Spillover of zoonotic parasites is the result of complex chains of ecological events, often involving multiple species. This is because many parasites rely on multiple hosts throughout their (often complex) life cycles. Traditionally, disease transmission cycles have been rough, non-quantitative diagrams providing a general overview of parasite transmission among various host species. However, these simplistic diagrams often lack the nuance inherent in the ecologies of parasites. Quantitative transmission cycle maps (QTCM) represent an alternative which borrows techniques from network ecology to more accurately model disease transmission cycles. These models allow for key links within transmission cycles to be identified and quantified so that targeted interventions can be undertaken, the results of which can then be accurately measured by comparing the past structure with the present structure of these models. Using tick-host data from Amami Ōshima (Japan), the concept of QTCMs is presented along with solutions to common pitfalls encountered when these models are being constructed.