Evidence map›Paper›PMID 21552326›Full record

ReviewPLoS pathogens2011

Genetic assignment methods for gaining insight into the management of infectious disease by understanding pathogen, vector, and host movement.

Justin V Remais, Ning Xiao, Adam Akullian, Dongchuan Qiu, David Blair

Open access · goldAbstract readReview
In one paragraph

Review in PLoS pathogens, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

10 citing papers in PubMed, 18 citations in OpenAlex.

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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 at 4 institutions in 3 countries.

Justin V RemaisDepartment of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA. justin.remais@emory.edu
Ning Xiao
Adam Akullian
Dongchuan Qiu
David Blair
Sichuan Center for Disease Control and Prevention · CNEmory University · USJames Cook University · AUUniversity of California, Berkeley · US

Funding

Models for improving surveillance of environmentally-mediated infectious diseasesK01AI091864 · NIAID · UNIVERSITY OF CALIFORNIA BERKELEY · PI REMAIS, JUSTIN V · 2011 to 2015
$643k
NIAID NIH HHS K01 AI091864NIAID NIH HHS K01AI091864
6 · The paper itself

Abstract

For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease.

Indexed as

Disease VectorsAdministration, OralAnimal MigrationAnimalsChagas DiseaseCoccidioidomycosisCommunicable DiseasesGenetics, PopulationGeographyHost-Parasite InteractionsHumansInsecticidesRabies VaccinesRaccoonsSciuridaeSiphonapteraInsecticidesRabies Vaccines

Identifiers

PMID21552326
PMCPMC3084202
OpenAlexW2055844170

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.