Evidence map›Paper›PMID 24058722›Full record

ArticleStatistical communications in infectious diseases2012

Episodic HIV Risk Behavior Can Greatly Amplify HIV Prevalence and the Fraction of Transmissions from Acute HIV Infection.

Xinyu Zhang, Lin Zhong, Ethan Romero-Severson, Shah Jamal Alam, Christopher J Henry, Erik M Volz, James S Koopman

Abstract read
In one paragraph

Article in Statistical communications in infectious diseases, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Review
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  9. The missing 27.AIDS (London, England) · 2017
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  14. Observational
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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

7 authors.

Xinyu ZhangUniversity of Michigan - Ann Arbor.
Lin Zhong
Ethan Romero-Severson
Shah Jamal Alam
Christopher J Henry
Erik M Volz
James S Koopman

Funding

HIV Risk Dynamics, Genetic Patterns, and ControlR01AI078752 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KOOPMAN, JAMES STEPHEN · 2008 to 2012
$2.7M
Estimation of HIV Transmission Dynamics Using Genetic Sequences of VirusK01AI091440 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI VOLZ, ERIK MCCULLOUGH · 2010 to 2013
$521k
NIAID NIH HHS K01 AI091440NIAID NIH HHS R01 AI078752
6 · The paper itself

Abstract

A deterministic compartmental model was explored that relaxed the unrealistic assumption in most HIV transmission models that behaviors of individuals are constant over time. A simple model was formulated to better explain the effects observed. Individuals had a high and a low contact rate and went back and forth between them. This episodic risk behavior interacted with the short period of high transmissibility during acute HIV infection to cause dramatic increases in prevalence as the differences between high and low contact rates increased and as the duration of high risk better matched the duration of acute HIV infection. These same changes caused a considerable increase in the fraction of all transmissions that occurred during acute infection. These strong changes occurred despite a constant total number of contacts and a constant total transmission potential from acute infection. Two phenomena played a strong role in generating these effects. First, people were infected more often during their high contact rate phase and they remained with high contact rates during the highly contagious acute infection stage. Second, when individuals with previously low contact rates moved into an episodic high-risk period, they were more likely to be susceptible and thus provided more high contact rate susceptible individuals who could get infected. These phenomena make test and treat control strategies less effective and could cause some behavioral interventions to increase transmission. Signature effects on genetic patterns between HIV strains could make it possible to determine whether these episodic risk effects are acting in a population.

Indexed as

HIVmathematical modelingMSMrisk behavior

Identifiers

PMID24058722
PMCPMC3778933

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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.