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Epidemics in large complete networks is well established. In contrast, we consider epidemics in non-complete networks. We establish the fluid limit macroscopic dynamics of a multi-virus spread over a multipartite network as the number of nodes at each partite or island grows large. The virus spread follows a peer-to-peer random rule of infection in line with the Harris contact process (refer to [1]). The model conforms to an SIS (susceptible-infected-susceptible) type, where a node is either infected or it is healthy and prone to be infected. The local (at node level) random infection model induces the emergence of structured dynamics at the macroscale. Namely, we prove that, as the multipartite network grows large, the normalized Markov jump vector process