Evidence map›Paper›PMID 26989062›Full record

ArticleJournal of the International AIDS Society2016

Estimating HIV incidence among key affected populations in China from serial cross-sectional surveys in 2010-2014.

Yan Cui, Wei Guo, Dongmin Li, Liyan Wang, Cynthia X Shi, Ron Brookmeyer, Roger Detels, Lin Ge, Zhengwei Ding, Zunyou Wu

Abstract read
In one paragraph

Article in Journal of the International AIDS Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. The Enigma of the Human Immunodeficiency Virus (HIV) Epidemic in China.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
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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

10 authors.

Yan CuiDivision of Epidemiology, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Wei GuoDivision of Epidemiology, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dongmin LiDivision of Epidemiology, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Liyan WangDivision of Epidemiology, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Cynthia X ShiDivision of Prevention and Intervention, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Ron BrookmeyerDepartment of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA.
Roger DetelsDepartment of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA.
Lin GeDivision of Epidemiology, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhengwei DingDivision of Epidemiology, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zunyou WuNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; wuzy@263.netwuzunyou@chinaaids.cn.

Funding

UCLA Rapid, Relevant, Rigorous Implementation Science HubP30MH058107 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RAPHAEL J LANDOVITZ · 1997 to 2026
$53.5M
Laboratory and Statistical Development of Cross-Sectional HIV Incidence AssaysR01AI095068 · NIAID · JOHNS HOPKINS UNIVERSITY · PI ESHLEMAN, SUSAN H · 2011 to 2021
$6.6M
NIAID NIH HHS R01 AI095068NIMH NIH HHS P30 MH058107
6 · The paper itself

Abstract

introductionHIV incidence is an important measure for monitoring the development of the epidemic, but it is difficult to ascertain. We combined serial HIV prevalence and mortality data to estimate HIV incidence among key affected populations (KAPs) in China.

methodsSerial cross-sectional surveys were conducted among KAPs from 2010 to 2014. Trends in HIV prevalence were assessed by the Cochran-Armitage test, adjusted by risk group. HIV incidence was estimated from a mathematical model that describes the relationship between changes in HIV incidence with HIV prevalence and mortality.

resultsThe crude HIV prevalence for the survey samples remained stable at 1.1 to 1.2% from 2010 to 2014. Among drug users (DUs), HIV prevalence declined from 4.48 to 3.29% (p<0.0001), and among men who have sex with men (MSM), HIV prevalence increased from 5.73 to 7.75% (p<0.0001). Changes in HIV prevalence among female sex workers (FSWs) and male patients of sexually transmitted disease clinics were more modest but remained statistically significant (all p<0.0001). The MSM population had the highest incidence estimates at 0.74% in 2011, 0.59% in 2012, 0.57% in 2013 and 0.53% in 2014. Estimates of the annual incidence for DUs and FSWs were very low and may not be reliable.

conclusionsSerial cross-sectional prevalence data from representative samples may be another approach to construct approximate estimates of national HIV incidence among key populations. We observed that the MSM population had the highest incidence for HIV among high-risk groups in China, and we suggest that interventions targeting MSM are urgently needed to curb the growing HIV epidemic.

Indexed as

ChinaCross-Sectional StudiesDrug UsersFemaleHIV InfectionsHomosexuality, MaleHumansIncidenceMalePrevalenceSex WorkersTime Factorscross-sectional surveyHIVincidencekey affected populationsmortalityprevalence

Identifiers

PMID26989062
PMCPMC4796775

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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.