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Limitations of malaria reactive case detection in an area of low and unstable transmission on the Myanmar–Thailand border

Overview of attention for article published in Malaria Journal, November 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Title
Limitations of malaria reactive case detection in an area of low and unstable transmission on the Myanmar–Thailand border
Published in
Malaria Journal, November 2016
DOI 10.1186/s12936-016-1631-9
Pubmed ID
Authors

Daniel M. Parker, Jordi Landier, Lorenz von Seidlein, Arjen Dondorp, Lisa White, Borimas Hanboonkunupakarn, Richard J. Maude, François H. Nosten

Abstract

Reactive case detection is an approach that has been proposed as a tool for malaria elimination in low-transmission settings. It is an intuitively justified approach based on the concept of space-time clustering of malaria cases. When an index malaria clinical case is detected, it triggers reactive screening and treatment in the index house and neighbouring houses. However, the efficacy of this approach at varying screening radii and malaria prevalence remains ill defined. Data were obtained from a detailed demographic and geographic surveillance study in four villages on the Myanmar-Thailand border. Clinical cases were recorded at village malaria clinics and were linked back to patients' residencies. These data were used to simulate the efficacy of reactive case detection for clinical cases using rapid diagnostic tests (RDT). Simulations took clinical cases in a given month and tabulated the number of cases that would have been detected in the following month at varying screening radii around the index houses. Simulations were run independently for both falciparum and vivax malaria. Each simulation of a reactive case detection effort was run in comparison with a strategy using random selection of houses for screening. In approximately half of the screenings for falciparum and 10% for vivax it would have been impossible to detect any malaria cases regardless of the screening strategy because the screening would have occurred during times when there were no cases. When geographically linked cases were present in the simulation, reactive case detection would have only been successful at detecting most malaria cases using larger screening radii (150-m radius and above). At this screening radius and above, reactive case detection does not perform better than random screening of an equal number of houses in the village. Screening within very small radii detects only a very small proportion of cases, but despite this low performance is better than random screening with the same sample size. The results of these simulations indicate that reactive case detection for clinical cases using RDTs has limited ability in halting transmission in regions of low and unstable transmission. This is linked to high spatial heterogeneity of cases, acquisition of malaria infections outside the village, as well missing asymptomatic infections. When cases are few and sporadic, reactive case detection would result in major time and budgetary losses.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Thailand 1 1%
Unknown 80 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 23%
Student > Ph. D. Student 11 14%
Student > Master 10 12%
Student > Doctoral Student 5 6%
Lecturer 4 5%
Other 11 14%
Unknown 21 26%
Readers by discipline Count As %
Medicine and Dentistry 19 23%
Nursing and Health Professions 5 6%
Biochemistry, Genetics and Molecular Biology 5 6%
Social Sciences 5 6%
Computer Science 4 5%
Other 15 19%
Unknown 28 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 February 2017.
All research outputs
#6,022,410
of 24,380,741 outputs
Outputs from Malaria Journal
#1,478
of 5,820 outputs
Outputs of similar age
#102,918
of 424,284 outputs
Outputs of similar age from Malaria Journal
#24
of 89 outputs
Altmetric has tracked 24,380,741 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,820 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 74% 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 424,284 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 89 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 74% of its contemporaries.