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A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots

Authors: Bejon, P.; Williams, T.N.; Nyundo, C.; Hay, S.I.; Benz, D.; Gething, P.W.; Otiende, M.; +9 Authors

A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots

Abstract

Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or ‘hotspots’ of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.

Countries
United States, United Kingdom, Netherlands, Netherlands
Keywords

Falciparum, Biomedical and clinical sciences, 550, Fever, QH301-705.5, Science, Clinical Sciences, 610, malaria control, Rare Diseases, falciparum, Risk Factors, Humans, Biology (General), Malaria, Falciparum, Child, Pediatric, Biomedical and Clinical Sciences, Q, R, Health sciences, Kenya, Malaria, Vector-Borne Diseases, Biological sciences, Infectious Diseases, Good Health and Well Being, Epidemiology and Global Health, Medical Microbiology, spatial epidemiology, Medicine, Biochemistry and Cell Biology, hotspot, Infection, Radboudumc 4: lnfectious Diseases and Global Health RIHS: Radboud Institute for Health Sciences

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    104
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
104
Top 10%
Top 10%
Top 1%
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gold