Most parasite species infect multiple host species, and reciprocally, most hosts are infected by multiple parasites. This leads to complex webs of interactions that influence disease within the community, making it challenging to understand and predict disease spread within the community and epidemics. Here, we used network approaches to analyze a multi-year time series dataset that includes eight zooplankton host species (in the Daphnia and Ceriodaphnia genera) and seven microparasite species to examine patterns of cross-species transmission. These analyses suggest that parasite species varied in their ability to infect multiple host species and in which host species they most commonly infected. Three parasites (the bacteria Pasteuria ramosa and Spirobacillus cienkowskii and the oomycete Blastulidium paedophthorum) showed signatures of relatively high cross species transmission, while the others seemed more restricted. Even for the three common multihost parasites, our approach also revealed differences in patterns of potential cross species transmission. For P. ramosa, two host species, Daphnia dentifera and D. retrocurva, seem particularly likely to transmit across species; in contrast, for S. cienkowskii, no host species stands out as particularly important for cross species transmission. Additionally, these patterns matched those describing epidemic size, suggesting that infected host density may drive cross-species transmission. These results are based on observations of patterns of infection in natural communities, and therefore we cannot draw definitive conclusions about interspecific transmission in lakes. However, some of the patterns are supported by additional lines of evidence, and others point to interesting avenues for future research. Together, these findings provide additional evidence that network approaches can provide valuable insights into patterns of transmission in complex multihost-multiparasite communities in nature.