Evidence map›Paper›PMID 29164341›Full record

ReviewCurrent topics in microbiology and immunology

Mathematical Models of HIV Latency.

Alison L Hill

Open access · greenAbstract readReview
In one paragraph

Review in Current topics in microbiology and immunology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
11.2field-weighted citation impact, top 1% 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

15 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Review
  11. Article
  12. Review
  13. Modeling the immune response to HIV infection.Current opinion in systems biology · 2018
    Article
  14. Review
  15. 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

1 author at 1 institution in 1 country.

Alison L HillProgram for Evolutionary Dynamics, Harvard University, Cambridge, MA, 02138, USA. alhill@fas.harvard.edu.
Harvard University · US

Funding

Revealing Reservoirs during Rebound (R3)P01AI131385 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DEGRUTTOLA, VICTOR GERARD · 2017 to 2021
$8.7M
Viral dynamics of rebound and control following early treatment of HIV/SIVP01AI131365 · NIAID · BOSTON COLLEGE · PI WHITNEY, JAMES BURTON · 2017 to 2021
$7.5M
Quantification and prediction of treatment efficacy for HIV cure strategiesDP5OD019851 · OD · JOHNS HOPKINS UNIVERSITY · PI HILL, ALISON LYNN · 2014 to 2018
$2.1M
NIAID NIH HHS P01 AI131365NIAID NIH HHS P01 AI131385NIH HHS DP5 OD019851
6 · The paper itself

Abstract

Viral latency is a major barrier to curing HIV infection with antiretroviral therapy, and consequently, for eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best understood and described with the help of mathematical models. Here we review the use of viral dynamics models for HIV, with a focus on applications to the latent reservoir. Such models have been used to explain the multiphasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of posttreatment control. In addition, mathematical models have been used to predict the efficacy of potential HIV cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

Indexed as

Models, BiologicalCD4-Positive T-LymphocytesHIV-1HIV InfectionsHumansViral LoadVirus Latency

Identifiers

PMID29164341
PMCPMC6117215
OpenAlexW2768185530

What OpenQuestion holds

Textmetadata
LicenceTDM
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.