Evidence map›Paper›PMID 30839918›Full record

ArticleInfectious Disease Modelling2018

Comparison of different strategies for controlling HIV/AIDS spreading in MSM.

Jie Lou, Jinjin Cheng, Yan Li, Chen Zhang, Hui Xing, Yuhua Ruan, Yiming Shao

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. 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

7 authors.

Jie LouDepartment of Mathematics, Shanghai University, 99 Shangda Road, Shanghai, China.
Jinjin ChengDepartment of Mathematics, Shanghai University, 99 Shangda Road, Shanghai, China.
Yan LiHenan Cable TV Network Group Co., Ltd, Zhengzhou Branch, Zhengzhou, China.
Chen ZhangSchool of Nursing, University of Rochester Medical Center, 255 Crittenden Blvd, Rm 2w218, Rochester, NY, 14642, USA.
Hui XingState Key Laboratory of Infectious Disease Prevention and Control (SKLID), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China.
Yuhua RuanGuangxi Center for Disease Control and Prevention, Nanning, China.
Yiming ShaoState Key Laboratory of Infectious Disease Prevention and Control (SKLID), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As proposed in the UNAIDSs 2014 report, to end global AIDS epidemic by 2030, 90% of people living with HIV need to be diagnosed, 90% of the diagnosed need to receive antiretroviral therapy (ART), and 90% of those on treatment need to achieve viral suppression (90-90-90 strategy). The strategies focus on the reservoir. It controls HIV spreading by reducing infectiousness of HIV infected individuals via diagnosis and treatment. In this manuscript, we compared the effects of HIV/AIDS interventions that focus on different individuals in MSM population through a dynamics model. Our results showed that, the success or not of the "90-90-90" strategies depends on a very important factor: the infectious strength among individuals taking ART. Without highly effective HIV treatment, the "90-90-90" strategies are likely to fail. Therefore, we call for the combination of both primary prevention among the susceptible with the 90-90-90 strategy among the infected to curb the HIV epidemic in Chinese MSM.

Indexed as

39A1192D30Dynamics modelHIV/AIDSPrevention and treatment strategies

Identifiers

PMID30839918
PMCPMC6326225

What OpenQuestion holds

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Registered trials

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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.