Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/30868
Title: Spatial Distribution of HIV Prevalence among Young People in Mozambique
Authors: MULEIA, Rachid 
Boothe, Makini
LOQUIHA, Osvaldo 
AERTS, Marc 
FAES, Christel 
Issue Date: 2020
Publisher: MDPI
Source: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 17 (3) (Art N° 885)
Abstract: Mozambique has a high burden of HIV and is currently ranked sixth worldwide for adult prevalence. In Mozambique, HIV prevalence is not uniformly distributed geographically and throughout the population. We investigated the spatial distribution of HIV infection among adolescents and young people in Mozambique using the 2009 AIDS Indicator Survey (AIS). Generalized geoadditive modeling, combining kriging and additive modeling, was used to study the geographical variability of HIV risk among young people. The nonlinear spatial effect was assessed through radial basis splines. The estimation process was done using two-stage iterative penalized quasi-likelihood within the framework of a mixed-effects model. Our estimation procedure is an extension of the approach by Vandendijck et al., estimating the range (spatial decay) parameter in a binary context. The results revealed the presence of spatial patterns of HIV infection. After controlling for important covariates, the results showed a greater burden of HIV/AIDS in the central and northern regions of the country. Several socio-demographic, biological, and behavioral factors were found to be significantly associated with HIV infection among young people. The findings are important, as they can help health officials and policy makers to design targeted interventions for responding to the HIV epidemic.
Notes: Muleia, R (reprint author), Hasselt Univ, Interuniv Inst Stat & Stat Bioinformat, B-3590 Diepenbeek, Belgium.; Muleia, R (reprint author), Univ Eduardo Mondlane, Dept Math & Informat, Fac Sci, Maputo 254, Mozambique.
rmuleia@gmail.com; makini.boothe@gmail.com; osvaldo.loquiha@gmail.com;
marc.aerts@uhasselt.be; christel.faes@uhasselt.be
Other: Muleia, R (reprint author), Hasselt Univ, Interuniv Inst Stat & Stat Bioinformat, B-3590 Diepenbeek, Belgium; Univ Eduardo Mondlane, Dept Math & Informat, Fac Sci, Maputo 254, Mozambique. rmuleia@gmail.com; makini.boothe@gmail.com; osvaldo.loquiha@gmail.com; marc.aerts@uhasselt.be; christel.faes@uhasselt.be
Keywords: HIV/AIDS;generalized geoadditive model;kriging mixed model;Mozambique
Document URI: http://hdl.handle.net/1942/30868
ISSN: 1661-7827
e-ISSN: 1660-4601
DOI: 10.3390/ijerph17030885
ISI #: WOS:000517783300210
Rights: 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

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