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

Application of the network scale-up method to estimate the sizes of key populations for HIV in Singapore using online surveys

INTRODUCTION

Singapore lacks robust data on the sizes of the key populations that are most at risk for HIV. Using the network scale-up method for hidden or hard-to-reach populations, we estimate the sizes of five key populations-male clients of female sex workers (MCFSW), men who have sex with men (MSM), female sex workers (FSW), people who inject drugs (PWID) and transgender people-and profile the ages and ethnicities of respondents with the high-risk contacts they report knowing.

METHODS

We conducted a cross-sectional online survey between March and May 2019 (n = 2802) using a network scale-up instrument previously developed for Singapore. Participants were recruited using an existing panel and online advertising, and the sample reweighted by age, sex, ethnicity and education attained to represent the general adult population. We built a Bayesian hierarchical model to estimate the sizes of the five key populations for HIV in Singapore.

RESULTS

After adjustment, the sizes of the at-risk populations are estimated to be: 76,800 (95% credible interval [CI]: 64,200-91,800) MCFSW; 139,000 (95% CI: 120,000-160,000) MSM; 8030 (95% CI: 3980-16,200) FSW; 3470 (95% CI: 1540-7830) PWID and 18,000 (95% CI: 14,000-23,200) transgender people. Generally, men reported knowing more people in all the high-risk groups; older people reported knowing more MCFSW, FSW and transgender people; and younger people reported knowing more MSM. There was a bimodal effect of age on those who reported knowing more PWIDs: people in their 20s and 60s reported more contacts.

CONCLUSIONS

This study demonstrates that a size estimation study of hidden populations is quickly and efficiently scalable through using online surveys in a socially conservative society, like Singapore, where key populations are stigmatized or criminalized. The approach may be suitable in other countries where stigma is prevalent and where barriers to surveillance and data collection are numerous.

Characteristics and Population Size Estimation of Female Sex Workers in Bhutan

BACKGROUND

Knowing the number of persons at risk for sexually transmitted diseases (STDs) and their risk behaviors are needed to allocate limited resources, set targets for prevention and care activities, gauge the reach of programs, and assess their impact. Female sex workers (FSWs) are a population at high risk for STD worldwide; little is known about FSW in Bhutan.

METHODS

We conducted a community-based survey and population size exercise of FSW in Bhutan. The survey used a hybrid venue-based/peer-referral sampling method. Population size estimation methods were key informant mapping, census and enumeration, unique object multiplier, and capture-recapture.

RESULTS

Of 517 women surveyed, 67.5% provided sex for money in the last year. Compared with FSWs at venues, FSWs referred by peers were more likely to have sex with alcohol (80.1% vs. 51.5%, P < 0.001) and more paying partners (mean, 3.5 vs. 2.0; P = 0.001), and less likely to have tested for an STD (28.3% vs. 51.0%, P < 0.001) or have outreach worker contact (27.6% vs. 41.5%, P = 0.007). The estimated number of FSWs in the 9 districts was 353 (95% confidence interval, 345-362). Extrapolation to the whole country projected 597 (417-777) FSWs nationally.

CONCLUSIONS

Our estimate of the number of FSW in Bhutan corresponds to 0.71% of adult urban women, a figure in line with other countries in South and Southeast Asia. Our data highlight the need for outreach beyond venues where women are employed to reach FSW at higher risk for STD but who have less access to interventions.

Updates to Spectrum's case surveillance and vital registration tool for HIV estimates and projections

INTRODUCTION

The Case Surveillance and Vital Registration (CSAVR) model within Spectrum estimates HIV incidence trends from surveillance data on numbers of new HIV diagnoses and HIV-related deaths. This article describes developments of the CSAVR tool to more flexibly model diagnosis rates over time, estimate incidence patterns by sex and age group and by key population group.

METHODS

We modelled HIV diagnosis rate trends as a mixture of three factors, including temporal and opportunistic infection components. The tool was expanded to estimate incidence rate ratios by sex and age for countries with disaggregated reporting of new HIV diagnoses and AIDS deaths, and to account for information on key populations such as men who have sex with men (MSM), males who inject drugs (MWID), female sex workers (FSW) and females who inject drugs (FWID). We used a Bayesian framework to calibrate the tool in 71 high-income or low-HIV burden countries.

RESULTS

Across countries, an estimated median 89% (interquartile range [IQR]: 78%-96%) of HIV-positive adults knew their status in 2019. Mean CD4 counts at diagnosis were stable over time, with a median of 456 cells/μl (IQR: 391-508) across countries in 2019. In European countries reporting new HIV diagnoses among key populations, median estimated proportions of males that are MSM and MWID was 1.3% (IQR: 0.9%-2.0%) and 0.56% (IQR: 0.51%-0.64%), respectively. The median estimated proportions of females that are FSW and FWID were 0.36% (IQR: 0.27%-0.45%) and 0.14 (IQR: 0.13%-0.15%), respectively. HIV incidence per 100 person-years increased among MSM, with median estimates reaching 0.43 (IQR: 0.29-1.73) in 2019, but remained stable in MWID, FSW and FWID, at around 0.12 (IQR: 0.04-1.9), 0.09 (IQR: 0.06-0.69) and 0.13% (IQR: 0.08%-0.91%) in 2019, respectively. Knowledge of HIV status among HIV-positive adults gradually increased since the early 1990s to exceed 75% in more than 75% of countries in 2019 among each key population.

CONCLUSIONS

CSAVR offers an approach to using routine surveillance and vital registration data to estimate and project trends in both HIV incidence and knowledge of HIV status.

shinyrecap: A Shiny Application for Population Size Estimation from Capture-Recapture Data (Preprint)

Background

Population size estimates (PSE) provide critical information in determining resource allocation for HIV services geared toward those at high risk of HIV, including female sex workers, men who have sex with men, and people who inject drugs. Capture-recapture (CRC) is often used to estimate the size of these often-hidden populations. Compared with the commonly used 2-source CRC, CRC relying on 3 (or more) samples (3S-CRC) can provide more robust PSE but involve far more complex statistical analysis.

Objective

This study aims to design and describe the Shiny application (shinyrecap), a user-friendly interface that can be used by field epidemiologists to produce PSE.

Methods

shinyrecap is built on the Shiny web application framework for R. This allows it to seamlessly integrate with the sophisticated CRC statistical packages (eg, Rcapture, dga, LCMCR). Additionally, the application may be accessed online or run locally on the user’s machine.

Results

The application enables users to engage in sample size calculation based on a simulation framework. It assists in the proper formatting of collected data by providing a tool to convert commonly used formats to that used by the analysis software. A wide variety of methodologies are supported by the analysis tool, including log-linear, Bayesian model averaging, and Bayesian latent class models. For each methodology, diagnostics and model checking interfaces are provided.

Conclusions

Through a use case, we demonstrated the broad utility of this powerful tool with 3S-CRC data to produce PSE for female sex workers in a subnational unit of a country in sub-Saharan Africa.

Programmatic mapping and size estimation of female sex workers, transgender sex workers and men who have sex with men in İstanbul and Ankara, Turkey

OBJECTIVES

Despite a growing HIV threat, there is no definition and characterisation of key populations (KPs), who could be the major drivers of the epidemic in Turkey. We used programmatic mapping to identify locations where KPs congregate, estimate their numbers and understand their operational dynamics to develop appropriate HIV programme implementation strategies.

METHODS

Female and transgender sex workers (FSWs and TGSWs), and men who have sex with men (MSM) were studied in İstanbul and Ankara. Within each district, hot spots were identified by interviewing key informants and a crude spot list in each district was developed. The spot validation process was led by KP members who facilitated spot access and interviews of KPs associated with that spot. Final estimates were derived by aggregating the estimated number of KPs at all spots, which was adjusted for the proportion of KPs who visit multiple spots, and for the proportion of KPs who do not visit spots.

RESULTS

FSWs were the largest KP identified in İstanbul with an estimate of 30 447 (5.8/1000 women), followed by 15 780 TGSWs (2.9/1000 men) and 11 656 MSM (2.1/1000). The corresponding numbers in Ankara were 9945 FSWs (5.2/1000 women), 1770 TGSWs (1/1000 men) and 5018 MSM (2.5/1000 men). Each KP had unique typologies based on the way they find and interact with sex partners. MSM were mostly hidden and a higher proportion operated through internet and phone-based applications. Night time was the peak time with Friday, Saturday and Sunday being the peak days of activity in both İstanbul and Ankara.

CONCLUSIONS

This study has highlighted the presence of a substantial number of FSWs, TGSW and MSM in İstanbul and Ankara. The information obtained from this study can be used to set priorities for resource allocation and provide HIV prevention services where coverage could be the highest.

Estimating the Population Size of Female Sex Workers in Zimbabwe: Comparison of Estimates Obtained Using Different Methods in Twenty Sites and Development of a National-Level Estimate

National-level population size estimates (PSEs) for hidden populations are required for HIV programming and modelling. Various estimation methods are available at the site-level, but it remains unclear which are optimal and how best to obtain national-level estimates.

Using factor analyses to estimate the number of female sex workers across Malawi from multiple regional sources

PURPOSE

Human immunodeficiency virus (HIV) risks are heterogeneous in nature even in generalized epidemics. However, data are often missing for those at highest risk of HIV, including female sex workers. Statistical models may be used to address data gaps where direct, empiric estimates do not exist.

METHODS

We proposed a new size estimation method that combines multiple data sources (the Malawi Biological and Behavioral Surveillance Survey, the Priorities for Local AIDS Control Efforts study, and the Malawi Demographic Household Survey). We used factor analysis to extract information from auxiliary variables and constructed a linear mixed effects model for predicting population size for all districts of Malawi.

RESULTS

On average, the predicted proportion of female sex workers among women of reproductive age across all districts was about 0.58%. The estimated proportions seemed reasonable in comparing with a recent study Priorities for Local AIDS Control Efforts II (PLACE II). Compared with using a single data source, we observed increased precision and better geographic coverage.

CONCLUSIONS

We illustrate how size estimates from different data sources may be combined for prediction. Applying this approach to other subpopulations in Malawi and to countries where size estimate data are lacking can ultimately inform national modeling processes and estimate the distribution of risks and priorities for HIV prevention and treatment programs.

Estimating the population size of female sex workers and transgender women in Sri Lanka

We implemented population size estimation of female sex workers (FSW) and transgender women (TGW) in Sri Lanka in 2018 using several approaches (geographical mapping, service and unique object multiplier and a modified Delphi method during the stakeholder consensus meeting). Mapping was done in 49 randomly selected Divisional Secretariats, which provided a basis for extrapolation of size estimates to the national level. Two types of adjustments were applied on the mean (minimum-maximum) population estimate obtained during mapping: (1) an adjustment for mobility to reduce double counting of FSW and TGW frequenting multiple spots, obtained during mapping; (2) an adjustment for “a hidden population”, obtained from surveys among FSW and TGW. For the multiplier method, we used data from services of non-governmental organisations that FSW and TGW were in contact with, and surveys based on respondent-driven sampling. Surveys were carried out in the cities of Colombo (FSW, TGW), Kandy (FSW), Galle (FSW) and Jaffna (TGW). We estimated that there are 30,000 FSWs in Sri Lanka, with a plausible range of 20,000–35,000, which implies a prevalence of FSW of 0.56% (0.37–0.65%) among adult females. This study provided baseline estimates of 2,200 TGW in the country, with a plausible range of 2,000–3,500, which is 0.04% (0.04–0.07%) of adult male population. Our estimates of the proportional contribution of the FSW and TGW populations among the adult population in Sri Lanka are consistent with the The Joint United Nations Programme on HIV/AIDS (UNAIDS) recommended estimates for Asia and the Pacific. The results provide an important point for macro- and micro-level planning of HIV services, allocating programme resources and assessing programme coverage and quality.

The size estimation of injection drug users (IDUs) using the network scale-up method (NSUM) in Iranshahr, Iran

Background: The size estimation of key populations is a necessary part of surveillance systems to access global human immunodeficiency virus (HIV) infection. In this study, the NSU method was used to estimate injection drug users (IDUs). Methods: NSU method was performed on 1000 individuals in Iranshahr province with street-based sampling from 2016 to 2017. A questionnaire comprising items on demographic information and items measuring the network size of participants about IDUs was administered. The estimated size was adjusted for transmission error and barrier effect with PF and VF factors. The relationship between knowing IDUs and demographic variables was assessed using logistic regression. All analyses were performed in SPSS 19 and Microsoft Excel. Results: In this study, 500 men and 500 women were included. The average age (standard deviation) of the participants was 29.6 (7.8) years. IDUs were estimated at 1263 per 100 000 population of Iranshahr in Sistan and Baluchestan province, Iran. The estimated size was 7.5 times more in men than in women (2766 vs 364). Moreover, the highest estimated size belonged to the population of 18- 30-year-olds (1187). Sex and education level had significant relationships with knowing IDUs (p<0.001). Conclusion: To improve preventive programs, the number of outreach teams must be increased to have access to IDUs, educate them, and upgrade the coverage of harm-reduction services. According to cultural considerations and the illegal nature of injection drug use, social mobilization is essential to reduce the stigma.

Estimating and projecting the number of new HIV diagnoses and incidence in Spectrum's case surveillance and vital registration tool

Supplemental Digital Content is available in the text

Objective:

The Joint United Nations Programme on HIV/AIDS-supported Spectrum software package is used by most countries worldwide to monitor the HIV epidemic. In Spectrum, HIV incidence trends among adults (aged 15–49 years) are derived by either fitting to seroprevalence surveillance and survey data or generating curves consistent with case surveillance and vital registration data, such as historical trends in the number of newly diagnosed infections or AIDS-related deaths. This article describes development and application of the case surveillance and vital registration (CSAVR) tool for the 2019 estimate round.

Methods:

Incidence in CSAVR is either estimated directly using single logistic, double logistic, or spline functions, or indirectly via the ‘r-logistic’ model, which represents the (log-transformed) per-capita transmission rate using a logistic function. The propensity to get diagnosed is assumed to be monotonic, following a Gamma cumulative distribution function and proportional to mortality as a function of time since infection. Model parameters are estimated from a combination of historical surveillance data on newly reported HIV cases, mean CD4⁺ at HIV diagnosis and estimates of AIDS-related deaths from vital registration systems. Bayesian calibration is used to identify the best fitting incidence trend and uncertainty bounds.

Results:

We used CSAVR to estimate HIV incidence, number of new diagnoses, mean CD4⁺ at diagnosis and the proportion undiagnosed in 31 European, Latin American, Middle Eastern, and Asian-Pacific countries. The spline model appeared to provide the best fit in most countries (45%), followed by the r-logistic (25%), double logistic (25%), and single logistic models. The proportion of HIV-positive people who knew their status increased from about 0.31 [interquartile range (IQR): 0.10–0.45] in 1990 to about 0.77 (IQR: 0.50–0.89) in 2017. The mean CD4⁺ at diagnosis appeared to be stable, at around 410 cells/μl (IQR: 224–567) in 1990 and 373 cells/μl (IQR: 174–475) by 2017.

Conclusion:

Robust case surveillance and vital registration data are routinely available in many middle-income and high-income countries while HIV seroprevalence surveillance and survey data may be scarce. In these countries, CSAVR offers a simpler, improved approach to estimating and projecting trends in both HIV incidence and knowledge of HIV status.

Population Size Estimations Among Hidden Populations Using Respondent-Driven Sampling Surveys: Case Studies From Armenia

Background

Estimates of the sizes of hidden populations, including female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID), are essential for understanding the magnitude of vulnerabilities, health care needs, risk behaviors, and HIV and other infections.

Objective

This article advances the successive sampling-population size estimation (SS-PSE) method by examining the performance of a modification allowing visibility to be jointly modeled with population size in the context of 15 datasets. Datasets are from respondent-driven sampling (RDS) surveys of FSW, MSM, and PWID from three cities in Armenia. We compare and evaluate the accuracy of our imputed visibility population size estimates to those found for the same populations through other unpublished methods. We then suggest questions that are useful for eliciting information needed to compute SS-PSE and provide guidelines and caveats to improve the implementation of SS-PSE for real data.

Methods

SS-PSE approximates the RDS sampling mechanism via the successive sampling model and uses the order of selection of the sample to provide information on the distribution of network sizes over the population members. We incorporate visibility imputation, a measure of a person’s propensity to participate in the study, given that inclusion probabilities for RDS are unknown and social network sizes, often used as a proxy for inclusion probability, are subject to measurement errors from self-reported study data.

Results

FSW in Yerevan (2012, 2016) and Vanadzor (2016) as well as PWID in Yerevan (2014), Gyumri (2016), and Vanadzor (2016) had great fits with prior estimations. The MSM populations in all three cities had inconsistencies with expert prior values. The maximum low prior value was larger than the minimum high prior value, making a great fit impossible. One possible explanation is the inclusion of transgender individuals in the MSM populations during these studies. There could be differences between what experts perceive as the size of the population, based on who is an eligible member of that population, and what members of the population perceive. There could also be inconsistencies among different study participants, as some may include transgender individuals in their accounting of personal network size, while others may not. Because of these difficulties, the transgender population was split apart from the MSM population for the 2018 study.

Conclusions

Prior estimations from expert opinions may not always be accurate. RDS surveys should be assessed to ensure that they have met all of the assumptions, that variables have reached convergence, and that the network structure of the population does not have bottlenecks. We recommend that SS-PSE be used in conjunction with other population size estimations commonly used in RDS, as well as results of other years of SS-PSE, to ensure generation of the most accurate size estimation.

Bayesian Estimation of MSM Population Size in Côte d'Ivoire

Côte d'Ivoire has among the most generalized HIV epidemics in West Africa with an estimated half million people living with HIV. Across West Africa, key populations, including gay men and other men who have sex with men (MSM), are often disproportionately burdened with HIV due to specific acquisition and transmission risks. Quantifying population sizes of MSM at the subnational level is critical to ensuring evidence-based decisions regarding the scale and content of HIV prevention interventions. While survey-based direct estimates of MSM numbers are available in a few urban centers across Côte d'Ivoire, no data on MSM population size exists in other areas without any community group infrastructure to facilitate sufficient access to communities of MSM. The data are used in a Bayesian regression setup to produce estimates of the numbers of MSM in areas of Côte d'Ivoire prioritized in the HIV response. Our hierarchical model imputes missing covariates using geo-spatial information and allows for proper uncertainty quantification leading to confidence bounds for predicted MSM population size estimates. This process provided population size estimates where there are no empirical data, to guide the prioritization of further collection of empirical data on MSM and inform evidence-based scaling of HIV prevention and treatment programs for MSM across Côte d'Ivoire.

Mapping and size estimates of female sex workers in Cameroon: Toward informed policy for design and implementation in the national HIV program

Background

Due to high HIV prevalence among Female Sex Workers (FSWs) in Cameroon (36.5%), this population is especially vulnerable to HIV acquisition and transmission nationwide. Though being prioritized in the national HIV response, it would be relevant to generate statistics on the number of FSWs in order to guide HIV interventions among FSWs. Our objective was to estimate the size of FSWs within hotspots of Cameroon.

Methods

A cross-sectional study was conducted from September-November 2015 in selected cities in Cameroon: Bafoussam, Bamenda, Bertoua, Buea, Douala, Kribi, Limbé, and Yaoundé. A programmatic mapping was used, consisting of interviews with secondary key informants (KI) to identify hotspots of FSWs and their respective estimated numbers. Validation of size estimates was done by interviews with FSW at each hotspot. Size estimations in the councils mapped were extended to others not mapped using a Poisson regression model.

Results

A total of 2,194 hotspots were identified: Douala (760), Yaoundé (622), Bamenda (263), Bafoussam (194), Kribi (154), Bertoua (140), Limbé (35), and Buea (26). The estimated total number (range) of FSWs was 21,124 (16,079–26,170), distributed per city as follows: Douala 7,557 (5,550–9,364), Yaoundé 6,596 (4,712–8,480), Bafoussam 2,458 (1,994–2,923), Bamenda 1,975 (1,605–2,345), Kribi 1,121 (832–1,408), Bertoua 1,044 (891–1,198), Buea 225 (185–266), and Limbé 148 (110–148). The variability of estimates among cities was also observed within the councils of each city. The national predicted estimate of FSW population was 112,580 (103,436–121,723), covering all councils of Cameroon. An estimate of 1.91% (112,580/5,881,526; 0.47%-3.36%) adult female population in Cameroon could be sex workers.

Conclusion

There are considerable numbers of FSW in major cities in Cameroon. There is a need to prioritize interventions for HIV prevention toward this population in order to limit the burden of HIV sexual transmission nationwide.

Estimating Sizes of Key Populations at the National Level: Considerations for Study Design and Analysis

Background:

National estimates of the sizes of key populations, including female sex workers, men who have sex with men, and transgender women are critical to inform national and international responses to the HIV pandemic. However, epidemiologic studies typically provide size estimates for only limited high priority geographic areas. This article illustrates a two-stage approach to obtain a national key population size estimate in the Dominican Republic using available estimates and publicly available contextual information.

Methods:

Available estimates of key population size in priority areas were augmented with targeted additional data collection in other areas. To combine information from data collected at each stage, we used statistical methods for handling missing data, including inverse probability weights, multiple imputation, and augmented inverse probability weights.

Results:

Using the augmented inverse probability weighting approach, which provides some protection against parametric model misspecification, we estimated that 3.7% (95% CI = 2.9, 4.7) of the total population of women in the Dominican Republic between the ages of 15 and 49 years were engaged in sex work, 1.2% (95% CI = 1.1, 1.3) of men aged 15–49 had sex with other men, and 0.19% (95% CI = 0.17, 0.21) of people assigned the male sex at birth were transgender.

Conclusions:

Viewing the size estimation of key populations as a missing data problem provides a framework for articulating and evaluating the assumptions necessary to obtain a national size estimate. In addition, this paradigm allows use of methods for missing data familiar to epidemiologists.

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

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.

A review of methods to estimate the visibility factor for bias correction in network scale-up studies

Network scale-up is an indirect size estimation method, in which participants are questioned on sensitive behaviors of their social network members. Therefore, the visibility of the behavior affects the replies and estimates. Many attempts to estimate visibility have been made. The aims of this study were to review the main methods used to address visibility and to provide a summary of reported visibility factors (VFs) across populations. We systematically searched relevant databases and Google. In total, 15 studies and reports that calculated VFs were found. VF calculation studies have been applied in 9 countries, mostly in East Asia and Eastern Europe. The methods applied were expert opinion, comparison of NSU with another method, the game of contacts, social respect, and the coming-out rate. The VF has been calculated for heavy drug users, people who inject drugs (PWID), female sex workers (FSWs) and their clients, male who have sex with male (MSM), alcohol and methamphetamine users, and those who have experienced extra-/pre-marital sex and abortion. The VF varied from 1.4% in Japan to 52.0% in China for MSM; from 34.0% in Ukraine to 111.0% in China for FSWs; and from 12.0% among Iranian students to 57.0% in Ukraine for PWID. Our review revealed that VF estimates were heterogeneous, and were not available for most settings, in particular the Middle East and North Africa region, except Iran. More concrete methodologies to estimate the VF are required.

Study design and the estimation of the size of key populations at risk of HIV: lessons from Viet Nam

BACKGROUND

Estimation of the size of populations at risk of HIV is a key activity in the surveillance of the HIV epidemic. The existing framework for considering future research needs may provide decision-makers with a basis for a fair process of deciding on the methods of the estimation of the size of key populations at risk of HIV. This study explores the extent to which stakeholders involved with population size estimation agree with this framework, and thus, the study updates the framework.

METHODS

We conducted 16 in-depth interviews with key informants from city and provincial governments, NGOs, research institutes, and the community of people at risk of HIV. Transcripts were analyzed and reviewed for significant statements pertaining to criteria. Variations and agreement around criteria were analyzed, and emerging criteria were validated against the existing framework.

RESULTS

Eleven themes emerged which are relevant to the estimation of the size of populations at risk of HIV in Viet Nam. Findings on missing criteria, inclusive participation, community perspectives and conflicting weight and direction of criteria provide insights for an improved framework for the prioritization of population size estimation methods.

CONCLUSIONS

The findings suggest that the exclusion of community members from decision-making on population size estimation methods in Viet Nam may affect the validity, use, and efficiency of the evidence generated. However, a wider group of decision-makers, including community members among others, may introduce diverse definitions, weight and direction of criteria. Although findings here may not apply to every country with a transitioning economy or to every emerging epidemic, the principles of fair decision-making, value of community participation in decision-making and the expected challenges faced, merit consideration in every situation.

Measuring Sexual Behavior Stigma to Inform Effective HIV Prevention and Treatment Programs for Key Populations

BACKGROUND

The levels of coverage of human immunodeficiency virus (HIV) treatment and prevention services needed to change the trajectory of the HIV epidemic among key populations, including gay men and other men who have sex with men (MSM) and sex workers, have consistently been shown to be limited by stigma.

OBJECTIVE

The aim of this study was to propose an agenda for the goals and approaches of a sexual behavior stigma surveillance effort for key populations, with a focus on collecting surveillance data from 4 groups: (1) members of key population groups themselves (regardless of HIV status), (2) people living with HIV (PLHIV) who are also members of key populations, (3) members of nonkey populations, and (4) health workers.

METHODS

We discuss strengths and weaknesses of measuring multiple different types of stigma including perceived, anticipated, experienced, perpetrated, internalized, and intersecting stigma as measured among key populations themselves, as well as attitudes or beliefs about key populations as measured among other groups.

RESULTS

With the increasing recognition of the importance of stigma, consistent and validated stigma metrics for key populations are needed to monitor trends and guide immediate action. Evidence-based stigma interventions may ultimately be the key to overcoming the barriers to coverage and retention in life-saving antiretroviral-based HIV prevention and treatment programs for key populations.

CONCLUSIONS

Moving forward necessitates the integration of validated stigma scales in routine HIV surveillance efforts, as well as HIV epidemiologic and intervention studies focused on key populations, as a means of tracking progress toward a more efficient and impactful HIV response.

Improvements in Spectrum's fit to program data tool

OBJECTIVE

The Joint United Nations Program on HIV/AIDS-supported Spectrum software package (Glastonbury, Connecticut, USA) is used by most countries worldwide to monitor the HIV epidemic. In Spectrum, HIV incidence trends among adults (aged 15-49 years) are derived by either fitting to seroprevalence surveillance and survey data or generating curves consistent with program and vital registration data, such as historical trends in the number of newly diagnosed infections or people living with HIV and AIDS related deaths. This article describes development and application of the fit to program data (FPD) tool in Joint United Nations Program on HIV/AIDS' 2016 estimates round.

METHODS

In the FPD tool, HIV incidence trends are described as a simple or double logistic function. Function parameters are estimated from historical program data on newly reported HIV cases, people living with HIV or AIDS-related deaths. Inputs can be adjusted for proportions undiagnosed or misclassified deaths. Maximum likelihood estimation or minimum chi-squared distance methods are used to identify the best fitting curve. Asymptotic properties of the estimators from these fits are used to estimate uncertainty.

RESULTS

The FPD tool was used to fit incidence for 62 countries in 2016. Maximum likelihood and minimum chi-squared distance methods gave similar results. A double logistic curve adequately described observed trends in all but four countries where a simple logistic curve performed better.

CONCLUSION

Robust HIV-related program and vital registration data are routinely available in many middle-income and high-income countries, whereas HIV seroprevalence surveillance and survey data may be scarce. In these countries, the FPD tool offers a simpler, improved approach to estimating HIV incidence trends.

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

Objective

To assess the availability and quality of population size estimations of female sex workers (FSW), men who have sex with men (MSM), people who inject drug (PWID) and transgender women.

Methods

Size estimation data since 2010 were retrieved from global reporting databases, Global Fund grant application documents, and the peer-reviewed and grey literature. Overall quality and availability were assessed against a defined set of criteria, including estimation methods, geographic coverage, and extrapolation approaches. Estimates were compositely categorized into ‘nationally adequate’, ‘nationally inadequate but locally adequate’, ‘documented but inadequate methods’, ‘undocumented or untimely’ and ‘no data.’

Findings

Of 140 countries assessed, 41 did not report any estimates since 2010. Among 99 countries with at least one estimate, 38 were categorized as having nationally adequate estimates and 30 as having nationally inadequate but locally adequate estimates. Multiplier, capture-recapture, census and enumeration, and programmatic mapping were the most commonly used methods. Most countries relied on only one estimate for a given population while about half of all reports included national estimates. A variety of approaches were applied to extrapolate from sites-level numbers to national estimates in two-thirds of countries.

Conclusions

Size estimates for FSW, MSM, PWID and transgender women are increasingly available but quality varies widely. The different approaches present challenges for data use in design, implementation and evaluation of programs for these populations in half of the countries assessed. Guidance should be further developed to recommend: a) applying multiple estimation methods; b) estimating size for a minimum number of sites; and, c) documenting extrapolation approaches.