25-29 May 2015 lisbon congress center, portugal
Bio & Abstract

Rofaida Elzubair
KM and GIS unit Coordinator
Epidemiological Laboratory

After Rofaida finished her BSc.computer science 2006 she started her Master in IT Management to link between IT & management after one and half working experience in programing and GIS, finished MSc 2009 then she is
working as Health Informatics Specialist in the EpiLab, public health research centre,also a collaborating lecturer in the UofK and UMST
she is a good volunteer enjoying voluntary work and has been engaged in different activities and community services programs

Geographical Impact Of Community Engagement In TB Management – Sudan Case Study.

The application of GIS within health is categorized into two distinctive areas of health; the first category is Epidemiology and the second is Health care, which it generally describes issues around accessibility to health services. GIS in health care is concerned about placement and accessibility of/to services, it used to estimate travel times to clinics, quantifying physical accessibility and providing comparisons for varying urban landscapes. The spatial characteristics such as topography or the geographical dispersion of population are a major determinant of whether an area does or does not receive services. Triage-Plus is a pragmatic control trial took place in 2010 up to 2012, to compare two localities in Khartoum state, capital of Sudan to study the impact of the intervention of using informal healthcare providers (IPs) in TB management and their influence in increasing TB case detection. GIS is being used within Triage-Plus planning designing, and implementation phases, taking the advantages of its ability to visualize information on a map which allows quick analysis of the information. The primary objectives of GIS usages were: a) To create patients' density map, that determines areas of most vulnerable groups; b)To assess whether the Informal health Providers (IPs) could change the geographical factor of health seeking behaviors by determining patients-centers distribution. Methods: GIS software product produced by ESRI called ArcGIS v9.3 was being used for drawing maps, adding layers of information as well as creating geo-datasets. Mapping of popular extension areas that were not available in official maps as they are slums unplanned settlement, required using of google earth images then Autocad v2008 software to digitize raster data (images) into vector data, so as to be integrated with ArcGIS Khartoum base-map. GPS device was also used to acquire health facilities and IPs' coordinates with a percentage of error +-3 meters. SPSS version 20, Epidata were used to work on raw data collected from the routine standard TB patients registry. Study area was divided into number of sectors, to monitor the distribution of services, TB cases and population, with compare to the the distribution of community workers (the IPs), also the identification of centers' catchment area took place using agreed methodology in order to visualize TB services coverage. Results: The GIS maps shows that the TB centers is not well distributed over the area, it neither based on population or patients density, in addition monitoring TB patients before and after the intervention shows, a significant decrease in distance that patients take to access TB centers (with P value =0.031), before the intervention patients tend to use centers that were located outside their residential area, the use of IPs help in changing their health seeking behavior by raising awareness. The distribution of patients with the association of IPs showed that there is no significant relation between them, which indicates that there is a wide networking took place over the areas which was expected form community prospective during the situation analysis activities of the project. Conclusions: The use of community members could improve accessibility to the formal health-care facilities, and reduce burdens that causes defaulting in TB cases, in addition policy makers needs to consider population density and patients distribution in the TB centers placement, as TB management required a Direct Observation Treatments DOTs.

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