It is important to identify the epidemic sources during epidemic outbreaks to optimize the control strategies. However, the identification process is difficult due to the dynamics and complexity of epidemic networks. In this paper, we propose an identification algorithm to more accurately localize the epidemic source based on social contact networks (SCNs) only with a limited number of observers. We give an approximate solution for the SCNs. The proposed algorithm is validated on both real and artificial SCNs. The obtained results demonstrate that the proposed algorithm achieves better performance than existing methods.
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