Address for correspondence:
Zoology Department
Cambridge University
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email: bryan@zoo.cam.ac.uk
This brief review takes as its starting point the symposium volume by Grenfell and Dobson (G&D) from the Newton Epidemics meeting in 1993. We survey theoretical (and relevant empirical) progress since then in understanding the ecology and evolution of infectious diseases. In particular, this leads us to suggest open problems and fruitful directions for future theoretical work. Any survey of recent (or even ancient!) literature runs the risk of descending into autobiography. We have tried to avoid this here (but see footnote), and hope that any lack of balance will be corrected at the meeting. The review follows G&D by focusing mainly on the ecological and evolutionary dynamics of infectious diseases in natural animal and plant populations. However, we also use human diseases examples, where these illuminate ecological and evolutionary issues. The following sections update a series of issues raised in the meeting, and summarized in the Introduction to G&D. There is inevitably some overlap with other meeting reviews, especially Ben Bolker's survey of spatial dynamics and the immuno-epidemiological survey. We consider both these areas, though in the context of biological issues, rather than as separate methodological sections.
Persistence of infection continues to be a major issue, especially for morbilliviruses and other SIR and SI infections with short incubation and infectious periods. Measles, as ever, provides a good empirical and theoretical test bed for these ideas, especially via the critical community size (CCS). In 1993, we were unable to capture Bartlett's figure of around 250,000 for the CCS, however, there has recently been progress in this area on a couple of fronts. First, stochastic population models for measles have tended to assume exponentially-distributed incubation and infectious periods. Incorporating a shorter, more biologically realistic (Bailey 1975), tail for these distributions, gives a much lower, more realistic CCS (Keeling & Grenfell 1997). Second, the dynamics and persistence of infection are also likely to depend on the hierarchical mixing structure of the host population. Recent work has also addressed this, using both spatial patch models (Ferguson et al. 1997) and dyad approximations to individual-based models (Keeling et al. In press). A very different and interesting perspective on persistence and dynamics of infection has also recently been provided by analyses of power law behaviour of measles epidemics on islands (Rhodes & Anderson 1996).
A key area for future work is extending spatio-temporal models to describe the impact of vaccination, and especially, how the observed decorrelation of epidemics produced by vaccination (Bolker & Grenfell 1995; Bolker & Grenfell 1996) affects the efficacy of disease control.
Wildlife metapopulations and conservation: There are deep parallels between questions of disease persistence and the ecological concept of the metapopulation (Gilpin & Hanski 1991). The latter are often used as metaphors for the impact of spatial heterogeneity on stochastic persistence of endangered species. Recent theoretical work, considering wildlife diseases in a metapopulation sense has focused in two main areas. First (from the ecological direction), Hess (1996) uses stochastic simulations to show that increasing the pattern of connectedness of spatially subdivided habitats could (against conventional wisdom) work against the persistence of threatened populations, by facilitating the spread of deadly infections. Of course, epidemiologically, these changes in mixing could also affect the persistence of infection. This brings us to the second, continuing area of interest: empirical and theoretical studies of the persistence of rabies, canine distemper virus (CDV), etc. The most important current issue here is the impact of domestic animals - and in particular domestic dogs (Cleaveland & Dye 1995) as infection reservoirs. More generally, there is considerable scope for using stochastic approaches to generalize the CCS concept to the dynamics of wildlife metapopulations (Swinton et al. Submitted). However the real need is for more epidemiological data on disease persistence. Proposed studies comparing the effects of dog vaccination against viruses with a range of epidemiological properties, from highly epidemics infections (eg, CDV) to relatively persistent diseases with carrier states (such as canine adenovirus), show particular promise here (Laurenson, pers. Commn). Disease persistence is a particularly complex issue for infections - such as Lyme disease and louping ill - with a complex life cycle based on invertebrates such as ticks and a range of vertebrate hosts (Hudson et al. 1995).
Control of wildlife diseases is the other side of the persistence coin. Most recent studies here have used deterministic models to calculate thresholds for disease persistence in the face of vaccination or culling of hosts, or host fertility control (Barlow 1996; Coleman & Dye 1996; Roberts 1996; Roberts & Aubert 1995; Swinton et al. In press). As with the measles vaccination story, there is likely to be significant scope here for spatial stochastic models, which explore the dynamical effects of control policies.
A perennial epidemiological challenge, which is especially difficult for wildlife infections, is estimating transmission coefficients (and therefore ultimately R0). Recently, DeLeo and Dobson (1996) have proposed a new approach to estimating comparative transmission rates, based on host allometry. This strategy could potentially provide an particular for emergent infections (see below). The next step here seems to be the development of statistical methods for assessing the methodology against empirical data (Hone et al. 1992).
Parasite aggregation among hosts: The causes and consequences of macroparasite aggregation continues to be a lively research area. In terms of data analysis, recent studies have improved the methodology for analyzing aggregated parasite data (Rousset et al. 1996; Wilson et al. 1996) and underlined the ubiquity of aggregation, using comparative analyses (Shaw 1994). An especially interesting comparison of data and models is by Haukisalmi et al. (1996), who assess the sex ratio and mating probability of nematode parasites (Heligmosomum mixtum) in a fluctuating vole population.
Recent theoretical studies of parasite aggregation have focused on `moment closure' models for the development of aggregation with host age (Grenfell et al. 1996; Isham 1995; Quinnell et al. 1995) and on the ecological consequences of patchy parasite distributions (Dobson & Roberts 1994; Jaenike 1996). The ultimate aim is to produce models which capture both the causes and consequences of aggregation. The neatest solution (Adler & Kretzschmar 1992; Kretzschmar & Adler 1993) is a population level extension of the standard Crofton/Anderson and May models. However, there are still (at least) three knotty problems for interested probabilists. First, how do we `close the loop' of the infection process, which both generates parasite distributions in the host and is generated by them? Do we need a spatially-explicit model here, or can the process be approximated at the host population level? Second, parasite aggregation arises from a combination of the stochastic encounter rate with transmission stages and heterogeneities between hosts in encounter rate, immunity etc. Can we model these complexities economically, without a horrible proliferation of parameters and subscripts? Finally, empirical workers actually measure the prevalence of infection as well as the mean and variance. Can these variables be captured simultaneously, perhaps based on approximations using the phenomenological fit of the negative binomial (Isham 1995)? Can we sometimes ignore the dynamic effects of parasite aggregation, when the mean is very high (Smith & Guerrero 1993)?
Aggregation is also an important variable in other recent developments in parasite ecology. Parasite communities have been examined using both theoretical models (Roberts & Dobson 1995) and new comparative statistical approaches (Morand et al. 1995). These two complementary methodologies are providing insights that link this area to some of the models being developed for the community structure of insects on plants, fish on coral reefs, and tropical forests (Hubbell & Foster 1986; Mapstone & Fowler 1988). The ecological role of parasites in mediating host competition has generally been addressed for microparasites. This issue is now also being examined for macroparasites (Yan 1996), though explicitly considering the above distributional issues greatly complicates the picture. Recent theoretical work on seasonality in host macroparasite interactions (White & Grenfell In press; White et al. 1996) indicates that a limited host reproductive season can potentially lessen the dynamic impact of parasites. There is significant scope for more work on macroparasite seasonality, though the real need is to bring together theory (Heesterbeek & Roberts 1995) with detailed empirical studies (Tinsley 1995). In parallel with the search for chaos in microparasites, Kaitala et al. (1996) have used discrete deterministic macroparasite models to generate complex dynamics. Overall, however, host-macroparasite interactions seem less prone to large amplitude fluctuations than do microparasites.
Parasites provide a wonderful model and potential explanatory mechanism for many evolutionary problems. Similarly, many areas of parasite ecology could benefit from an evolutionary perspective (Anderson 1995), especially as new molecular techniques reveal the population genetic complexities boiling away beneath previously seemingly placid epidemiological surfaces. The major conclusion from the Newton meeting was that evolutionary models should incorporate epidemiology and vice versa. There have been more signs of the former than the latter; we present some recent highlights below.
Optimal sex ratios in malaria: Read et al. (1995) combine simple epidemiological models and optimality theory to show that malaria sex ratio may reflect population structure. They use a comparative analysis of 12 populations with avian malaria to show a positive relationship between gametocyte sex ratio and prevalence. Apart for its epidemiological significance, this is arguably the first time an ESS/optimality model has made quantitatively successful predictions, in the context of infectious diseases. However, the theory does not work in some other systems (Shutler et al. 1995), indicating that more theoretical and comparative work is needed in this area.
Strain structure - in malaria and other systems (Gupta et al. 1996; Saul 1996) - is a particularly ripe area for combining empirical data with epidemiological and population genetic theory. Gupta et al. (1996) show how recombining strains could be maintained by selection on dominant polymorphic determinants, thought it is important now to establish how adding spatial mixing structure complicates this picture. The need for spatially-explicit theory is also apparent in the main applied issue in this area - the question whether recombination (which in malaria is associated with transmission) enhances or slows the rate of multi-locus resistance (Mackinnon 1997). Epidemiological variations in the extent of recombination are likely to be an important issue here (Paul et al. 1995).
This leads us naturally to the question of parasites and the maintenance of sex, where there have been significant recent developments. Asexual organism possess a two-fold reproductive advantage compared to a sexually reproducing organism, and yet sexual creatures abound. The idea that sexual reproduction provides a means for organisms to escape parasitism due to the greater genetic heterogeneity of the population (the Red Queen Hypothesis), has become one of the central hypotheses to explain this (Hamilton 1980; Maynard Smith 1978). Recent work has shown how temporal cycles in host and parasite phenotypes could give an advantage to sexual creatures (Ladle et al. 1993) and experimental data are being accumulated which also support the Red Queen Hypothesis (Schrag et al. 1994; Vrijenhoek 1993). A variation on the usual theme is provided by Gemmill et al. (1997) who provide empirical evidence that parasite sex may be a means of escaping (somatic) evolution of the host immune system.
A novel development which brings ideas from stochastic spatial systems (Keeling & Rand 1995) has the benefit of replacing temporal cycles (which are not in general observed) with a more generic explanation based on spatial heterogeneity. In a sexual population, parasites which disperse locally see a heterogeneous environment; so that there are large fluctuations in their evolutionary target. However those parasites in an asexual population are surrounded by host clones so their evolutionary target is clear. In this way, sexual hosts succeed, as they are able to escape parasitism by all but the most rapidly evolving parasites. When a host's level of sexuality is also subject to slow mutation, this model predicts evolution to high levels of sexual reproduction; this goes against the usual, but inaccurate, result that `a little sex goes a long way' (Green & Noakes 1995). Virulence and transmissibility. The thrust of recent theory is that the evolution of virulence is intimately bound up with within-host population interactions of parasite strains and that the evolutionary process is intimately bound up with population dynamics (Frank 1994; Frank 1996; May & Nowak 1994; Nowak & May 1994; Van Baalen & Sabelis 1995). Many of the issues and complexities are clearly set out by Van Baalen and Sabelis (1995). In particular, they show - for double clone infections - that the (ESS) evolutionary outcome depends on population iteractions within the host as well as at the host population level. The importance of the population dynamic scale to virulence outcomes is also increasingly underlined by empirical studies (Herre 1995).
Spatial issues at the parasite population level are again likely to be important here in many situations. For example, Lively and Jokela (1996) use experiments on trematode-snail interactions to show that host-parasite coevolution and cycling can happen on very local scales. The general area of spatial variations in host-parasite compatibility has been modelled by Morand et al. (1996). They find, using data analysis of schistosome-snail interactions and deterministic models, that host-parasite compatibility may not simply decrease with geographical distance. This approach is particularly stimulating in its fusion of population genetic and epidemiological ideas; it will be interesting to see what spatial stochastic models incorporating definitive host dynamics, can add to the story.
The most dramatic manifestation of evolutionary novelty is provided by new emergent diseases, as well as the invasion of existing parasites into previously unexposed `virgin' host populations (Grenfell & Gulland 1996). TSEs are the most important and intriguing recent case of an emergent disease (Anderson et al. 1996), whilst morbillivirus infections in lions, canids and horses (Murray et al. 1995; Roelke-Parker et al. 1996) appear to be a recent dramatic example of diseases crossing the species barrier. By definition, the analysis of novel infections tends to be post hoc, though there may be scope here for theoretical work on expected dynamic and evolutionary transients as a function of host-parasite life history, host metapopulation structure, etc.
Evolutionary trees and epidemiological wood: There has recently been significant progress in using coalescence theory to put the interpretation of molecular evolutionary trees from pathogens onto a firm statistical footing (Harvey et al. 1994). In principle, pathogen sequence data along a chain of transmission could provide a vastly important tool for estimation of epidemiological parameters. By contrast, it is not yet clear whether evolutionary trees are a sharp enough instrument to tease out useful information at an epidemiological timescale. However, there is a vast, and increasing, volume of pathogen sequence data, so that this issue needs to be examined by epidemiological theory.
Finally, analyses of comparative data (Morand 1996; Read & Skorping 1995) indicate significant scope for modelling parasite life history strategies. A key issue in this area is how different strategies affect R0 and lessons from epidemiological theory can help here.
In summary, recent work indicates a range of exciting ecological and evolutionary challenges for epidemiological theory. However, these can only be addressed fully by a proper fusion of empirical and theoretical approaches and expertise. Overall, we think that significant recent progress has been made in this synthesis, especially in the study of plant diseases (Kleczkowski et al. 1996). However, a recent review of G&D (Ashford 1996) illustrates - with unintentional brilliance - the gulf that still remains between theory and practice in some circles.
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Smith, G. & Guerrero, J. 1993 Mathematical-Models For the Population Biology of Ostertagia- Ostertagi and the Significance of Aggregated Parasite Distributions. 46, 243-257.
Swinton, J., Harwood, J., Grenfell, B. T. & Gilligan, C. A. Submitted Persistence thresholds for phocine distemper virus infection in harbour seal (Phoca vitulina) metapopulations. .
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Footnote: Though Andy Dobson will be signing copies of volume 15 of his autobiography, "The Gods are nought mocked", at the meeting.
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Denis Mollison, 21st March 1997