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Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Côte d’Ivoire

Overview of attention for article published in Parasites & Vectors, September 2016
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Title
Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Côte d’Ivoire
Published in
Parasites & Vectors, September 2016
DOI 10.1186/s13071-016-1775-z
Pubmed ID
Authors

Clarisse A. Houngbedji, Frédérique Chammartin, Richard B. Yapi, Eveline Hürlimann, Prisca B. N’Dri, Kigbafori D. Silué, Gotianwa Soro, Benjamin G. Koudou, Serge-Brice Assi, Eliézer K. N’Goran, Agathe Fantodji, Jürg Utzinger, Penelope Vounatsou, Giovanna Raso

Abstract

In Côte d'Ivoire, malaria remains a major public health issue, and thus a priority to be tackled. The aim of this study was to identify spatially explicit indicators of Plasmodium falciparum infection among school-aged children and to undertake a model-based spatial prediction of P. falciparum infection risk using environmental predictors. A cross-sectional survey was conducted, including parasitological examinations and interviews with more than 5,000 children from 93 schools across Côte d'Ivoire. A finger-prick blood sample was obtained from each child to determine Plasmodium species-specific infection and parasitaemia using Giemsa-stained thick and thin blood films. Household socioeconomic status was assessed through asset ownership and household characteristics. Children were interviewed for preventive measures against malaria. Environmental data were gathered from satellite images and digitized maps. A Bayesian geostatistical stochastic search variable selection procedure was employed to identify factors related to P. falciparum infection risk. Bayesian geostatistical logistic regression models were used to map the spatial distribution of P. falciparum infection and to predict the infection prevalence at non-sampled locations via Bayesian kriging. Complete data sets were available from 5,322 children aged 5-16 years across Côte d'Ivoire. P. falciparum was the predominant species (94.5 %). The Bayesian geostatistical variable selection procedure identified land cover and socioeconomic status as important predictors for infection risk with P. falciparum. Model-based prediction identified high P. falciparum infection risk in the north, central-east, south-east, west and south-west of Côte d'Ivoire. Low-risk areas were found in the south-eastern area close to Abidjan and the south-central and west-central part of the country. The P. falciparum infection risk and related uncertainty estimates for school-aged children in Côte d'Ivoire represent the most up-to-date malaria risk maps. These tools can be used for spatial targeting of malaria control interventions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Kenya 1 1%
Nigeria 1 1%
Unknown 73 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 21%
Researcher 14 19%
Student > Ph. D. Student 9 12%
Student > Bachelor 5 7%
Lecturer 5 7%
Other 12 16%
Unknown 14 19%
Readers by discipline Count As %
Medicine and Dentistry 14 19%
Environmental Science 9 12%
Agricultural and Biological Sciences 6 8%
Computer Science 5 7%
Immunology and Microbiology 4 5%
Other 15 20%
Unknown 22 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2016.
All research outputs
#14,168,716
of 24,217,496 outputs
Outputs from Parasites & Vectors
#2,438
of 5,701 outputs
Outputs of similar age
#180,831
of 340,730 outputs
Outputs of similar age from Parasites & Vectors
#51
of 129 outputs
Altmetric has tracked 24,217,496 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,701 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,730 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.