In epidemiology, contact tracing is a process to control the spread of an infectious disease and identify individuals who were previously exposed to patients with the disease. After the emergence of AIDS, Social Network Analysis (SNA) was demonstrated to be a good supplementary tool for contact tracing. Traditionally, social networks for disease investigations are constructed only with personal contacts. However, for diseases which transmit not only through personal contacts, incorporating geographical contacts into SNA has been demonstrated to reveal potential contacts among patients. In this research, we use Taiwan SARS data to investigate the differences in connectivity between personal and geographical contacts in the construction of social networks for these diseases. According to our results, geographical contacts, which increase the average degree of nodes from 0 to 108.62 and decrease the number of components from 961 to 82, provide much higher connectivity than personal contacts. Therefore, including geographical contacts is important to understand the underlying context of the transmission of these diseases. We further explore the differences in network topology between one-mode networks with only patients and multi-mode networks with patients and geographical locations for disease investigation. We find that including geographical locations as nodes in a social network provides a good way to see the role that those locations play in the disease transmission and reveal potential bridges among those geographical locations and households.