Estimating the Size of Key Populations for HIV in Singapore Using The

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Estimating the Size of Key Populations for HIV in Singapore Using The Epidemiology Sex Transm Infect: first published as 10.1136/sextrans-2018-053747 on 9 May 2019. Downloaded from ORIGINAL ARTICLE Estimating the size of key populations for HIV in Singapore using the network scale-up method Alvin Kuo Jing Teo, 1 Kiesha Prem,1 Mark I C Chen,1,2 Adrian Roellin,1,3 Mee Lian Wong,1 Hanh Hao La,4,5 Alex R Cook1,3 ► Additional material is ABSTRact applied in various countries to estimate sizes of published online only. To view Objectives To develop a localised instrument and at-risk populations. It was simple to implement please visit the journal online 5 (http:// dx. doi. org/ 10. 1136/ Bayesian statistical method to generate size estimates— and less expensive, and yielded important infor- sextrans- 2018- 053747). adjusted for transmission error and barrier effects—of mation for individual country-level HIV prevention at-risk populations in Singapore. programme planning, monitoring and evalua- 1 Saw Swee Hock School Methods We conducted indepth interviews and tion.6–8 Given these successes, the NSUM may be of Public Health, National focus group to guide the development of the survey suitable for behavioural surveillance in Singapore, University of Singapore, Singapore questionnaire. The questionnaire was administered and it is therefore of interest that we evaluate the 2Infectious Disease Research between July and August 2017 in Singapore. Using feasibility of using a similar strategy locally. Find- and Training Office, National the network scale-up method (NSUM), we developed ings from this study will inform the development Centre for Infectious Diseases, a Bayesian hierarchical model to estimate the number of the tools and methodologies to estimate the size Singapore 3Department of Statistics and of individuals in four hidden populations at risk of HIV. of populations at risk of HIV and provide pertinent Applied Probability, National The method accounted for both transmission error and information to complement the national-level HIV University of Singapore, barrier effects using social acceptance measures and surveillance system. Singapore 4 demographics. The objectives of this study are to generate esti- Center for High Impact Results The adjusted size estimate of the population of mates of the size of four key populations at risk of Philanthropy, University of Pennsylvania, Philadelphia, male clients of female sex workers was 72 000 (95% CI HIV—male clients of female sex workers (MCFSW), Pennsylvania, USA 51 000 to 100 000), of female sex workers 4200 (95% MSM, female sex workers (FSW) and intravenous 5Center for Public Health CI 1600 to 10 000), of men who have sex with men 210 drug users (IVDU)—and develop methods to incor- Initiatives, University of 000 (95% CI 140 000 to 300 000) and of intravenous porate parameters that may account for both trans- Pennsylvania, Philadelphia, Pennsylvania, USA drug users 11 000 (95% CI 6500 to 17 000). mission error and barrier effects that are inherent Conclusions The NSUM with adjustment for attitudes in the NSUM. Correspondence to and demographics allows national-level estimates of Dr Alex R Cook, National multiple priority populations to be determined from University Singapore Saw Swee simple surveys of the general population, even in METHODS http://sti.bmj.com/ Hock School of Public Health, relatively conservative societies. Overview Singapore 117549; alex. richard. We developed and fielded the NSUM survey4 and cook@ gmail. com developed a Bayesian hierarchical NSUM model AKJT and KP contributed to determine the national-level size estimates of equally. INTRODUCTION key populations at risk of HIV in Singapore. The The HIV epidemic in Singapore is classified as low approach is outlined below and detailed in the Received 27 June 2018 level but is likely to be a concentrated epidemic on September 30, 2021 by guest. Protected copyright. Revised 1 April 2019 online supplementary material. Accepted 10 April 2019 among key populations such as men who have sex with men (MSM).1 2 Most new HIV infections occur among men, and 95% of cases were acquired Questionnaire design through sexual transmission in 2016.3 Like many First, we conducted formative research between Asian countries, Singapore does not currently have March and May 2017 to adapt the NSUM to the a systematic approach to collect data on the size Singapore context. Four focus group discussions of key populations that are most likely to acquire using homogeneous participants and nine indepth and transmit HIV. Without these populations size interviews were conducted with key stakeholders estimates, it is challenging to generate reliable working in the field of HIV/AIDS—clinicians, © Author(s) (or their projections of the number of people with HIV, academics, programme officers, social workers, employer(s)) 2019. Re-use effectively plan or evaluate prevention and treat- counsellors and policymakers—to guide the devel- permitted under CC BY-NC. No ment responses, or allocate resources. opment of the size estimation component of the commercial re-use. See rights and permissions. Published The network scale-up method (NSUM) is a HIV surveillance system in Singapore. Participants by BMJ. relatively new and promising approach to esti- were purposively sampled by the research team to mate the size of hard-to-reach populations at maximise efficiency and data validity. Information To cite: Teo AKJ, risk of HIV/AIDS.4 It involves estimation of the collected from the formative assessment was used Prem K, Chen MIC, et al. Sex Transm Infect Epub ahead personal network size of a representative sample to develop the survey questionnaire, as detailed in of print: [please include Day of the general population and, with this infor- online supplementary table 1 and online supple- Month Year]. doi:10.1136/ mation, estimation of the number of members of mentary table 2. The questionnaire was pilot-tested sextrans-2018-053747 a hidden subpopulation. This method has been prior to the main survey. Teo AKJ, et al. Sex Transm Infect 2019;0:1–6. doi:10.1136/sextrans-2018-053747 1 Epidemiology Sex Transm Infect: first published as 10.1136/sextrans-2018-053747 on 9 May 2019. Downloaded from Data source population sizes. A mean 1 random effect αi for each participant The Singapore Population Health Studies (SPHS) is a consor- was used to characterise variability in network size. Non-inform- tium of several population health cohorts in Singapore, namely ative prior distributions were assigned to the subpopulation sizes the Multi-Ethnic Cohort, Diabetic Cohort and Singapore and the scaling parameter, and a non-informative hyperprior for Health Study. The sampling method for the cohort studies has the precision of the random effect. The fitted model was also been previously described.9 10 We recruited SPHS participants used to estimate the average social network size, λS , where S is between 21 and 70 years old. Those who were illiterate or did the size of the population living in Singapore. not fulfil the age criteria were excluded. Because the basic model does not account for two structural features that may bias estimates of the four key populations at Data collection risk of HIV/AIDS, two variants of the basic model were consid- Out of the 269 individuals approached between July and August ered—transmission error model and transmission error and 2017, 17 did not fulfil the age criteria, while 53 were either barrier effect model—both described below. The former accounts illiterate or declined to participate. In total, 199 individuals for transmission error by incorporating respondents’ perception were recruited. The SPHS and research staff explained the study of that population. The latter builds on the former by incorpo- and answered any questions that the participant had before rating demographics, which may be associated with the chance the questionnaire was completed onsite. The self-administered of knowing people in the hidden populations. questionnaire was made available in the three main languages in Singapore—Chinese, English and Malay. The questionnaire Transmission error model was anonymous and verbal consent was obtained from all partic- We attempted to adjust for transmission error—the possibility ipants. Participants were reimbursed with S$10 (~US$7.30) on that members of the hidden population might not divulge completion. membership to some of their contacts—by introducing a correc- tion factor to estimate the size of the at-risk populations. In this Measures model, the mean of the Poisson variate of the number of at-risk The questionnaire sought participants’ sociodemographic infor- populations is modified to account for the individual’s percep- mation, their opinions about certain behaviours, the social tion of that population measured through the variable xi,j : standing of different groups of people and their opinions on H H N Po λαi exp βl xi,l Ul S penal code section 377A.11 Participants were requested to quan- i,l ∼ − l ( ) tify the number of people whom they knew from a list of 24 where U l is the upper bound of the{ Likert[ scale]} for the question specified populations (the 19 known populations are listed in to which xi,l corresponds, and β (if >0) lowers the mean number online supplementary table 4) and how have they been in contact of people belonging to a hidden population who are known with one person from each category within the last year (the one to the individual and whose membership of the hidden popu- person being the most recently contacted). lation is known to the individual, if that individual expresses In this study, we defined knowing a person as follows: A an unfavourable attitude towards that population. For instance, knows B if (1) A knows B by name and sight, and vice versa; (2) someone who has an unfavourable attitude towards MSM may B is currently living in Singapore; and (3) A had contact with B know fewer people who have confided their sexuality to that at least once in the last 12 months.
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