Remote Sensing and Geographical Information System to map environmental factors associated with Children Malnutrition Severity in Khartoum State, Sudan

Abstract

TPS 723: Low and middle income countries: sanitation infections and other health effects, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Severe Acute Malnutrition (SAM) is a major health problem in the World. The available data on nutritional status of children under 5 years old in Sudan reflects the worse and miserable situation, especially in the marginalized rural areas. Khartoum State; where this study was conducted is among the top five States with increasing number of severely malnourished children in Sudan. Remote Sensing and Geographical Information System (RS/GIS) are gradually becoming popularly applied in many researches including epidemiology, and have been indispensably available instruments environmental resource management and programming. The main objectives of this study were to investigate applying GIS technique to map the distribution of children with SAM age (6-59) months in Khartoum State in 2016 (Jan-Dec), and to detect the relationship between environmental deficiencies and SAM cases using RS data and GIS. This study sited in Khartoum State including 36 Administrative Units, 14 sited hospitals and 21 of Outpatient Therapeutic Programme (OTP). The health data used included records of 1150 children cases with complicated SAM and 5796 children with non-complicated SAM over the study period. Retrospective study, based on Hospitals and OTPs. Using RS/GIS integrated spatial and non-spatial factors. The study used different RS and GIS technologies Software. The result showed thematic maps which present the variation of distribution of SAM children in Khartoum State. Influence by several factors such as socioeconomic and environmental realities of Khartoum State. SAM cases are concentrated in AUs areas where poverty, worse drinking water resources and lack of sanitation such as Alnaser AU and Asalam AU. This research concluded that both RS and GIS technologies have the capability to link and update the information on disease (SAM) and monitoring of environmental changes through mapping of cases.