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AIDS and Behavior

, Volume 23, Issue 1, pp 295–301 | Cite as

Estimating the Population Size of Males Who Inject Drugs in Myanmar: Methods for Obtaining Township and National Estimates

  • Lisa G. JohnstonEmail author
  • Phyu-Mar Soe
  • Min Yu Aung
  • Savina Ammassari
Original Paper

Abstract

Estimating the sizes of key populations at risk for HIV is crucial for HIV prevention and treatment. We provide findings of population size estimates (PSE) of males who inject drugs (MWID) in Myanmar, provide an intuitive method for countries to extrapolate subnational estimates into national estimates and provide guidance on how to maximize the utility of current PSE techniques. We used unique object and service multipliers, and successive sampling PSE in conjunction with a respondent driven sampling survey of MWID in ten Myanmar townships in 2014. Township estimates were assessed at a stakeholder meeting for biases and coded into ranges of high, medium and low MWID prevalence areas. Using the sampled townships as benchmarks for a range of MWID proportion estimates, national level MWID size estimates were derived by multiplying the adult male population for all townships with their corresponding proportion estimates. Final PSE ranged from high (4.12%), medium (1.02%) and low (0.11%), with the final agreed national point estimate of 83,000 MWID. Using estimates from survey data, this can translate into actual numbers of MWID living with HIV and practicing risky injecting and sexual behaviors. Although PSE are vital for monitoring HIV epidemics, no guidance exists for interpreting results of different PSE techniques or for extrapolating these results into national estimates. Assessing bias and gaining consensus on township level estimates and deriving ranges of MWID PSE throughout the country using stakeholder input is intuitive and accessible to countries.

Keywords

People who inject drugs Myanmar Population size estimation Respondent driven sampling Multiplers 

Notes

Funding

This study was funded by The Global Fund to Fight AIDS, Tuberculosis and Malaria.

Compliance with Ethical Standards

Conflict of interest

All authors declare no conflict of interest.

Ethicial Aproval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

References

  1. 1.
    UNAIDS. Guidelines on estimating the size of populations most at risk to HIV. Geneva, Switzerland: UNAIDS; 2010. http://www.unaids.org/en/resources/documents/2011/2011_Estimating_Populations
  2. 2.
    Sabin K, Zhao J, Calleja JMG, Sheng Y, Garcia SA, Reinisch A, et al. Availability and quality of size estimations of female sex workers, men who have sex with men, people who inject drugs and transgender women in low- and middle-income countries. PLoS ONE. 2016;11(5):e0155150.  https://doi.org/10.1371/journal.pone.0155150.Google Scholar
  3. 3.
    Johnston L, Saumtally A, Corceal S, Mahadoo I, Oodally F. High HIV and hepatitis C prevalence amongst injecting drug users in Mauritius: findings from a population size estimation and respondent driven sampling survey. Int J Drug Policy. 2011;22(4):252–8.Google Scholar
  4. 4.
    Johnston LG, McLaughlin KR, Rouhani SA, Bartels SA. Measuring a hidden population: a novel technique to estimate the population size of women with sexual violence-related pregnancies in South Kivu Province, Democratic Republic of Congo. J Epidemiol Glob Health. 2017;7(1):45–53.Google Scholar
  5. 5.
    Jose H, Rahman B, Dolan K, Rawstorne P. Population size estimation of female sex workers, men who have sex with men and people who use and inject drugs in Timor-Leste. Dili, Timor-Leste: National HIV/AIDS & STIs Control Programme of the Ministry of Health Timor-Leste; 2015.Google Scholar
  6. 6.
    Johnston LG, Prybylski D, Raymond HF, Mirzazadeh A, Manopaiboon C, McFarland W. Incorporating the service multiplier method in respondent-driven sampling surveys to estimate the size of hidden and hard-to-reach populations: case studies from around the world. Sex Transm Dis. 2013;40(4):304–10.Google Scholar
  7. 7.
    Paz-Bailey G, Jacobson JO, Guardado ME, Hernandez FM, Nieto AI, Estrada M, et al. How many men who have sex with men and female sex workers live in El Salvador? Using respondent-driven sampling and capture-recapture to estimate population sizes. Sex Transm Infect. 2011;87(4):279–82.Google Scholar
  8. 8.
    Sulaberidze L, Mirzazadeh A, Chikovani I, Shengelia N, Tsereteli N, Gotsadze G, et al. Population size estimation of men who have sex with men in Tbilisi, Georgia: multiple methods and triangulation of findings. PLoS ONE. 2016;11(2):e0147413.  https://doi.org/10.1371/journal.pone.0147413.Google Scholar
  9. 9.
    Johnston LG, McLaughlin KR, Rhilani HE, Latifi A, Toufik A, Bennani A, et al. Estimating the size of hidden populations using respondent-driven sampling data: case examples from Morocco. Epidemiology. 2015;26(6):846.Google Scholar
  10. 10.
    Heckathorn DD. Respondent-driven sampling: a new approach to the study of hidden populations. Soc Probl. 1997;44(2):174–99.Google Scholar
  11. 11.
    Heckathorn DD. Extensions of respondent-driven sampling: analyzing continuous variables and controlling for differential recruitment. Sociol Methodol. 2007;37(1):151–207.Google Scholar
  12. 12.
    Gile KJ, Handcock MS. Respondent-driven sampling: an assessment of current methodology. Sociol Methodol. 2010;40(1):285–327.Google Scholar
  13. 13.
    Sabin K, Zhao J, Garcia Calleja JM, Sheng Y, Arias Garcia S, Reinisch A, et al. Availability and quality of size estimations of female sex workers, men who have sex with men, people who inject drugs and transgender women in low- and middle-income countries. PLoS ONE. 2016;11(5):e0155150.Google Scholar
  14. 14.
    Handcock MS, Gile KJ, Mar CM. Estimating hidden population size using respondent-driven sampling data. Electronic Journal of Statistics. 2012;8(1):1491.Google Scholar
  15. 15.
    Handcock MS, Gile KJ, Mar CM. Estimating hidden population size using respondent-driven sampling data. Electron J Stat. 2014;8(1):1491–521.Google Scholar
  16. 16.
    Johnston LG. Introduction to HIV/AIDS and sexually transmitted infection surveillance, module 4, supplement: a guide to using RDS analyst and NetDraw. Geneva: WHO; 2013.Google Scholar
  17. 17.
    Gile KJ, Johnston LG, Salganik MJ. Diagnostics for respondent-driven sampling. J R Stat Soc Ser A. 2015;1(1):241–69.  https://doi.org/10.1111/rssa.12059.Google Scholar
  18. 18.
    McLaughlin KR, Handcock MS, Johnston LG, Japuki X, Gexha-Bunjaku D, Deva E, et al. Inference for the visibility distribution for respondent-driven sampling. In: JSM Proceedings. Alexandria, VA: American Statistical Association; 2015.Google Scholar
  19. 19.
    Johnston LG, McLaughlin KR, El Rhilani H, Latifi A, Toufik A, Bennani A, et al. Estimating the size of hidden populations using respondent-driven sampling data: case examples from Morocco. Epidemiology. 2015;26(6):846–52.Google Scholar
  20. 20.
    Ministry of Labour Immigration and Population. The 2014 Myanmar population and housing census: thematic report on maternal mortality, Vol. 4C. Nay Pi Daw, Myanmar; 2016. http://myanmar.unfpa.org/sites/default/files/pub-pdf/4C_Maternal_Mortality_preview.pdf
  21. 21.
    Handcock MS, Gile KJ, Mar CM. Estimating the size of populations at high risk for HIV using respondent-driven sampling data. Biometrics. 2015;71(1):258–66.Google Scholar
  22. 22.
    UNAIDS. 90-90-90 An ambitious treatment target to help end the AIDS epidemic. Geneva, Switzerland: UNAIDS; 2014. http://www.unaids.org/sites/default/files/media_asset/90-90-90_en_0.pdf
  23. 23.
    National AIDS Program. Myanmar integrated biological and behavioural surveillance survey and population size estimates among people who inject drugs. Nai Pyi Daw; 2016. https://pr-myanmar.org/sites/pr-myanmar.org/files/publication_docs/myanmar_pwid_ibbs_pse_report_300516.pdf
  24. 24.
    National AIDS Control Programme. Global AIDS response progress report Myanmar. 2015. http://www.unaids.org/sites/default/files/country/documents/MMR_narrative_report_2015.pdf
  25. 25.
    Yu D, Calleja JMG, Zhao J, Reddy A, Seguy N. Estimating the size of key populations at higher risk of HIV infection: a summary of experiences and lessons presented during a technical meeting on size estimation among key populations in Asian countries. West Pacific Surveill Response. 2014;5(3):43–9.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Lisa G. Johnston
    • 1
    Email author
  • Phyu-Mar Soe
    • 2
  • Min Yu Aung
    • 3
  • Savina Ammassari
    • 2
  1. 1.Independent Consultant, UNAIDS MyanmarYangonMyanmar
  2. 2.UNAIDS MyanmarYangonMyanmar
  3. 3.National AIDS ProgramYangonMyanmar

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