Evidence map›Paper›PMID 25892032›Full record

ReviewPathogens and global health2015

The utility of genomic data for Plasmodium vivax population surveillance.

Rachel F Daniels, Benjamin L Rice, Noah M Daniels, Sarah K Volkman, Daniel L Hartl

Abstract readReview
In one paragraph

Review in Pathogens and global health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Clinical microbiology reviews · 2019
    Review
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Rachel F Daniels
Benjamin L Rice
Noah M Daniels
Sarah K Volkman
Daniel L Hartl

Funding

Novel Genetic Mechanism of Artemisinin Resistance for MalariaR01AI099105 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HARTL, DANIEL L, WIRTH, DYANN F · 2013 to 2021
$5.4M
Compressive genomics for large omics data sets: Algorithms applications & toolsR01GM108348 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2013 to 2019
$2.1M
Evolutionary medicine in the development of antimalaria drugsR01AI106734 · NIAID · HARVARD UNIVERSITY · PI HARTL, DANIEL L · 2014 to 2017
$1.6M
NIAID NIH HHS AI106734NIAID NIH HHS R01 AI099105NIAID NIH HHS R01 AI106734NIGMS NIH HHS GM108348
6 · The paper itself

Abstract

Genetic polymorphisms identified from genomic sequencing can be used to track changes in parasite populations through time. Such tracking is particularly informative when applying control strategies and evaluating their effectiveness. Using genomic approaches may also enable improved ability to categorise populations and to stratify them according to the likely effectiveness of intervention. Clinical applications of genomic approaches also allow relapses to be classified according to reinfection or recrudescence. These tools can be used not only to assess the effectiveness of malaria interventions but also to appraise the strategies for malaria elimination.

Indexed as

GenomicsAnimalsAntimalarialsDNA, ProtozoanDrug ResistanceHumansMalaria, VivaxMolecular EpidemiologyPlasmodium vivaxPolymorphism, Single NucleotidePopulation SurveillanceSecondary PreventionAntimalarialsDNA, ProtozoanElimination,Eradication,GenotypingMalaria,Plasmodium vivax,

Identifiers

PMID25892032
PMCPMC4455356

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.