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Estimation of the impact of changing drug-use trend on HIV, hepatitis C and syphilis epidemics among people who use synthetic drug-only, polydrug and heroin-only during 2005–2035 in China: modelling study
  1. Shu Su1,2,
  2. Christopher K Fairley2,3,
  3. Limin Mao4,
  4. Nicholas Medland2,3,
  5. Mingwang Shen1,
  6. Yan Li5,6,
  7. Guihua Zhuang1,
  8. Lei Zhang1,2,3,7
  1. 1 China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi'an, China
  2. 2 Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
  3. 3 Melbourne Sexual Health Centre, Alfred Health, Melbourne, Victoria, Australia
  4. 4 Center for Social Research in Health, Faculty of Arts and Social Science, University of New South Wales, Sydney, New South Wales, Australia
  5. 5 Health Policy Modeling Laboratory, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
  6. 6 Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
  7. 7 Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan province, China
  1. Correspondence to Dr Lei Zhang, China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi Province, China; lei.zhang1{at}


Objective The rapid expansion of the recreational drug market becomes a global health concern. It is worrying that the bacterial and viral infection epidemics linking to drug use may worsen accordingly. This study aimed to estimate the impacts of changing trend and behaviours of using heroin only, synthetic drug (SD) only and polydrug (using SD and heroin concurrently) on HIV, hepatitis C virus (HCV) and syphilis epidemics among people who use drugs in China by 2035.

Methods We constructed a compartmental model to estimate HIV, HCV and syphilis epidemics in the dynamic drug-use trend by three scenarios: SD-only use, heroin-only use and polydrug use based on Monte Carlo simulations. The parameters for the model were collected from a comprehensive literature search.

Results Our model estimated that polydrug use led to the highest HIV and HCV prevalence among three drug-use patterns. The prevalences were projected to increase from 10.9% (95% CI 10.2% to 11.5%) and 61.7% (95% CI 59.4% to 62.5%) in 2005 to 19.0% (95% CI 17.3% to 20.7%) and 69.1% (95% CI 67.3% to 69.5%), respectively, in 2035 among people using polydrug. Similarly, HIV and HCV prevalence in the SD-only group were projected to increase from 0.4% (95% CI 0.3% to 0.4%) and 19.5% (95% CI 19.4% to 21.7%) to 1.8% (95% CI 1.4 to 2.1%) and 33.7% (95% CI 33.2% to 34.9%) in 2005–2035. Conversely, HIV prevalence in the heroin-only group was projected to decrease from 8.0% (95% CI 7.6% to 8.1%) to 2.2% (95% CI 2.0% to 2.3%) in 2005–2035. Syphilis prevalence was estimated to remain unchanged in all population groups within this time frame. It was projected that the proportion of HIV transmitted by sexual transmission will increase compared with unsafe injection transmission in all people who use drugs from 2005 to 2035.

Conclusion Our modelling suggests that polydrug use is projected to lead to the highest HIV and HCV disease burden by 2035, and the proportion of HIV transmitted by sexual transmission will increase. Current HIV intervention among people using heroin seems effective according to our estimation.

  • HIV
  • hepatitis C
  • syphilis
  • mathematical model
  • drug misuse

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  • Handling editor Laith J Abu-Raddad

  • Correction notice This article has been corrected since it was published online first. The funding statement has been updated.

  • Contributors LZ, CKF and LMM conceived and designed the study; SS and LZ established the model; SS wrote the paper; NM, MWS, CKF, YL, GHZ and LZ revised the manuscript. All authors approved the final manuscript.

  • Funding This work was supported by the National Natural Science Foundation of China (grant numbers: 8191101420, 11801435 (MS)); Thousand Talents Plan Professorship for Young Scholars (grant number: 3111500001); Xi’An Jiaotong University Young Talent Support Program; Xi’an Jiaotong University Basic Research; Profession Grant (grant number: XTR022019003); China Postdoctoral Science Foundation (grant number: 2018M631134); the Fundamental Research Funds for the Central Universities (grant numbers: XJH012019055, XZY032020026) and Natural Science Basic Research Program of Shaanxi Province (grant number: 2019JQ-187).

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement No data are available. The data was all collected from published articles and reports.