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Estimating the Number of Persons Who Inject Drugs in the United States by Meta-Analysis to Calculate National Rates of HIV and Hepatitis C Virus Infections

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Listed:
  • Amy Lansky
  • Teresa Finlayson
  • Christopher Johnson
  • Deborah Holtzman
  • Cyprian Wejnert
  • Andrew Mitsch
  • Deborah Gust
  • Robert Chen
  • Yuko Mizuno
  • Nicole Crepaz

Abstract

Background: Injection drug use provides an efficient mechanism for transmitting bloodborne viruses, including human immunodeficiency virus (HIV) and hepatitis C virus (HCV). Effective targeting of resources for prevention of HIV and HCV infection among persons who inject drugs (PWID) is based on knowledge of the population size and disparity in disease burden among PWID. This study estimated the number of PWID in the United States to calculate rates of HIV and HCV infection. Methods: We conducted meta-analysis using data from 4 national probability surveys that measured lifetime (3 surveys) or past-year (3 surveys) injection drug use to estimate the proportion of the United States population that has injected drugs. We then applied these proportions to census data to produce population size estimates. To estimate the disease burden among PWID by calculating rates of disease we used lifetime population size estimates of PWID as denominators and estimates of HIV and HCV infection from national HIV surveillance and survey data, respectively, as numerators. We calculated rates of HIV among PWID by gender-, age-, and race/ethnicity. Results: Lifetime PWID comprised 2.6% (95% confidence interval: 1.8%–3.3%) of the U.S. population aged 13 years or older, representing approximately 6,612,488 PWID (range: 4,583,188–8,641,788) in 2011. The population estimate of past-year PWID was 0.30% (95% confidence interval: 0.19 %–0.41%) or 774,434 PWID (range: 494,605–1,054,263). Among lifetime PWID, the 2011 HIV diagnosis rate was 55 per 100,000 PWID; the rate of persons living with a diagnosis of HIV infection in 2010 was 2,147 per 100,000 PWID; and the 2011 HCV infection rate was 43,126 per 100,000 PWID. Conclusion: Estimates of the number of PWID and disease rates among PWID are important for program planning and addressing health inequities.

Suggested Citation

  • Amy Lansky & Teresa Finlayson & Christopher Johnson & Deborah Holtzman & Cyprian Wejnert & Andrew Mitsch & Deborah Gust & Robert Chen & Yuko Mizuno & Nicole Crepaz, 2014. "Estimating the Number of Persons Who Inject Drugs in the United States by Meta-Analysis to Calculate National Rates of HIV and Hepatitis C Virus Infections," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-9, May.
  • Handle: RePEc:plo:pone00:0097596
    DOI: 10.1371/journal.pone.0097596
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    References listed on IDEAS

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    1. Holmberg, S.D., 1996. "The estimated prevalence and incidence of HIV in 96 large US metropolitan areas," American Journal of Public Health, American Public Health Association, vol. 86(5), pages 642-654.
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    1. Hannah L F Cooper & Sabriya Linton & Mary E Kelley & Zev Ross & Mary E Wolfe & Yen-Tyng Chen & Maria Zlotorzynska & Josalin Hunter-Jones & Samuel R Friedman & Don C Des Jarlais & Barbara Tempalski & E, 2016. "Risk Environments, Race/Ethnicity, and HIV Status in a Large Sample of People Who Inject Drugs in the United States," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-21, March.
    2. Georgiy Bobashev & Sarah Mars & Nicholas Murphy & Clinton Dreisbach & William Zule & Daniel Ciccarone, 2019. "Heroin type, injecting behavior, and HIV transmission. A simulation model of HIV incidence and prevalence," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-17, December.
    3. Amy Lansky & Christopher Johnson & Emeka Oraka & Catlainn Sionean & M Patricia Joyce & Elizabeth DiNenno & Nicole Crepaz, 2015. "Estimating the Number of Heterosexual Persons in the United States to Calculate National Rates of HIV Infection," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-13, July.
    4. Natalia Estévez-Lamorte & Simon Foster & Gerhard Gmel & Meichun Mohler-Kuo, 2021. "Routes of Administration of Illicit Drugs among Young Swiss Men: Their Prevalence and Associated Socio-Demographic Characteristics and Adverse Outcomes," IJERPH, MDPI, vol. 18(21), pages 1-17, October.

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