“Understanding differences in HIV/HCV prevalence according to differentiated risk behaviors in a sample of PWID in rural Puerto Rico.” Journal of Harm Reduction 13 (10): 1-7.
Roberto Abadie, Melissa Welch-Lazoritz, Camila Gelpi-Acosta, Juan Carlos Reyes, Ric Curtis, Kirk Dombrowski
Blood contained in needles and injection equipment has been identified as a vector for HIV and HCV transmission among people who inject drugs (PWID). Yet, there is often a wide discrepancy in prevalence for both viruses. While microbiological differences between viruses influence prevalence, other variables associated with the way drugs are acquired and used, also play a role.
Respondent-driven sampling (RDS) methods recruited a sample of 315 current intravenous drug users in rural Puerto Rico. Information about type and frequency of use, HIV and HVC risk behaviors (sharing needles, cookers, cotton, and water), sexual behaviors, and alcohol use was collected. HIV and HCV statuses were assessed via rapid antibody tests. T tests compare means of participants who tested positive (reactive) to those who tested negative. Logistic regression analyses were used to validate the association of the risk factors involved.
Tests showed a significant difference in HIV (6 %) and HCV (78.4 %) prevalence among a population of current PWID. The main risk behaviors in HCV transmission are the sharing of injection “works”, (e.g., cookers, cotton, and water). Sharing works occurred more than twice as often as the sharing of needles, and HCV+ and HCV? individuals reported the same needle sharing habits.
“Improving the Network Scale-Up Estimator: Incorporating Means of Sums, Recursive Back Estimation, and Sampling Weights.” PLoSOne 10(12): e0143406.
Patrick Habecker, Kirk Dombrowski, and Bilal Khan
Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM) provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations) via traditional survey tools such as telephone or mail surveys—by asking a representative sample to estimate the number of people they know who are members of such a “hidden” subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation “trimming” to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights.
“Predictors of police reporting among Hispanic immigrant victims of violence.” Race and Justice 5(3): 235-258. 2015
Dane Hautala, Kirk Dombrowski, and Anthony Marcus.
The purpose of this study was to examine predictors of police reporting among Hispanic immigrant victims of violence. A sample of 127 Hispanic immigrants was generated through a chain-referral procedure in the city of Hempstead, New York. Participants were asked about their most recent victimization experiences, and detailed information was collected on up to three incidents. The analyses were based on a total of 214 separate victimization incidents, one third of which were reported to the police. Logistic regression analyses indicated that serious injury, multiple-victim incidents, and perceptions of discrimination increase the odds of a police report. Moreover, incidents involving a Black primary assailant were less likely to be reported to the police than incidents involving an assailant perceived to be of Hispanic origin. Supplementary analyses suggested that this latter relationship may be contingent upon the type of crime and the victim’s relationship with the assailant. At the policy level, these findings call into question assumptions about very recent immigrants being too socially isolated and distrustful of law enforcement to sustain robust reporting levels, as well as pointing to encouraging possibilities for productive engagement between police and Hispanic immigrant populations.
Reducing Recurrent Homelessness: Some Methodological Lessons from the Critical Time Intervention Experiment
Anthony Marcus Ph.D
City University of New York
Social Networks Research Group
It is well established that quantitative surveys and qualitative interviews can easily complement each other. However, as one moves deeper into their respective “territories”, towards randomized control trials and ethnography the potential for misunderstanding increases. This article examines the tensions and possibilities in this relationship through the first ethnographic assessment of Critical Time Intervention (CTI), a randomized clinical trial of an experiment in reducing homelessness among mentally ill men in New York City in the early 1990s. CTI has had a decade of positive quantitative assessments, praise from President George W. Bush’s 2003 New Freedom Commission on Mental Health, and replication attempts, but its ethnographic data has not been used in evaluation. This article seeks to correct this omission and reveal some of the broader challenges to creating a qualitative/quantitative synthesis.
PI: Holly Hagan (NYU)
Investigators: Bilal Khan and Kirk Dombrowski
Hepatitis C virus (HCV)-related deaths now exceed HIV-related deaths in the US. Throughout the world, HCV is hyperendemic in people who inject drugs (PWID). New outbreaks of acute HCV infection are unfolding in HIV-positive men who have sex with men (MSM) and in 15-24 year olds who have transitioned from abuse of prescription opioids to illicit opiate injection. In patients with chronic HCV infection, 20-25% will develop liver disease which may manifest as cirrhosis, liver failure or hepatocellular carcinoma (HCC). The prognosis for HCC is extremely poor, and HCV is the chief etiologic agent for this type of cancer. Recent discoveries in HCV prevention and treatment provide a great opportunity to reverse the trend toward increasing rates of HCV, HCV/HIV co-infection, and HCC. This study will use the methods of Implementation Science – research synthesis, mathematical modeling and simulation, and comparative effectiveness analyses – to determine how best to constitute a portfolio of interventions for the prevention and control of HCV and its consequences while taking into account limited resources and underlying epidemiologic and social network features. A dissemination plan will make extensive use of technology, including social media, and guidance from key stakeholders. These are our specific aims:
1. Synthesize evidence characterizing a) transition from misuse of prescription opioids to drug injection, b) HCV epidemiology and prevention for PWID and HIV+ MSM, and c) progression and treatment of HCV disease in these two groups, to derive best estimates to populate our HCV natural history and transmission models.
2. Use agent-based modeling to estimate the effects of scale-up of individual and combined prevention- and treatment-related interventions on HCV transmission and natural history in PWID and HIV+MSM.
3. Determine the combination of interventions for particular budget and epidemiologic scenarios that a) minimizes acute and chronic HCV infections, including HIV/HCV co-infection, b) prevents the greatest number of cases of HCV-related HCC and other serious sequelae, c) maximizes life expectancy and quality-adjusted life expectancy and d) reduces health disparities.
4. In collaboration with our Dissemination Advisory Board, apply an integrated knowledge-exchange approach to providing our target audiences (policymakers, public health and harm reduction practice communities, PWID and HIV+MSM) with the knowledge and tools to implement evidence-based HCV control strategies or reduce personal risk of infection and its consequences.
The broad objective of this study is to provide an evidence base to guide allocation of scarce public resources in the US and other countries where HCV is principally transmitted among PWID. This will be accomplished by synthesizing, modeling and translating very recent developments in HCV epidemiology, prevention and treatment into practical tools to optimize population health.