Socio-demographic factors associated with HIV infection
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Date
2009-11Author
Mutanda, Albino L
Type
ThesisLanguage
enMetadata
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Background: From the "Kenya Modes of Transmission" (KMOT) study (Haile G. 2008), Kenya has a
mixed epidemic with (a) National prevalence ranging from 6.7% (KDHS2003) to 7.4% (KAIS 2007) 7.1%
translated to approximately 1.33 million Kenyans aged 15-64 living with HIV in 2007 while casual
heterosexual sex contributing two thirds new infections and (b) Great regional variations, ranging from
almost 1% (Northeast Province) to above 12% (Nyanza Province, and up to 30% in some fishing
communities of Districts adjacent to Lake Victoria area). The KMOT study recommended that more
research on the behaviour and mapping of most-at-risk individual(s), cultural issues requiring behaviour
change and uptake of HIV services be conducted to establish where, how and who gets the next new
HIV infection. Such research would require the use of geospatial multilevel and multidimensional survey
Methods: All 13,060 participants who consented to be counseled and tested for HIV drawn from a
population under continuous demographical surveillance were linked to their homesteads and geolocated
using a geographical information system (accuracy of <2 m). Individuals and/or families were
counseled and tested as per national counseling and testing guidelines. In addition to capturing
their behavioral, social and demographic variables, spatial coordinates of their homesteads
were recorded as well. Point patterns were used to show geospatial variations while spatial
auto-correlations were used to produce robust estimates of HIV prevalence that varied across continuous
geographical space and discreet demographic factors (sex, age, marital status, education and
occupation). Neighborhood spatial effects with a threshold of 0.135 degrees (15 km radius) were also
applied to identify clusters of prevalence (P < 0.05).
Results: The results reveal considerable geographical variation in local HIV prevalence (range = 0.001-2.16) within this relatively homogenous population and provide clear empirical evidence for the localized
clustering of HIV infections. Four discreet spatial clusters with filled contours ranging from 0.02-0.97 were identified by using ordinary least squares autocorrelation after testing for residual auto-correlation (P<0.05), within the study area.
Conclusions: The findings show the existence of several clustered HIV prevalence of varying intensity
contained within the study community. Despite the overall low prevalence of HIV in Kalimoni sublocation,
the results support the need for interventions that target socio-geographic spaces (clustered villages) at greatest risk to supplement measures aimed at the general population.
Sponsorhip
University of NairobiPublisher
Institute of Tropical and Infectious Diseases, College of Health Sciences, University of Nairobi