16 research outputs found
Seroprevalence of select bloodborne pathogens and associated risk behaviors among injection drug users in the Paso del Norte region of the United States – Mexico border
<p>Abstract</p> <p>Background</p> <p>The region situated where the borders of Mexico, Texas and New Mexico meet is known as 'Paso del Norte'. The Paso del Norte Collaborative was formed to study the seroprevalence of select pathogens and associated risk behaviors among injection drug users (IDUs) in the region.</p> <p>Methods</p> <p>Respondent-driven sampling (RDS) was used: 459 IDU participants included 204 from Mexico; 155 from Texas; and 100 from New Mexico. Each of the three sites used a standardized questionnaire that was verbally administered and testing was performed for select bloodborne infections.</p> <p>Results</p> <p>Participants were mostly male (87.4%) and Hispanic/Latino (84.7%) whose median age was 38. In Mexico, Texas and New Mexico, respectively: hepatitis B virus (HBV) was seen in 88.3%, 48.6% and 59.6% of participants; hepatitis C virus (HCV) in 98.7%, 76.4% and 80.0%; human immunodeficiency virus (HIV) in 2.1%, 10.0% and 1.0%; and syphilis in 4.0%, 9.9% and 3.0%. Heroin was the drug injected most often. More IDUs in New Mexico were aware of and used needle exchange programs compared with Texas and Mexico.</p> <p>Conclusion</p> <p>There was mixed success using RDS: it was more successfully applied after establishing good working relationships with IDU populations. Study findings included similarities and distinctions between the three sites that will be used to inform prevention interventions.</p
Respondent-Driven Sampling of Injection Drug Users in Two U.S.–Mexico Border Cities: Recruitment Dynamics and Impact on Estimates of HIV and Syphilis Prevalence
Respondent-driven sampling (RDS), a chain referral sampling approach, is increasingly used to recruit participants from hard-to-reach populations, such as injection drug users (IDUs). Using RDS, we recruited IDUs in Tijuana and Ciudad (Cd.) Juárez, two Mexican cities bordering San Diego, CA and El Paso, TX, respectively, and compared recruitment dynamics, reported network size, and estimates of HIV and syphilis prevalence. Between February and April 2005, we used RDS to recruit IDUs in Tijuana (15 seeds, 207 recruits) and Cd. Juárez (9 seeds, 197 recruits), Mexico for a cross-sectional study of behavioral and contextual factors associated with HIV, HCV and syphilis infections. All subjects provided informed consent, an anonymous interview, and a venous blood sample for serologic testing of HIV, HCV, HBV (Cd. Juárez only) and syphilis antibody. Log-linear models were used to analyze the association between the state of the recruiter and that of the recruitee in the referral chains, and population estimates of the presence of syphilis antibody were obtained, correcting for biased sampling using RDS-based estimators. Sampling of the targeted 200 recruits per city was achieved rapidly (2 months in Tijuana, 2 weeks in Cd. Juárez). After excluding seeds and missing data, the sample prevalence of HCV, HIV and syphilis were 96.6, 1.9 and 13.5% respectively in Tijuana, and 95.3, 4.1, and 2.7% respectively in Cd. Juárez (where HBV prevalence was 84.7%). Syphilis cases were clustered in recruitment trees. RDS-corrected estimates of syphilis antibody prevalence ranged from 12.8 to 26.8% in Tijuana and from 2.9 to 15.6% in Ciudad Juárez, depending on how recruitment patterns were modeled, and assumptions about how network size affected an individual’s probability of being included in the sample. RDS was an effective method to rapidly recruit IDUs in these cities. Although the frequency of HIV was low, syphilis prevalence was high, particularly in Tijuana. RDS-corrected estimates of syphilis prevalence were sensitive to model assumptions, suggesting that further validation of RDS is necessary
At the Borders, on the Edge: Use of Injected Methamphetamine in Tijuana and Ciudad Juarez, Mexico
Parsing social network survey data from hidden populations using stochastic context-free grammars.
BACKGROUND:Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a OhiddenO population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process. METHODOLOGY/PRINCIPAL FINDINGS:Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits. CONCLUSIONS:SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics
Prevalence of hepatitis C virus and HIV infection among injection drug users in two Mexican cities bordering the U.S Prevalencia de los virus de la hepatitis C y de la inmunodeficiencia humana entre usuarios de drogas intravenosas, en dos ciudades mexicanas fronterizas con los Estados Unidos de America
OBJECTIVE: To estimate the prevalence of the hepatitis C virus (HCV) and HIV infection and associated risk behaviors among injection drug users (IDUs) in two northern Mexican cities. MATERIAL AND METHODS: Between February and April 2005, IDUs were recruited in Tijuana (N=222) and Ciudad Juarez (N=206) using respondent-driven sampling (RDS), a chain referral sampling approach. Interviewer-administered questionnaires assessed drug-using behaviors during the prior six months. Venous blood was collected for immunoassays to detect HIV and HCV antibodies. For HIV, Western blot or immunofluorescence assay was used for confirmatory testing. Final HCV antibody prevalence was estimated using RDS adjustments. RESULTS: Overall, HCV and HIV prevalence was 96.0% and 2.8%, respectively, and was similar in both cities. Most IDUs (87.5%) reported passing on their used injection equipment to others, and 85.9% had received used equipment from others. CONCLUSIONS: HIV prevalence was relatively high given the prevalence of HIV in the general population, and HCV prevalence was extremely high among IDUs in Tijuana and Ciudad Juarez. Frequent sharing practices indicate a high potential for continued transmission for both infections. HCV counseling and testing for IDUs in Mexico and interventions to reduce sharing of injection equipment are needed.OBJETIVO: Estimar las prevalencias de los virus de hepatitis C (VHC) y de VIH y los comportamientos de riesgo asociados con ellos, entre usuarios de drogas inyectables (UDI) en dos ciudades del norte de México. MATERIAL Y MÉTODOS: Entre febrero y abril de 2005, se reclutaron UDIs en Tijuana (N=222) y en Ciudad Juárez (N=206), mediante un método de muestreo llamado en inglés "respondent-driven sampling" (RDS), lo cual es un sistema basado en cadenas de referencia. Los participantes contestaron una encuesta aplicada por entrevista, la cual indagó acerca de los comportamientos en el uso de drogas durante los seis meses previos. Una muestra de sangre venosa fue colectada de cada individuo, para determinar la presencia de anticuerpos contra VIH y VHC mediante técnicas inmunoenzimáticas. En el caso del VIH la técnica de "Western blot" se aplicó con fines de confirmación. La prevalencia final de anticuerpos contra VHC se hizo mediante un cálculo ajustado, que empleó un estimador poblacional del RDS. RESULTADOS: Las seroprevalencias globales de VHC y VIH, fueron 96% y 2.8%, respectivamente. Estas frecuencias fueron similares entre las muestras de ambas ciudades. La gran mayoría de los UDI (87.5%) manifestó haber transferido a otros sus equipos de inyección usados y a su vez 85.9% de los participantes declaró haber recibido equipos usados de otros. CONCLUSIONES: La seroprevalencia encontrada de VIH fue relativamente alta dada la prevalencia de VIH en la población general y la de VHC fue extremadamente alta entre los UDI estudiados en Tijuana y en Ciudad Juárez. Las prácticas frecuentes de compartimiento de equipo señalan hacia un alto potencial que favorece la transmisión de ambas infecciones investigadas. Por tanto, son necesarias actividades de consejería y pruebas de laboratorio para VHC dirigidas a UDI en México y asimismo intervenciones para reducir el uso compartido de equipos de inyección