 The COVID-19 pandemic has been characterized by strong spatial and temporal heterogeneities in terms of both the number of cases and the rate at which they have spread. To better understand these dynamics, researchers have developed models that estimate the transmission of infection between different populations and communities. However, existing models do not take into account the fact that the transmission of infection can vary across different communities. This paper proposes a new approach that takes into account the transmission of infection across multiple communities and estimates the time varying reproduction numbers of each community. The proposed method was applied to data on the COVID-19 pandemic and revealed the spatial, temporal heterogeneity of the epidemic.