Malaria is a vector-borne disease between human and mosquito. Malaria imposes a huge health burden on the world’s most vulnerable populations. Recently, we analyzed more than 10000 malaria case data reported in Greater Giyani in South Africa, and tried to understand spatial and temporal spread of malaria. Greater Giyani consists 95 villages and each village are connected by roads which characterize “network structure” of this area. Since mosquito mobility is very limited compared with human one, we assumed only humans move among villages, and this movement is an important factor on malaria transmission. Therefore, we considered malaria spread mainly depends on topological network distance, but not Euclidean distance among villages. Using GIS, we identified villages which show significantly higher or lower malaria cases (i.e., hot-spot or cold-spot) and are spatially clustered. These analysis might help a policy-making for malaria control. Based on these GIS analysis, we will make a spatially heterogeneous model like meta-population model for this malaria spread and investigate a mechanism behind those malaria hot- and cold-spots.