Abstract: Affected by global climate change, the losses caused by typhoon storm surge are increasing gradually. Building an accurate, efficient and reasonable loss assessment model is highly demanded for marine disaster prevention and mitigation projects. Four sets of indexes were used to construct the index system of typhoon storm surge, and the input factors were selected by principal component analysis. The sparrow search algorithm (SSA) was used to optimize the support vector machine model for loss classification and direct economic loss assessment of typhoon storm surge. Compared with other optimization algorithms, the SSA model showed better prediction accuracy. In addition, the four sets of indicators in the index system were evaluated individually, from which the order of effectiveness of them is: danger level > climate change > vulnerability > disaster prevention and mitigation capability. This study showed the rationality of the experiment and provided an effective assessment method for disaster prevention and mitigation.