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Assessment of the utility of a symptom-based algorithm for identifying febrile patients for malaria diagnostic testing in Senegal

Overview of attention for article published in Malaria Journal, March 2017
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3 tweeters

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5 Dimensions

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36 Mendeley
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Title
Assessment of the utility of a symptom-based algorithm for identifying febrile patients for malaria diagnostic testing in Senegal
Published in
Malaria Journal, March 2017
DOI 10.1186/s12936-017-1750-y
Pubmed ID
Authors

Julie Thwing, Fatou Ba, Alou Diaby, Younouss Diedhiou, Assane Sylla, Guelaye Sall, Mame Birame Diouf, Alioune Badara Gueye, Seynabou Gaye, Medoune Ndiop, Moustapha Cisse, Daouda Ndiaye, Mady Ba

Abstract

Malaria rapid diagnostic tests (RDTs) enable point-of-care testing to be nearly as sensitive and specific as reference microscopy. The Senegal National Malaria Control Programme introduced RDTs in 2007, along with a case management algorithm for uncomplicated febrile illness, in which the first step stipulates that if a febrile patient of any age has symptoms indicative of febrile illness other than malaria (e.g., cough or rash), they would not be tested for malaria, but treated for the apparent illness and receive an RDT for malaria only if they returned in 48 h without improvement. A year-long study in 16 health posts was conducted to determine the algorithm's capacity to identify patients with Plasmodium falciparum infection identifiable by RDT. Health post personnel enrolled patients of all ages with fever (≥37.5 °C) or history of fever in the previous 2 days. After clinical assessment, a nurse staffing the health post determined whether a patient should receive an RDT according to the diagnostic algorithm, but performed an RDT for all enrolled patients. Over 1 year, 6039 patients were enrolled and 58% (3483) were determined to require an RDT according to the algorithm. Overall, 23% (1373/6039) had a positive RDT, 34% (1130/3376) during rainy season and 9% (243/2661) during dry season. The first step of the algorithm identified only 78% of patients with a positive RDT, varying by transmission season (rainy 80%, dry 70%), malaria transmission zone (high 75%, low 95%), and age group (under 5 years 68%, 5 years and older 84%). In all but the lowest malaria transmission zone, use of the algorithm excludes an unacceptably large proportion of patients with malaria from receiving an RDT at their first visit, denying them timely diagnosis and treatment. While the algorithm was adopted within a context of malaria control and scarce resources, with the goal of treating patients with symptomatic malaria, Senegal has now adopted a policy of universal diagnosis of patients with fever or history of fever. In addition, in the current context of malaria elimination, the paradigm of case management needs to shift towards the identification and treatment of all patients with malaria infection.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 17%
Student > Ph. D. Student 5 14%
Student > Master 5 14%
Student > Postgraduate 4 11%
Student > Bachelor 2 6%
Other 8 22%
Unknown 6 17%
Readers by discipline Count As %
Medicine and Dentistry 11 31%
Nursing and Health Professions 8 22%
Biochemistry, Genetics and Molecular Biology 2 6%
Agricultural and Biological Sciences 2 6%
Computer Science 1 3%
Other 4 11%
Unknown 8 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 02 March 2017.
All research outputs
#4,421,373
of 9,138,320 outputs
Outputs from Malaria Journal
#1,999
of 3,176 outputs
Outputs of similar age
#125,770
of 253,874 outputs
Outputs of similar age from Malaria Journal
#80
of 121 outputs
Altmetric has tracked 9,138,320 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,176 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 253,874 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.