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Finding malaria hot-spots in northern Angola: the role of individual, household and environmental factors within a meso-endemic area

Magalhães, Ricardo J.; Langa, Antonio; Sousa-Figueiredo, José; Clements, Archie CA; Nery, Susana

Description

BACKGROUND Identifying and targeting hyper-endemic communities within meso-endemic areas constitutes an important challenge in malaria control in endemic countries such like Angola. Recent national and global predictive maps of malaria allow the identification and quantification of the population at risk of malaria infection in Angola, but their small-scale accuracy is surrounded by large uncertainties. To observe the need to develop higher resolution malaria endemicity maps a predictive risk...[Show more]

dc.contributor.authorMagalhães, Ricardo J.
dc.contributor.authorLanga, Antonio
dc.contributor.authorSousa-Figueiredo, José
dc.contributor.authorClements, Archie CA
dc.contributor.authorNery, Susana
dc.date.accessioned2016-01-06T04:28:19Z
dc.date.available2016-01-06T04:28:19Z
dc.identifier.issn1475-2875
dc.identifier.urihttp://hdl.handle.net/1885/95295
dc.description.abstractBACKGROUND Identifying and targeting hyper-endemic communities within meso-endemic areas constitutes an important challenge in malaria control in endemic countries such like Angola. Recent national and global predictive maps of malaria allow the identification and quantification of the population at risk of malaria infection in Angola, but their small-scale accuracy is surrounded by large uncertainties. To observe the need to develop higher resolution malaria endemicity maps a predictive risk map of malaria infection for the municipality of Dande (a malaria endemic area in Northern Angola) was developed and compared to existing national and global maps, the role of individual, household and environmental risk factors for malaria endemicity was quantified and the spatial variation in the number of children at-risk of malaria was estimated. METHODS Bayesian geostatistical models were developed to predict small-scale spatial variation using data collected during a parasitological survey conducted from May to August 2010. Maps of the posterior distributions of predicted prevalence were constructed in a geographical information system. RESULTS Malaria infection was significantly associated with maternal malaria awareness, households with canvas roofing, distance to health care centre and distance to rivers. The predictive map showed remarkable spatial heterogeneity in malaria risk across the Dande municipality in contrast to previous national and global spatial risk models; large high-risk areas of malaria infection (prevalence >50%) were found in the northern and most eastern areas of the municipality, in line with the observed prevalence. CONCLUSIONS There is remarkable spatial heterogeneity of malaria burden which previous national and global spatial modelling studies failed to identify suggesting that the identification of malaria hot-spots within seemingly mesoendemic areas may require the generation of high resolution malaria maps. Individual, household and hydrological factors play an important role in the small-scale geographical variation of malaria risk in northern Angola. The results presented in this study can be used by provincial malaria control programme managers to help target the delivery of malaria control resources to priority areas in the Dande municipality.
dc.description.sponsorshipThis work was funded by the promoters of the CISA Project (Portuguese Institute for Development Assistance, Calouste Gulbenkian Foundation, Bengo Provincial Government and the Ministry of Health of Angola). RJSM is supported by a UQ Postdoctoral Research Fellowship and ACAC is supported by a NHMRC Career Development Fellowship.
dc.publisherBioMed Central
dc.rights© 2012 Magalhães et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.sourceMalaria Journal
dc.subjectadolescent
dc.subjectadult
dc.subjectaged
dc.subjectaged, 80 and over
dc.subjectangola
dc.subjectchild
dc.subjectchild, preschool
dc.subjectcross-sectional studies
dc.subjectepidemiologic studies
dc.subjectfamily characteristics
dc.subjectfemale
dc.subjecthumans
dc.subjectinfant
dc.subjectmalaria
dc.subjectmale
dc.subjectmiddle aged
dc.subjectprevalence
dc.subjectrisk assessment
dc.subjectyoung adult
dc.subjectendemic diseases
dc.subjecttopography, medical
dc.titleFinding malaria hot-spots in northern Angola: the role of individual, household and environmental factors within a meso-endemic area
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume11
dc.date.issued2012-11-22
local.identifier.absfor060800
local.identifier.ariespublicationU3488905xPUB4096
local.publisher.urlhttp://www.biomedcentral.com/
local.type.statusPublished Version
local.contributor.affiliationMagalhaes, Ricardo Soares, The University of Queensland, Australia
local.contributor.affiliationLanga, Antonio J, Hospital Provincial do Bengo, Angola
local.contributor.affiliationSousa-Figueiredo, Jose Carlos, Liverpool School of Tropical Medicine, United Kingdom
local.contributor.affiliationClements, Archie, College of Medicine, Biology and Environment, CMBE Research School of Population Health, Natl Centre for Epidemiology & Population Health, The Australian National University
local.contributor.affiliationvas Nery, Susana, Hospital Provincial do Bengo, Angola
local.identifier.essn1475-2875
local.bibliographicCitation.issue1
local.bibliographicCitation.startpage385
local.bibliographicCitation.lastpage12
local.identifier.doi10.1186/1475-2875-11-385
dc.date.updated2016-06-14T08:44:41Z
local.identifier.scopusID2-s2.0-84870924448
CollectionsANU Research Publications

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