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Elife. 2015 Dec 29;4. pii: e09520. doi: 10.7554/eLife.09520.

Mapping residual transmission for malaria elimination.

Author information

1
Fogarty International Center, National Institutes of Health, Bethesda, United States.
2
Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, United States.
3
Clinton Health Access Initiative, Boston, United States.
4
National Malaria Control Program, Manzini, Swaziland.
5
Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, United States.
6
Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, San Francisco, United States.
7
Department of Pediatrics, University of California, San Francisco Benioff Children's Hospital, , United States.
8
Eck Institute for Global Health, University of Notre Dame, Notre Dame, United States.
9
Department of Biological Sciences, University of Notre Dame, Notre Dame, United States.
10
Department of Medicine, University of California, San Francisco, San Francisco, United States.
11
Department of Geography and Environment, University of Southampton, Southampton, United Kingdom.
12
Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.
13
Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States.
14
Sanaria Institute for Global Health and Tropical Medicine, Rockville, Maryland, United States.

Abstract

Eliminating malaria from a defined region involves draining the endemic parasite reservoir and minimizing local malaria transmission around imported malaria infections . In the last phases of malaria elimination, as universal interventions reap diminishing marginal returns, national resources must become increasingly devoted to identifying where residual transmission is occurring. The needs for accurate measures of progress and practical advice about how to allocate scarce resources require new analytical methods to quantify fine-grained heterogeneity in malaria risk. Using routine national surveillance data from Swaziland (a sub-Saharan country on the verge of elimination), we estimated individual reproductive numbers. Fine-grained maps of reproductive numbers and local malaria importation rates were combined to show 'malariogenic potential', a first for malaria elimination. As countries approach elimination, these individual-based measures of transmission risk provide meaningful metrics for planning programmatic responses and prioritizing areas where interventions will contribute most to malaria elimination.

KEYWORDS:

ecology; epidemiology; global health; human; malaria elimination; plasmodium falciparum; spatio-temporal transmission dynamics

PMID:
26714110
PMCID:
PMC4744184
DOI:
10.7554/eLife.09520
[Indexed for MEDLINE]
Free PMC Article

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