Due to the recent and devastating Ebola outbreak in Western Africa, several efforts have been made to further the current understanding of the virus’s transmission and its prevention. Several first-hand narratives regarding Ebola transmission report on superspreading. Nevertheless, the dynamics of superspreading has not been identified in a systematic manner. As such, the purpose of the following paper was to rectify this issue. A Bayesian model inference was carried out in order to combine epidemiological data of community-based cases with spatial data. The model focused upon measuring and estimating the distribution of cases created per infected person.