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Published in: Malaria Journal 1/2011

Open Access 01-12-2011 | Research

Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey

Authors: William J Moss, Harry Hamapumbu, Tamaki Kobayashi, Timothy Shields, Aniset Kamanga, Julie Clennon, Sungano Mharakurwa, Philip E Thuma, Gregory Glass

Published in: Malaria Journal | Issue 1/2011

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Abstract

Background

The burden of malaria has decreased dramatically within the past several years in parts of sub-Saharan Africa. Further malaria control will require targeted control strategies based on evidence of risk. The objective of this study was to identify environmental risk factors for malaria transmission using remote sensing technologies to guide malaria control interventions in a region of declining burden of malaria.

Methods

Satellite images were used to construct a sampling frame for the random selection of households enrolled in prospective longitudinal and cross-sectional surveys of malaria parasitaemia in Southern Province, Zambia. A digital elevation model (DEM) was derived from the Shuttle Radar Topography Mission version 3 DEM and used for landscape characterization, including landforms, elevation, aspect, slope, topographic wetness, topographic position index and hydrological models of stream networks.

Results

A total of 768 individuals from 128 randomly selected households were enrolled over 21 months, from the end of the rainy season in April 2007 through December 2008. Of the 768 individuals tested, 117 (15.2%) were positive by malaria rapid diagnostic test (RDT). Individuals residing within 3.75 km of a third order stream were at increased risk of malaria. Households at elevations above the baseline elevation for the region were at decreasing risk of having RDT-positive residents. Households where new infections occurred were overlaid on a risk map of RDT positive households and incident infections were more likely to be located in high-risk areas derived from prevalence data. Based on the spatial risk map, targeting households in the top 80th percentile of malaria risk would require malaria control interventions directed to only 24% of the households.

Conclusions

Remote sensing technologies can be used to target malaria control interventions in a region of declining malaria transmission in southern Zambia, enabling a more efficient use of resources for malaria elimination.
Appendix
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Metadata
Title
Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey
Authors
William J Moss
Harry Hamapumbu
Tamaki Kobayashi
Timothy Shields
Aniset Kamanga
Julie Clennon
Sungano Mharakurwa
Philip E Thuma
Gregory Glass
Publication date
01-12-2011
Publisher
BioMed Central
Published in
Malaria Journal / Issue 1/2011
Electronic ISSN: 1475-2875
DOI
https://doi.org/10.1186/1475-2875-10-163

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