Evidence map›Paper›PMID 25781919›Full record

ArticleViruses2015

Simple mathematical models do not accurately predict early SIV dynamics.

Cecilia Noecker, Krista Schaefer, Kelly Zaccheo, Yiding Yang, Judy Day, Vitaly V Ganusov

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2015. 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
1.7field-weighted citation impact, top 16% 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, 21 citations in OpenAlex.

  1. Article
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  3. Article
  4. Review
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  7. Article
  8. Modeling Kick-Kill Strategies toward HIV Cure.Frontiers in immunology · 2017
    Review
  9. Article
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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

6 authors at 2 institutions in 1 country.

Cecilia NoeckerNational institute for Mathematical and Biological synthesis (NIMBioS), Knoxville, TN 37996, USA. cecilia.noecker@gmail.com.
Krista SchaeferNational institute for Mathematical and Biological synthesis (NIMBioS), Knoxville, TN 37996, USA. krista.schaefer@valpo.edu.
Kelly ZaccheoNational institute for Mathematical and Biological synthesis (NIMBioS), Knoxville, TN 37996, USA. k.zaccheo@yahoo.com.
Yiding YangDepartment of Microbiology, University of Tennessee, Knoxville, TN 37996, USA. yidingyang@gmail.com.
Judy DayNational institute for Mathematical and Biological synthesis (NIMBioS), Knoxville, TN 37996, USA. judyday@utk.edu.
Vitaly V GanusovNational institute for Mathematical and Biological synthesis (NIMBioS), Knoxville, TN 37996, USA. vitaly.ganusov@gmail.com.
National Institute for Mathematical and Biological Synthesis · USUniversity of Tennessee at Knoxville · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1-2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the "standard" mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available.

Indexed as

Models, TheoreticalViral LoadAnimalsBloodMacaca mulattaSimian Acquired Immunodeficiency SyndromeSimian Immunodeficiency Virus

Identifiers

PMID25781919
PMCPMC4379566
OpenAlexW2007985320

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.