Abstract: To explore “Monmonier′s algorithm” and its application on spatial structures of natural focal disease. MethodsThe improved Monmonier′s algorithm model based on Monmonier′s maximum-distance algorithm and distance matrix between the corresponding data, which were connected using a Delaunay triangulation, was built. Structures and boundaries of Hemorrhagic fever with renal syndrome (HFRS) were identified. Results The improved Monmonier′s algorithm model well showed the edges associated with the highest rate of changes in the given distance measure, namely the areas where differences between locations of disease are largest. The bootstrap test was used to assess the robustness of computed boundaries and infer the spatial connection and arrangement of boundaries. Conclusion The improved Monmonier′s algorithm model is useful in detecting spatial heterogeneity of disease boundary.

Key words: Spatial heterogeneity of disease, Geographic boundary, Monmonier′s algorithm