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Epidemiology
Original article
Estimating the size of key populations for HIV in Singapore using the network scale-up method
  1. Alvin Kuo Jing Teo1,
  2. Kiesha Prem1,
  3. Mark I C Chen1,2,
  4. Adrian Roellin1,3,
  5. Mee Lian Wong1,
  6. Hanh Hao La4,5,
  7. Alex R Cook1,3
  1. 1 Saw Swee Hock School of Public Health, National University of Singapore, Singapore
  2. 2 Infectious Disease Research and Training Office, National Centre for Infectious Diseases, Singapore
  3. 3 Department of Statistics and Applied Probability, National University of Singapore, Singapore
  4. 4 Center for High Impact Philanthropy, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  5. 5 Center for Public Health Initiatives, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  1. Correspondence to Dr Alex R Cook, National University Singapore Saw Swee Hock School of Public Health, Singapore 117549; alex.richard.cook{at}gmail.com

  • Present affiliation The present affiliation of Hanh Hao La is: Center for High Impact Philanthropy, Center for Public Health Initiatives, University of Pennsylvania, Pennsylvania, Philadelphia, USA

Abstract

Objectives To develop a localised instrument and Bayesian statistical method to generate size estimates—adjusted for transmission error and barrier effects—of at-risk populations in Singapore.

Methods We conducted indepth interviews and focus group to guide the development of the survey questionnaire. The questionnaire was administered between July and August 2017 in Singapore. Using the network scale-up method (NSUM), we developed a Bayesian hierarchical model to estimate the number of individuals in four hidden populations at risk of HIV. The method accounted for both transmission error and barrier effects using social acceptance measures and demographics.

Results The adjusted size estimate of the population of male clients of female sex workers was 72 000 (95% CI 51 000 to 100 000), of female sex workers 4200 (95% CI 1600 to 10 000), of men who have sex with men 210 000 (95% CI 140 000 to 300 000) and of intravenous drug users 11 000 (95% CI 6500 to 17 000).

Conclusions The NSUM with adjustment for attitudes and demographics allows national-level estimates of multiple priority populations to be determined from simple surveys of the general population, even in relatively conservative societies.

  • Bayes theorem
  • sex workers
  • drug users
  • sexual and gender minorities
  • demography
  • singapore

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/sextrans-2018-053747

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    Footnotes

    • Handling editor Jackie A Cassell

    • AKJT and KP contributed equally.

    • Contributors HHL and ARC conceptualised the study. HHL, ARC and AKJT contributed to study design. AKJT, HHL and KP were involved in data collection. KP, ARC and AR contributed to statistical analysis and made the figures. AKJT, HHL and KP did the literature review. AKJT, KP and ARC wrote the initial draft. All authors contributed equally to data interpretation, critically reviewed the manuscript and approved the final version.

    • Funding This work was funded by the Health Promotion Board Singapore and Singapore Population Health Improvement Centre (SPHERiC), and supported by the Singapore Population Health Studies.

    • Disclaimer The funders did not play a role in the design, conduct or analysis of the study, nor in the drafting of this manuscript.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval We obtained ethics approval for both qualitative and survey phases of the study from the National Unversity of Singapore's Institutional Review Board (references: N-17–012 and S-17–164).

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

    • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.