Assessing the stability of parasite communities through perturbation experiments

In the past twenty years, there has been a surge of interest in the role of disease on individual health and its effects on host populations. These studies and, indeed, the majority of disease control programmes of humans and domestic animals tend to consider individual infections in isolation. However, hosts are typically infected by many parasite species at any one time. For example, humans, particularly in the developing world, can be simultaneously co-infected with a variety of parasites: around 40.3 million people are currently infected with HIV/AIDS, over one third of the population worldwide has TB, and over one fourth has soil transmitted helminths. Importantly, these co-infecting parasites are unlikely to occur in isolation within each host, indeed there may be a vast network of interactions between them. These interactions may arise through direct competition between parasites within each host. However, they may also be indirect, possibly through competition for shared resources (bottom-up interactions) or via the host's immune system (top-down interactions). In this case, immune responses raised against one parasite may also affect other co-infecting parasite species. Alternatively, if the host is combating one parasite type it may not be able to mount an effective response against another. Therefore there may be a complex network of subtle, and difficult to detect interactions between parasite species that result in a diverse, interactive community within each individual host. Clearly, understanding how these communities are shaped is vital for the design of truly effective and sustainable disease control programs. If control approaches only consider one parasite species there may be unpredictable consequences for disease caused by other, co-infecting parasites. However, current approaches to measure parasite interactions are purely observational and, so far, have produced unclear information about their strength or existence. We propose to adopt a new, direct way of measuring interactions using classical community ecology perturbation experiments, by removing certain parasites from wild wood mice and measuring what happens to the remaining parasite species - if they increase after the target parasites have been removed then this suggests that the target species was previously suppressing their abundance. By repeating this process for all main parasite groups in the wood mice, we can build a more complete picture of how these parasite communities are shaped by the interactions between species. Putting all these interactions into a mathematical model will allow us to predict how such parasite communities will respond to more complex treatments, such as the removal of two species at the same time. If our model predictions prove accurate for more complex co-treatment strategies, then these within host network approaches may provide a vital tool for developing long-term disease control strategies in other host species, such as humans, domestic animals or wildlife threatened to extinction by infectious diseases. It is gradually being realised that parasite co-infections play an important role in the occurrence and management of many diseases of human concern. Given the increasing concerns about emerging infectious diseases around the globe, it has never been more pressing to develop a genuine understanding of the factors affecting parasite invasion, transmission, persistence, and control. This project will be a major step in that direction.