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Abstract Sudan is the largest country in Africa characterized with different topographical features such as River Nile and its head streams and other tributaries, Nubian desert in the north, swamps in the south and hills which are extended a long the coast. This variations in topography lead to variations in climatic conditions e.g. The desert climate is prevail in the north, tropical and subtropical in the middle of Sudan while equatorial climates predominates in the south accompanied by a heavy rainfall, thunder clouds and swamps. This diversity results in creating different environments including those which may favor rearing of insects-transmitted diseases. This vast areas and the biodiversity in addition to the weakened in infrastructure such as public health system, vector control programmes, build roads, population movement (immigration), military conflicts and telecommunications for transmitting the basic services had led to unconventional handling and dealing with the most public health problems in a time manner which may some times exacerbate the problem. Recently, the revolution in space and information technologies (IT) and GIS has impacted upon the ordinary life style of man and his environment as well as on various disciplines of science. The scientific community had exploited these new technologies. The application of such technologies then moved from basic science into operation through developing vector and disease distribution, prediction and furthermore, to developing disease early warning systems. The current study was conducted in the Sudan by utilizing GIS and RS technologies to study malaria occurrence and its vector(s) at three spatial levels; state, locality and square. The ultimate targets were to identify factors- related malaria prevalence and its vector(s), describing, analyzing mosquitogenic habitats and identifying, if any, the most important malaria vector(s) and calculating its capacity in disease transmission. Due to availability of necessary and reliable information concerning this research in the northern states only, therefore, southern states were excluded. Climatic data were obtained from Meteorological Authority- weather department for the period 1998- 2007, MPR from the National Malaria Administration for the same period and the NDVI for the years 2003 and 2007 during the autumn season where malaria prevalence rate is at its peak and the vector is more abundance. Regarding square level, it was carried out at Khartoum State in three squares; it involves collection of climatic variables, MPR, soil type, availability of water supply and electricity, entomological indices and length of drains and canals. Environmental, biotic and a biotic variable in a malaria GIS data base were analyzed to discriminate between squares at high and low risk of malaria. Greater Darfur States were categorized as the most prevalence rates of malaria during the last decade also as a high risk area, the reason behind such catastrophic situation is the conflict occurred there which obstruct the implementation of the malaria control activities since 2002, while Khartoum State, Northern State and Red Sea area were categorized as the low malaria risk states, a situation could be attributed to environmental and special political considerations for these states. Khartoum State in particular differ from its neighbors states solely due to availability and ease accessibility of health facilities, urbanization parameters, stability, political support and the presence of sustainable control measures representing of what is known as Khartoum free malaria zone, while Northern State and Red Sea area, the unfavorable climatic conditions for malaria transmission were revealed as the factors behind the low prevalence rate of malaria. With regard to the rest of the states, the prevalence rates were moderately found, and the little pit variations could be attributed to the differences in climatic conditions as well as similarity in control activities. Regression analysis was carried out in order to identify the environmental variables behind the heterogeneity in malaria distribution. Rain fall, NDVI, average of minimum temperature and the relative humidity were identified as the pronounced factors behind such heterogeneity. At the square level, the vector density, man-biting rate, vectorial capacity, proximity to the river banks, presence of open drains and canals, type of soil and the NDVI were identified as the most important determinants for heterogeneity of malaria, hence, proper dealing with these variables such as preventing vector-human contacts by using window screens or impregnated mosquito nets and increasing the flow rate of water in drains and canals were considered as the most effective measures to mitigate the risk of malaria and should be supported by sustainable and organized malaria control measures |