Spatial structure in a host population results in heterogeneity in transmission dynamics. We used a Bayesian framework to evaluate competing metapopulation models of rabies transmission among domestic dog populations in villages in Tanzania. A proximate indicator of disease, medical records of animal-bite injuries, is used to infer the occurrence (presence/absence) of suspected rabid dog cases in one month intervals. State-space models were used to explore the implications of different levels of reporting probability on model parameter estimates. We find evidence for a relatively high rate of infection of these populations from neighbouring districts or from other species distributed throughout the study area, rather than from adjacent wildlife protected areas, suggesting wildlife is unlikely to be implicated in the long-term persistence of rabies. Stochastic simulation of our highest ranked models in vaccinated and hypothetical unvaccinated populations indicated that pulsed vaccination campaigns occurring from 2002 to 2007 reduced rabies occurrence by 57.3 per cent in vaccinated villages in the 1 year following each pulse, and that a similar regional campaign would deliver an 80.9 per cent reduction in occurrence. This work demonstrates how a relatively coarse, proximate sentinel of rabies infection is useful for making inferences about spatial disease dynamics and the efficacy of control measures.