Chronic infections can shape epidemic exposure: Pathogen co-occurrence networks in the Serengeti lions

Nicholas M. Fountain-Jones; Craig Packer; Maude Jacquot; F. Guillaume Blanchet; Karen Terio; Meggan E. Craft

There are, however, limitations to this approach. The inability to distinguish mortality from competitive interactions is one of them, and careful interpretation of negative associations is necessary. Incorporating approaches such as structural equation models that explicitly include potential mechanisms that underly candidate pathogen interactions (Carver et al. 2015) could be a valuable additional step in future pathogen network studies. Another weakness is the inability to estimate the timing of these infections more precisely. For example, the negative association between RVF and H. felis could be due to differences in rainfall affecting vector abundance with higher rainfall years increase mosquito abundance thus increasing RVF prevalence (Fig. S2 ). In contrast, low rainfall years increase the risk of lions being exposed to ticks (Munson et al. 2008) thus potentially increasing H. felis prevalence. As rainfall was calibrated to the age of sampling rather than the age of infection (which could differ) the JSDM approach could not capture this variation. Furthermore, we cannot quantify the importance of these associations in shaping pathogen distribution across scales compared to processes such as host density. Also, the number of samples we had did differ across years (Table S1 ) with most coming between 1985 and 1994, and this have influenced some patterns, particularly between genotypes. Lastly, incorporating immune function and host resources in both the summary network and JSDM analyses are likely to provide mechanistic insight into pathogen network structure (Griffiths et al. 2014) . However, given the daunting complexity of pathogen infra-community dynamics, our two-step approach can assess broad network structure and identify useful candidate interactions between pathogens thereby reducing some of this complexity.