the generation of the negative binomial distributions; it's also why "inappropriate" lumping (the definition of which depends on your question) leads to higher estimates of aggregation.
Heterogeneity between individuals (phenotypic or genotypic), in resistance/tolerance etc. (or perhaps in behavior, which would translate to heterogeneity in exposure). Evidence:

Heterogeneity in exposure or resistance can occur at different levels:

inbred or clonal organisms (mice?) in the lab: variation due to "luck" or exposure. (How would we expect this "aggregation" to show up
genetic heterogeneity: the same organisms in a controlled environment, but allow natural variation (how much is there?? there is some evidence, but much of it is from (i) hybrid zones or (ii) agricultural populations, neither of which might tell us all that much about wild populations (although there are differences between strains in susceptibility to infection). This is a tough question: once again, the question of maintenance of genetic variability for apparently favorable traits comes up. Could be RQ, other kinds of nonequilibrium dynamics (e.g. recently introduced diseases), drift, mutation-selection balance, ?). In one simple case (a cestode, Hymenolepis citelli in rodents) resistance follows simple Mendelian genetics (only homozygous recessives get the parasite [cf "genetic diseases", where lethal recessives are maintained in populations]).
environmental variability between populations

We can go beyond this and think about other levels: between-individual, between-family, between-subpopulation, etc. etc.. They can also interact. (S&D do point out that unlike in other ecological studies, we at least have a natural "population" to measure, which prevents some kinds of inappropriate grouping.)

Density-dependent host mortality, or density-dependent increases in parasite mortality or decreases in fecundity and growth (indirectly affecting fecundity) decrease aggregation (think back to Lloyd's index). An extreme example of this is concomitant immunity, where the first parasite into a host actually primes the host's immune system to reject future parasitic attacks (e.g. human filariasis).