Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys

HIV and Hepatitis C Among People Who Inject Drugs in Memphis, Tennessee: an Intersectional Risk Environment Analysis of the Social Determinants of Health

BACKGROUND

The Southern US is confronting bourgeoning HIV and hepatitis C virus (HCV) epidemics among people who inject drugs (PWID), yet little is known about shared and unique risk factors across the region. We applied an intersectional risk environment framework to understand infectious disease outcomes for sub-groups of PWID that experience multiple axes of social marginalization related to racial and ethnic identity and social and economic vulnerability.

METHODS

HIV and HCV prevalence was estimated from the first iteration of the CDC's National HIV Behavioral Surveillance respondent driven sample of PWID in Shelby County, Tennessee in 2018. We ran adjusted multinomial models to test main and interaction effects of race/ethnicity and structural factors on the prevalence of a three-level outcome: HIV-only, HCV-only, and no infection.

RESULTS

A total of 564 PWID participated, 558 (99%) completed HIV testing, and 540 (96%) HCV testing. Thirty (5%) were HIV-positive, 224 (40%) HCV-positive, and less than 1% were co-infected. Descriptive differences by race/ethnicity and levels of structural vulnerability for HIV and HCV subpopulations were present; however, there was no evidence for statistical interaction. In the final main effects model, HIV status was positively associated with non-Hispanic Black identity (aRR 4.95, 95% CI 1.19, 20.6), whereas HCV status was associated with non-white identity (aRR 0.11 95% CI 0.07, 0.18). Factors associated with HCV infection were higher scores of structural vulnerability (aRR 2.19 95% CI 1.10, 4.35), and criminal legal involvement (aOR 1.99 95% CI 1.18, 3.37).

CONCLUSION

This is the first study to implement local population-based survey data to evaluate distinctive intersections of ethnic/racial and social factors associated with HIV and HCV status among PWID in the Memphis region. Findings come at an opportune time as harm reduction programs are in development in the South and shed light to the need for socially equitable race conscious resource investment.

Association between in-country migration and HIV infection among transgender women from northeastern Brazil: a respondent-driven sampling survey

BACKGROUND

Migration is common among transgender women (TGW), often driven by the desire to escape stigma, find acceptance, establish new connections, access body modifications, or enter new avenues of sex work. Given the heightened mobility of TGW, they are mostly vulnerable to human immunodeficiency virus (HIV) due to migration. This study aimed to evaluate the association between in-country migration and HIV infection among TGW in Northeast Brazil.

METHODS

The DIVAS was a cross-sectional, multicity study investigating risk behaviors and sexually transmitted infections (STI) among TGW in 2016-2017. A total of 864 TGW were recruited through respondent-driven sampling from three capital cities in Northeast Brazil. Logistic regression estimating odds ratios (OR) and 95% confidence intervals (CI) was used to assess the relationship between in-country migration and HIV infection.

RESULTS

The prevalence of HIV among TGW was 24.5%, 21.4% among those aged 18-34 and 36.1% among those ≥ 35 years old. In-country migration increased the odds of HIV infection among TGW aged 18-34 years (OR = 1.84; 95%CI:1.04-3.27) and even higher among those aged ≥ 35y old (OR = 3.08; 95%CI:1.18-8.04).

CONCLUSIONS

These data reinforce the pressing need for public health policies that provide comprehensive access and strategies for demand creation for HIV/AIDS prevention and care for TGW who are already highly vulnerable to infection.

Hidden population size estimation and diagnostics using two respondent-driven samples with applications in Armenia

Estimating the size of hidden populations is essential to understand the magnitude of social and healthcare needs, risk behaviors, and disease burden. However, due to the hidden nature of these populations, they are difficult to survey, and there are no gold standard size estimation methods. Many different methods and variations exist, and diagnostic tools are needed to help researchers assess method-specific assumptions as well as compare between methods. Further, because many necessary mathematical assumptions are unrealistic for real survey implementation, assessment of how robust methods are to deviations from the stated assumptions is essential. We describe diagnostics and assess the performance of a new population size estimation method, capture-recapture with successive sampling population size estimation (CR-SS-PSE), which we apply to data from 3 years of studies from three cities and three hidden populations in Armenia. CR-SS-PSE relies on data from two sequential respondent-driven sampling surveys and extends the successive sampling population size estimation (SS-PSE) framework by using the number of individuals in the overlap between the two surveys and a model for the successive sampling process to estimate population size. We demonstrate that CR-SS-PSE is more robust to violations of successive sampling assumptions than SS-PSE. Further, we compare the CR-SS-PSE estimates to population size estimations using other common methods, including unique object and service multipliers, wisdom of the crowd, and two-source capture-recapture to illustrate volatility across estimation methods.

Exploring Preventive Healthcare in a High-Risk Vulnerable Population

This study describes preventive care behaviors and explores opportunities to deliver preventive sexual healthcare to a high-risk vulnerable population. Data from the National HIV Behavioral Surveillance (NHBS) system high-risk heterosexuals (HET) cycle (2019) in Houston, Texas, was used to describe preventive care utilization and assess the relationship between healthcare utilization and sociodemographic characteristics. More than 47% reported having no usual source of healthcare, and 94.6% reported receiving no non-HIV STI testing in the past 12 months. Additionally, many sociodemographic factors were associated with healthcare utilization and having a usual source of healthcare. Future efforts should be targeted at increasing preventive healthcare utilization among high-risk vulnerable populations as well as implementing more preventive sexual healthcare services in the community health centers where these populations most frequently encounter healthcare.

Human social sensing is an untapped resource for computational social science

The ability to 'sense' the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others' experiences. Here we argue that, through the lens of computational social science, this ability can be used to advance research into human sociality. When strategically selected to represent a specific population of interest, human social sensors can help to describe and predict societal trends. In addition, their reports of how they experience their social worlds can help to build models of social dynamics that are constrained by the empirical reality of human social systems.