TY - JOUR
T1 - Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission
T2 - A cross-sectional and longitudinal community survey
AU - Moss, William J.
AU - Hamapumbu, Harry
AU - Kobayashi, Tamaki
AU - Shields, Timothy
AU - Kamanga, Aniset
AU - Clennon, Julie
AU - Mharakurwa, Sungano
AU - Thuma, Philip E.
AU - Glass, Gregory
N1 - Funding Information:
WJM conceived of the study, participated in its design and coordination, and drafted the manuscript. HH participated in the design and coordination of field aspects of the study. TK participated in the coordination of the study and preparation of the manuscript. AK participated in the coordination of the study. JC carried out statistical analyses and participated in the preparation of the manuscript. SM participated in the design and coordination of the study. PET participated in the design and coordination of the study. GG conceived of the study, participated in its design, coordination and statistical analysis and drafted the manuscript. All authors read and approved the final manuscript. Funding This work was supported by the Johns Hopkins Malaria Research Institute and the Bloomberg Family Foundation.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
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U2 - 10.1186/1475-2875-10-163
DO - 10.1186/1475-2875-10-163
M3 - Review article
C2 - 21663661
AN - SCOPUS:79958110757
SN - 1475-2875
VL - 10
JO - Malaria journal
JF - Malaria journal
M1 - 163
ER -