Evidence map›Paper›PMID 16721632›Full record

ReviewEuropean journal of epidemiology2006

Gaining insights into human viral diseases through mathematics.

Seyed M Moghadas

Open access · bronzeAbstract readReview
In one paragraph

Review in European journal of epidemiology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

1 author at 1 institution in 1 country.

Seyed M MoghadasInstitute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, R3B 1Y6, Winnipeg, Manitoba, Canada. Seyed.Moghadas@nrc-cnrc.gc.ca
National Research Council Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mathematical models have been recognized as powerful tools for providing new insights into the understanding of viral dynamics of human diseases at both the population and cellular levels. This article briefly reviews the role of mathematical models and their historical precedents for creating new knowledge of the mechanisms of disease pathogenesis, transmission, and control of some human viral infections. Future research in the modelling of infectious diseases will need to rely upon incorporation of the fundamental principles that govern viral dynamics in vivo as well as in the population.

Indexed as

HumansMathematicsModels, BiologicalVirus Diseases

Identifiers

PMID16721632
PMCPMC7087669
OpenAlexW2007422223

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.