Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques

The first population size estimation of transgender and non-binary people in Georgia

Purpose

Accurate data on the number of transgender and non-binary people are essential for the effectiveness of planning and implementation of transgender services, as well as for advocacy, but these data are insufficient. Our goal in this study was to estimate the number of transgender people in Georgia and compare it with estimations in other Eastern European and Central Asian (EECA) countries.

Methods

We used a variety of methodologies, including the mobile/web app multiplier, service multiplier, and network-based capture-recapture (Telefunken) methods, which all were included in a survey of 100 transgender people. A final estimation was obtained using the Anchored Multiplier method. We also review the existing research on estimating transgender and non-binary population sizes in EECA countries.

Results

The estimation final value of transgender and non-binary people in Georgia was 0.06 [0.05-0.07%] of the total adult (18-54 years) population of the country or 1,044 [870-1,219].

Conclusion

Our transgender and non-binary population size estimates in Georgia are in line with those in other EECA countries. These estimates can offer useful information for planning and assessing trans specific services, including HIV prevention programs at the national level. Furthermore, we believe that our findings will close the information gap regarding regional estimates of transgender and non-binary populations.

Dependence-Robust Confidence Intervals for Capture-Recapture Surveys

Capture-recapture (CRC) surveys are used to estimate the size of a population whose members cannot be enumerated directly. CRC surveys have been used to estimate the number of Coronavirus Disease 2019 (COVID-19) infections, people who use drugs, sex workers, conflict casualties, and trafficking victims. When k-capture samples are obtained, counts of unit captures in subsets of samples are represented naturally by a 2 k contingency table in which one element-the number of individuals appearing in none of the samples-remains unobserved. In the absence of additional assumptions, the population size is not identifiable (i.e., point identified). Stringent assumptions about the dependence between samples are often used to achieve point identification. However, real-world CRC surveys often use convenience samples in which the assumed dependence cannot be guaranteed, and population size estimates under these assumptions may lack empirical credibility. In this work, we apply the theory of partial identification to show that weak assumptions or qualitative knowledge about the nature of dependence between samples can be used to characterize a nontrivial confidence set for the true population size. We construct confidence sets under bounds on pairwise capture probabilities using two methods: test inversion bootstrap confidence intervals and profile likelihood confidence intervals. Simulation results demonstrate well-calibrated confidence sets for each method. In an extensive real-world study, we apply the new methodology to the problem of using heterogeneous survey data to estimate the number of people who inject drugs in Brussels, Belgium.

Using Social Networks to Sample Migrants and Study the Complexity of Contemporary Immigration: An Evaluation Study

We test the effectiveness of a link-tracing sampling approach-network sampling with memory (NSM)-to recruit samples of rare immigrant populations with an application among Chinese immigrants in the Raleigh-Durham area of North Carolina. NSM uses the population network revealed by data from the survey to improve the efficiency of link-tracing sampling and has been shown to substantially reduce design effects in simulated sampling. Our goals are to (1) show that it is possible to recruit a probability sample of a locally rare immigrant group using NSM and achieve high response rates; (2) demonstrate the feasibility of the collection and benefits of new forms of network data that transcend kinship networks in existing surveys and can address unresolved questions about the role of social networks in migration decisions, the maintenance of transnationalism, and the process of social incorporation; and (3) test the accuracy of the NSM approach for recruiting immigrant samples by comparison with the American Community Survey. Our results indicate feasibility, high performance, cost-effectiveness, and accuracy of the NSM approach to sample immigrants for studies of local immigrant communities. This approach can also be extended to recruit multisite samples of immigrants at origin and destination.

Risks and Opportunities to Ensure Equity in the Application of Big Data Research in Public Health

The big data revolution presents an exciting frontier to expand public health research, broadening the scope of research and increasing the precision of answers. Despite these advances, scientists must be vigilant against also advancing potential harms toward marginalized communities. In this review, we provide examples in which big data applications have (unintentionally) perpetuated discriminatory practices, while also highlighting opportunities for big data applications to advance equity in public health. Here, big data is framed in the context of the five Vs (volume, velocity, veracity, variety, and value), and we propose a sixth V, virtuosity, which incorporates equity and justice frameworks. Analytic approaches to improving equity are presented using social computational big data, fairness in machine learning algorithms, medical claims data, and data augmentation as illustrations. Throughout, we emphasize the biasing influence of data absenteeism and positionality and conclude with recommendations for incorporating an equity lens into big data research.

Project BESPOKE (Integrated Bio-Behavioral Assessment of HIV and STI Among Young Tertiary Student Men Who Have Sex With Men in Nairobi, Kenya): A Respondent-Driven Sampling Survey Protocol

Introduction: Globally, men who have sex with men (MSM) are a key population for the human immunodeficiency virus (HIV) epidemic. Among MSM, young men who have sex with men (YMSM) are disproportionately affected by HIV and other sexually transmitted infections (STI). However, there is a dearth of research and interventions targeting HIV/STI prevention among YMSM. In Kenya, there is paucity of knowledge on the burden of HIV/STI and related factors among YMSM, including tertiary student men who have sex with men (TSMSM). The barriers TSMSM experience in accessing and utilizing health services in their learning institutions have seldom been explored. In the context of healthcare providers (HCP) working in tertiary institutions, little is known about their knowledge, attitudes, and practices toward providing services to TSMSM. Methods: The aims of the study are to: estimate prevalence and correlates of HIV/STI among TSMSM; estimate population size of TSMSM; explore experiences of TSMSM with access and utilization of health services; and assess HCP knowledge of, attitudes toward, and practices in provision of services to TSMSM. A mixed-methods approach will be used in three phases: Phase I-formative qualitative research will be conducted to understand TSMSM social networks, select "seeds", and explore strategies for implementing a respondent-driven sampling (RDS) survey. Interviews will be conducted with at least three staff who work in community based/non-governmental organizations (CBO/NGO) that serve MSM and at least 10 TSMSM. Phase II-an integrated bio-behavioral assessment (IBBA) will be conducted, where 200 TSMSM recruited by RDS will be offered HIV/STI testing, complete a behavioral survey, and provide information for population size estimation (PSE). Phase III-in-depth interviews will be held with 20 TSMSM selected from 200 TSMSM in phase II, to explore their experiences with access and utilization of healthcare services. Focus group discussions (FGD) will be conducted with HCP working in tertiary institutions to assess their knowledge of, attitudes toward, and practices in providing services to TSMSM. Data collection started in September 2020 and is expected to end by September 2021. Discussion: Findings from this study will be useful in informing HIV/STI prevention programming for TSMSM, by policy makers such the Kenyan ministries of health and education, tertiary education institutions, service providers, advocacy groups, and other interested stakeholders.

Privacy and Confidentiality Considerations for Collecting HIV Risk Network Data among Men who Have Sex with Men and Implications for Constructing Valid Risk Networks

Studies aiming to construct risk networks have historically collected network members' names, demographic characteristics and relational data (i.e., type, strength, duration, frequency of interaction, and HIV-related risk behaviors between the pair). Due to difficulties in constructing risk networks stemming from partner anonymity and the use of nicknames, some studies also collect network members' screen names, phone numbers, physical attributes, and scars/tattoos to assist with entity resolution. In-depth interviews with 20 men who have sex with men and transgender women in Kentucky assessed privacy/confidentiality concerns as well as accuracy/recall issues associated with providing these details. Most preferred providing alters' nicknames/first names only or a first name with the first letter of the last name. Many perceived screen names, phone numbers, and scars/tattoos to be too personal/identifying. Willingness to provide more detailed information varied by relationship type/strength, which could influence the validity of the resulting network.

Event-level patterns of methamphetamine and poly-drug use among millennial sexual minority men: The P18 Cohort Study

INTRODUCTION

Knowledge on methamphetamine use among a new generation of sexual minority men (SMM) is limited. This study describes the event-level patterns of methamphetamine use and characteristics of methamphetamine users across time among Millennial SMM emerging into adulthood.

METHODS

A prospective cohort study was conducted in two waves: 2009-2014 (Wave I) and 2014-2019 (Wave II) in the New York City metropolitan area. A total of 600 Millennial SMM ages 18-19 years were recruited for Wave I. A total of 665 SMM ages 22-23 years were recruited for Wave II, of which 41.2% (n = 274) were retained from Wave I. The Timeline Followback assessment was conducted every six months to record event-level drug use in the 30 days prior to the visit.

RESULTS

A total of 5.4% of participants of between the ages of 18-27 reported methamphetamine use throughout the study period. The average number of days of methamphetamine use was significantly higher among racial/ethnic minority men in Wave II (F = 4.34, p = 0.0029). We found methamphetamine use occurred more often on weekend days and same-day use of methamphetamine occurred most often with cannabis and gamma-hydroxybutyrate. Usage of methamphetamine was significantly greater among SMM in Wave II who by design were older than Wave I.

CONCLUSION

We have identified differences in methamphetamine use by race/ethnicity. Weekend use and poly-drug use were common among methamphetamine-using SMM. Data indicate differential use in the population and that attempts to address this addictive behavior must be linked to other drug use and socialization among young SMM.

Estimating Hidden Population Sizes with Venue-based Sampling: Extensions of the Generalized Network Scale-up Estimator

BACKGROUND

Researchers use a variety of population size estimation methods to determine the sizes of key populations at elevated risk of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), an important step in quantifying epidemic impact, advocating for high-risk groups, and planning, implementing, and monitoring prevention, care, and treatment programs. Conventional procedures often use information about sample respondents' social network contacts to estimate the sizes of key populations of interest. A recent study proposes a generalized network scale-up method that combines two samples-a traditional sample of the general population and a link-tracing sample of the hidden population-and produces more accurate results with fewer assumptions than conventional approaches.

METHODS

We extended the generalized network scale-up method from link-tracing samples to samples collected with venue-based sampling designs popular in sampling key populations at risk of HIV. Our method obviates the need for a traditional sample of the general population, as long as the size of the venue-attending population is approximately known. We tested the venue-based generalized network scale-up method in a comprehensive simulation evaluation framework.

RESULTS

The venue-based generalized network scale-up method provided accurate and efficient estimates of key population sizes, even when few members of the key population were sampled, yielding average biases below ±6% except when false-positive reporting error is high. It relies on limited assumptions and, in our tests, was robust to numerous threats to inference.

CONCLUSIONS

Key population size estimation is vital to the successful implementation of efforts to combat HIV/AIDS. Venue-based network scale-up approaches offer another tool that researchers and policymakers can apply to these problems.

"You Never Know What You're Getting": Opioid Users' Perceptions of Fentanyl in Southwest Pennsylvania

BACKGROUND

Urban areas in the United States have experienced a dramatic surge in fentanyl overdose deaths since 2014, a trend affecting both larger and smaller metropolitan areas. Encompassing only 1.2 million residents, Allegheny County, Pennsylvania, nevertheless saw 412 fentanyl-involved deaths in 2016, a number surpassed only by New York City and Cook County (Chicago), Illinois.

OBJECTIVES

This article seeks to describe opioid users' perceptions of fentanyl in Allegheny and three adjacent counties; it further considers how the drug's emergence shapes some users' market behaviors and consumption practices.

METHODS

This article reports on qualitative interview data (N = 30) collected as part of a larger, multi-phase, mixed methods study (N = 125) among individuals reporting past-year prescription opioid misuse or heroin use in four southwest Pennsylvania Counties.

RESULTS

Most interviewees reported past-year suspected exposure to fentanyl, and many reported suffering or seeing suspected fentanyl overdoses. Where roughly one-third reported strategies for avoiding fentanyl, a small group of interviewees identified advantages to fentanyl, while still acknowledging its associated risks. Conclusions/Importance: Given users' diverse opinions around fentanyl, the distribution of fentanyl test strips may represent an effective response to the current crisis.

Network Research Experiences in New York and Eastern Europe: Lessons for the Southern US in Understanding HIV Transmission Dynamics

PURPOSE

This paper presents an overview of different kinds of risk and social network methods and the kinds of research questions each can address.

RECENT FINDINGS

It also reviews what network research has discovered about how network characteristics are associated with HIV and other infections, risk behaviors, preventive behaviors, and care, and discusses some ways in which network-based public health interventions have been conducted. Based on this, risk and social network research and interventions seem both feasible and valuable for addressing the many public health and social problems raised by the widespread use of opioids in the US South.

One-step estimation of networked population size: Respondent-driven capture-recapture with anonymity

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section.

Rural and urban injection drug use in Puerto Rico: Network implications for human immunodeficiency virus and hepatitis C virus infection

Understanding the short- and long-term transmission dynamics of blood-borne illnesses in network contexts represents an important public health priority for people who inject drugs and the general population that surrounds them. The purpose of this article is to compare the risk networks of urban and rural people who inject drugs in Puerto Rico. In the current study, network characteristics are drawn from the sampling "trees" used to recruit participants to the study. We found that injection frequency is the only factor significantly related to clustering behavior among both urban and rural people who inject drugs.

Network Approaches to Substance Use and HIV/Hepatitis C Risk among Homeless Youth and Adult Women in the United States: A Review

During the United States economic recession of 2008-2011, the number of homeless and unstably housed people in the United States increased considerably. Homeless adult women and unaccompanied homeless youth make up the most marginal segments of this population. Because homeless individuals are a hard to reach population, research into these marginal groups has traditionally been a challenge for researchers interested in substance abuse and mental health. Network analysis techniques and research strategies offer means for dealing with traditional challenges such as missing sampling frames, variation in definitions of homelessness and study inclusion criteria, and enumeration/population estimation procedures. This review focuses on the need for, and recent steps toward, solutions to these problems that involve network science strategies for data collection and analysis. Research from a range of fields is reviewed and organized according to a new stress process framework aimed at understanding how homeless status interacts with issues related to substance abuse and mental health. Three types of network innovation are discussed: network scale-up methods, a network ecology approach to social resources, and the integration of network variables into the proposed stress process model of homeless substance abuse and mental health. By employing network methods and integrating these methods into existing models, research on homeless and unstably housed women and unaccompanied young people can address existing research challenges and promote more effective intervention and care programs.

Sampling Migrants from their Social Networks: The Demography and Social Organization of Chinese Migrants in Dar es Salaam, Tanzania

The streams of Chinese migration to Africa are growing in tandem with rising Chinese investments and trade flows in and to the African continent. In spite of the high profile of this phenomenon in the media, there are few rich and broad descriptions of Chinese communities in Africa. Reasons for this include the rarity of official statistics on foreign-born populations in African censuses, the absence of predefined sampling frames required to draw representative samples with conventional survey methods and difficulties to reach certain segments of this population. Here, we use a novel network-based approach, Network Sampling with Memory, which overcomes the challenges of sampling 'hidden' populations in the absence of a sampling frame, to recruit a sample of recent Chinese immigrants in Dar es Salaam, Tanzania and collect information on the demographic characteristics, migration histories and social ties of members of this sample. These data reveal a heterogeneous Chinese community composed of "state-led" migrants who come to Africa to work on projects undertaken by large Chinese state-owned enterprises and "independent" migrants who come on their own accord to engage in various types of business ventures. They offer a rich description of the demographic profile and social organization of this community, highlight key differences between the two categories of migrants and map the structure of the social ties linking them. We highlight needs for future research on inter-group differences in individual motivations for migration, economic activities, migration outcomes, expectations about future residence in Africa, social integration and relations with local communities.

Population Size Estimation of Men Who Have Sex with Men in Tbilisi, Georgia; Multiple Methods and Triangulation of Findings

INTRODUCTION

An accurate estimation of the population size of men who have sex with men (MSM) is critical to the success of HIV program planning and to monitoring of the response to epidemic as a whole, but is quite often missing. In this study, our aim was to estimate the population size of MSM in Tbilisi, Georgia and compare it with other estimates in the region.

METHODS

In the absence of a gold standard for estimating the population size of MSM, this study reports a range of methods, including network scale-up, mobile/web apps multiplier, service and unique object multiplier, network-based capture-recapture, Handcock RDS-based and Wisdom of Crowds methods. To apply all these methods, two surveys were conducted: first, a household survey among 1,015 adults from the general population, and second, a respondent driven sample of 210 MSM. We also conducted a literature review of MSM size estimation in Eastern European and Central Asian countries.

RESULTS

The median population size of MSM generated from all previously mentioned methods was estimated to be 5,100 (95% Confidence Interval (CI): 3,243~9,088). This corresponds to 1.42% (95%CI: 0.9%~2.53%) of the adult male population in Tbilisi.

CONCLUSION

Our size estimates of the MSM population (1.42% (95%CI: 0.9%~2.53%) of the adult male population in Tbilisi) fall within ranges reported in other Eastern European and Central Asian countries. These estimates can provide valuable information for country level HIV prevention program planning and evaluation. Furthermore, we believe, that our results will narrow the gap in data availability on the estimates of the population size of MSM in the region.

Boundary conditions of methamphetamine craving

Methamphetamine use has increased significantly and become a global health concern. Craving is known to predict methamphetamine use and relapse following abstinence. Some have suggested that cravings are automatic, generalized, and uncontrollable, but experimental work addressing these claims is lacking. In 2 exploratory studies, we tested the boundary conditions of methamphetamine craving by asking: (a) is craving specific to users' preferred route of administration?, and (b) can craving be regulated by cognitive strategies? Two groups of methamphetamine users were recruited. In Study 1, participants were grouped by their preferred route of administration (intranasal vs. smoking), and rated their craving in response to photographs and movies depicting methamphetamine use (via the intranasal vs. smoking route). In Study 2, methamphetamine smokers implemented cognitive regulation strategies while viewing photographs depicting methamphetamine smoking. Strategies involved either focusing on the positive aspects of smoking methamphetamine or the negative consequences of doing so-the latter strategy based on treatment protocols for addiction. In Study 1, we found a significant interaction between group and route of administration, such that participants who preferred to smoke methamphetamine reported significantly stronger craving for smoking stimuli, whereas those who preferred the intranasal route reported stronger craving for intranasal stimuli. In Study 2, participants reported significantly lower craving when focusing on the negative consequences associated with methamphetamine use. Taken together, these findings suggest that strength of craving for methamphetamine is moderated by users' route of administration and can be reduced by cognitive strategies. This has important theoretical, methodological, and clinical implications.

Application of Network Scale Up Method in the Estimation of Population Size for Men Who Have Sex with Men in Shanghai, China

BACKGROUND

Men who have sex with men (MSM) are at high risk of HIV infection. For developing proper interventions, it is important to know the size of MSM population. However, size estimation of MSM populations is still a significant public health challenge due to high cost, hard to reach and stigma associated with the population.

OBJECTIVES

We aimed to estimate the social network size (c value) in general population and the size of MSM population in Shanghai, China by using the net work scale-up method.

METHODS

A multistage random sampling was used to recruit participants aged from 18 to 60 years who had lived in Shanghai for at least 6 months. The "known population method" with adjustment of backward estimation and regression model was applied to estimate the c value. And the MSM population size was further estimated using an adjusted c value taking into account for the transmission effect through social respect level towards MSM.

RESULTS

A total of 4017 participants were contacted for an interview, and 3907 participants met the inclusion criterion. The social network size (c value) of participants was 236 after adjustment. The estimated size of MSM was 36354 (95% CI: 28489-44219) for the male Shanghaies aged 18 to 60 years, and the proportion of MSM among the total male population aged 18 to 60 years in Shanghai was 0.28%.

CONCLUSIONS

We employed the network scale-up method and used a wide range of data sources to estimate the size of MSM population in Shanghai, which is useful for HIV prevention and intervention among the target population.

Bi-national Social Networks and Assimilation: A Test of the Importance of Transnationalism

While the concept of transnationalism has gained widespread popularity among scholars as a way to describe immigrants' long-term maintenance of cross-border ties to their origin communities, critics have argued that the overall proportion of immigrants who engage in transnational behavior is low and that, as a result, transnationalism has little sustained effect on the process of immigrant adaptation and assimilation. In this paper, we argue that a key shortcoming in the current empirical debate on transnationalism is the lack of data on the social networks that connect migrants to each other and to non-migrants in communities of origin. To address this shortcoming, our analysis uses unique bi-national data on the social network connecting an immigrant sending community in Guanajuato, Mexico, to two destination areas in the United States. We test for the effect of respondents' positions in cross-border networks on their migration intentions and attitudes towards the United States using data on the opinions of their peers, their participation in cross border and local communication networks, and their structural position in the network. The results indicate qualified empirical support for a network-based model of transnationalism; in the U.S. sample we find evidence of network clustering consistent with peer effects, while in the Mexican sample we find evidence of the importance of cross-border communication with friends.

Estimating the size of key populations: current status and future possibilities

PURPOSE OF REVIEW

Estimation of key population sizes is essential for advocacy, program planning, and monitoring of HIV epidemics in these populations. A review of recent publications on population size estimation among key populations including MSM, people who inject drugs, and male and female sex workers was conducted to identify and assess current practices at the global level.

RECENT FINDINGS

Studies have used multiple methods including capture-recapture, service multiplier, and unique object multiplier. Other studies apply census and enumeration, often before implementation of a behavioral survey. Network scale-up is used infrequently. Newer methods or variations of existing size estimation methods have emerged that are applied solely within surveys.

SUMMARY

A range of size estimation methods is available. All methods rely on theoretical assumptions that are difficult to meet in practice, are logistically difficult to conduct, or have yet to be fully validated. Accurate and valid key population size estimates remain as necessary as they are challenging to undertake; the concurrent use of multiple methods may be justified to facilitate the triangulation and interpretation of the resulting estimates. Formative assessment can help inform the appropriateness and feasibility of different size estimation methods.

A reexamination of connectivity trends via exponential random graph modeling in two IDU risk networks

Patterns of risk in injecting drug user (IDU) networks have been a key focus of network approaches to HIV transmission histories. New network modeling techniques allow for a reexamination of these patterns with greater statistical accuracy and the comparative weighting of model elements. This paper describes the results of a reexamination of network data from the SFHR and P90 data sets using Exponential Random Graph Modeling. The results show that "transitive closure" is an important feature of IDU network topologies, and provides relative importance measures for race/ethnicity, age, gender, and number of risk partners in predicting risk relationships.

Network Sampling with Memory: A proposal for more efficient sampling from social networks

Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)-the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a "List" mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a "Search" mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS.