There is a need for brief HIV prevention interventions that can be disseminated and implemented widely. This article reports the results of a small randomized field experiment that compared the relative effects of a brief 2-session counselor-delivered computer-tailored intervention and a control condition. The intervention is designed for use with African American, non-Hispanic white and Hispanic males and females who may be at risk of HIV through unprotected sex, selling sex, male to male sex, injecting drug use or use of stimulants. Participants (n=120) were recruited using a quota sampling approach and randomized using block randomization, which resulted in 10 male and 10 female participants of each racial/ethnic group (i.e. African-American, non-Hispanic white and Hispanic) being assigned to either the intervention or a control arm. In logistic regression analyses using a generalized estimating equations approach, at 3-month followup, participants in the intervention arm were more likely than participants in the control arm to report condom use at last sex (Odds ratio [OR] = 4.75; 95% Confidence interval [C.I.] = 1.70, 13.26; p = 0.003). The findings suggest that a brief tailored intervention may increase condom use. Larger studies with longer followups are needed to determine if these results can be replicated.
HIV prevention; brief interventions; computer-tailored; African-Americans; Hispanics; males; females
A new concept of within-individual epidemiology termed “myEpi” is introduced. It is argued that traditional epidemiological methods, which are usually applied to populations of humans, can be applicable to a single individual and thus used for self-monitoring and forecasting of “epidemic” outbreaks within an individual. Traditional epidemiology requires that results be generalizable to a predefined population. The key component of myEpi is that a single individual may be viewed as an entire population of events and thus, the analysis should be generalizable to this population. Applications of myEpi are aimed for, but not limited to, the analysis of data collected by individuals with the help of wearable sensors and digital diaries. These data can include physiological measures and records of healthy and risky behaviors (e.g., exercise, sleep, smoking, food consumption, alcohol, and drug use). Although many examples of within-individual epidemiology exist, there is a pressing need for systematic guidance to the analysis and interpretation of intensive individual-level data. myEpi serves this need by adapting statistical methods (e.g., regressions, hierarchical models, survival analysis, agent-based models) to individual-level data.
mobile health; epidemiology; statistics; data science; myEpi; wearable devices; evidence-based practice; self-care
This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed.
A number of factors have been identified that are related to sexual and injecting HIV transmission. We developed a probabilistic mathematical model to put these factors together and interpret risks in the context of individual behavior among injecting drug-using (IDU) couples in St. Petersburg, Russia. Some HIV-discordant couples have unprotected sex and sometimes inject drugs together but stay discordant for a long time, while some individuals acquire HIV on the first encounter. We considered existing estimates of HIV transmission risks through injecting and sexual contacts to develop a predictive survival model for an individual who is exposed to HIV through intimate relationships. We computed simulated survival curves for a number of behavioral scenarios and discussed sources of simulated uncertainty. We then applied the model to a longitudinal study of HIV-discordant couples and validated the model’s forecast. Although individual prediction of seroconversion time appeared impossible, the ability to rank behavioral patterns in terms of HIV risk and to estimate the probability of survival HIV-free will be important to educators and counselors.
Recursive partitioning is a non-parametric modeling technique, widely used in regression and classification problems. Model-based recursive partitioning is used to identify groups of observations with similar values of parameters of the model of interest. The mob() function in the party package in R implements model-based recursive partitioning method. This method produces predictions based on single tree models. Predictions obtained through single tree models are very sensitive to small changes to the learning sample. We extend the model-based recursive partition method to produce predictions based on multiple tree models constructed on random samples achieved either through bootstrapping (random sampling with replacement) or subsampling (random sampling without replacement) on learning data.
Here we present an R package called “mobForest” that implements bagging and random forests methodology for model-based recursive partitioning. The mobForest package constructs large number of model-based trees and the predictions are aggregated across these trees resulting in more stable predictions. The package also includes functions for computing predictive accuracy estimates and plots, residuals plot, and variable importance plot.
The mobForest package implements a random forest type approach for model-based recursive partitioning. The R package along with it source code is available at http://CRAN.R-project.org/package=mobForest.
Random forests; Model-based recursive partitioning; Ensemble; R
With HIV prevalence estimated at 20% among female injecting drug users (IDUs) in St. Petersburg, Russia, there is a critical need to address the HIV risks of this at-risk population. This study characterized HIV risks associated with injecting drug use and sex behaviors and assessed the initial feasibility and efficacy of an adapted Woman-Focused intervention, the Women's CoOp, relative to a Nutrition control to reduce HIV risk behaviors among female IDUs in an inpatient detoxification drug treatment setting.
Women (N = 100) were randomized into one of two one-hour long intervention conditions--the Woman-Focused intervention (n = 51) or a time and attention-matched Nutrition control condition (n = 49).
The results showed that 57% of the participants had been told that they were HIV-positive. At 3-month follow-up, both groups showed reduced levels of injecting frequency. However, participants in the Woman-Focused intervention reported, on average, a lower frequency of partner impairment at last sex act and a lower average number of unprotected vaginal sex acts with their main sex partner than the Nutrition condition.
The findings suggest that improvements in sexual risk reduction are possible for these at-risk women and that more comprehensive treatment is needed to address HIV and drug risks in this vulnerable population.
HIV; women; female IDUs; Woman-Focused intervention; Russia
To determine (1) the magnitude of clustering of bronchopulmonary dysplasia (36 weeks) or death (the outcome) across centers of the Eunice Kennedy Shriver National Institute of Child and Human Development National Research Network, (2) the infant-level variables associated with the outcome and estimate their clustering, and (3) the center-specific practices associated with the differences and build predictive models.
Data on neonates with a birth weight of <1250 g from the cluster-randomized benchmarking trial were used to determine the magnitude of clustering of the outcome according to alternating logistic regression by using pairwise odds ratio and predictive modeling. Clinical variables associated with the outcome were identified by using multivariate analysis. The magnitude of clustering was then evaluated after correction for infant-level variables. Predictive models were developed by using center-specific and infant-level variables for data from 2001 2004 and projected to 2006.
In 2001–2004, clustering of bronchopulmonary dysplasia/death was significant (pairwise odds ratio: 1.3; P < .001) and increased in 2006 (pairwise odds ratio: 1.6; overall incidence: 52%; range across centers: 32%–74%); center rates were relatively stable over time. Variables that varied according to center and were associated with increased risk of outcome included lower body temperature at NICU admission, use of prophylactic indomethacin, specific drug therapy on day 1, and lack of endotracheal intubation. Center differences remained significant even after correction for clustered variables.
Bronchopulmonary dysplasia/death rates demonstrated moderate clustering according to center. Clinical variables associated with the outcome were also clustered. Center differences after correction of clustered variables indicate presence of as-yet unmeasured center variables.
logistic models; infant; premature; predictive value of tests; clustering
Assessments of infectious disease spread in hospitals seldom account for interfacility patient sharing. This is particularly important for pathogens with prolonged incubation periods or carrier states.
We quantified patient sharing among all 32 hospitals in Orange County (OC), California, using hospital discharge data. Same-day transfers between hospitals were considered “direct” transfers, and events in which patients were shared between hospitals after an intervening stay at home or elsewhere were considered “indirect” patient-sharing events. We assessed the frequency of readmissions to another OC hospital within various time points from discharge and examined interhospital sharing of patients with Clostridium difficile infection.
In 2005, OC hospitals had 319,918 admissions. Twenty-nine percent of patients were admitted at least twice, with a median interval between discharge and readmission of 53 days. Of the patients with 2 or more admissions, 75% were admitted to more than 1 hospital. Ninety-four percent of interhospital patient sharing occurred indirectly. When we used 10 shared patients as a measure of potential interhospital exposure, 6 (19%) of 32 hospitals “exposed” more than 50% of all OC hospitals within 6 months, and 17 (53%) exposed more than 50% within 12 months. Hospitals shared 1 or more patient with a median of 28 other hospitals. When we evaluated patients with C. difficile infection, 25% were readmitted within 12 weeks; 41% were readmitted to different hospitals, and less than 30% of these readmissions were direct transfers.
In a large metropolitan county, interhospital patient sharing was a potential avenue for transmission of infectious agents. Indirect sharing with an intervening stay at home or elsewhere composed the bulk of potential exposures and occurred unbeknownst to hospitals.
Gay and bisexual men are often treated as a homogenous group; however, there may be important differences between them. In addition, behaviorally bisexual men are a potential source of HIV infection for heterosexual women. In this study, we compared 97 men who have sex with men only (MSM) to 175 men who have sex with men and women (MSMW). We also compared the 175 MSMW to 772 men who have sex with women only (MSW). Bivariate and multiple logistic regression analyses were performed to assess correlates of MSMW risk behaviors with men and with women as well as whether MSMW, compared with MSW, engaged in more risky behaviors with women. Compared with MSM, MSMW were less likely to be HIV-positive or to engage in unprotected receptive anal intercourse. In contrast, MSMW were more likely than MSW to be HIV-positive and to engage in anal intercourse with their female partners; however, rates of unprotected anal intercourse were similar. The study findings suggest that there may be important differences in HIV risk behaviors and HIV prevalence between MSM and MSMW as well as between MSMW and MSW.
Behaviorally bisexual men; Men who have sex with men; Risk behaviors; HIV
Transactional sex refers to selling sex (exchanging sex for money, drugs, food, shelter, or other items) or purchasing sex (exchanging money, drugs, food, shelter, or other items for sex). These activities have been associated with a higher risk for HIV and other sexually transmitted infections in a variety of populations and settings. This paper examines correlates of purchasing and selling sex in a large sample of drug users, men who have sex with men, and sex partners of these groups. Using respondent-driven sampling, participants were recruited between 2005 and 2008 in two urban and two rural counties in North Carolina. We used multiple logistic regressions to examine separate models for selling and purchasing sex in men and women. In addition, we estimated direct and indirect associations among independent variables in the logistic regression models and transactional sex using structural equation models. The analysis shows that factors associated with women selling and buying sex include being homeless, use of stimulants, bisexual behavior, and neighborhood disorder. There was also a significant difference by race. For men, the factors associated with selling and buying sex include being homeless, bisexual behavior, and not being in a relationship. Although neighborhood violence and disorder show significance in bivariate associations with the outcome, these associations disappear in the structural equation models.
Transactional sex; Sex trading; Sexual risk; Men who have sex with men; Women; HIV
This study examines the association between using and sharing high dead-space syringes (HDSSs)—which retain over 1,000 times more blood after rinsing than low dead-space syringes (LDSSs)—and prevalent HIV and hepatitis C virus (HCV) infections among injecting drug users (IDUs). A sample of 851 out-of-treatment IDUs was recruited in Raleigh-Durham, North Carolina, between 2003 and 2005. Participants were tested for HIV and HCV antibodies. Demographic, drug use, and injection practice data were collected via interviews. Data were analyzed using multiple logistic regression analysis. Participants had a mean age of 40 years and 74% percent are male, 63% are African American, 29% are non-Hispanic white, and 8% are of other race/ethnicity. Overall, 42% of participants had ever used an HDSS and 12% had shared one. HIV prevalence was 5% among IDUs who had never used an HDSS compared with 16% among IDUs who had shared one. The HIV model used a propensity score approach to adjust for differences between IDUs who had used an HDSS and those who had never used one. The HCV models included all potential confounders as covariates. A history of sharing HDSSs was associated with prevalent HIV (Odds Ratio = 2.50; 95% Confidence Interval = 1.01, 6.15). Use and sharing of HDSSs were also associated with increased odds of HCV infection. Prospective studies are needed to determine if sharing HDSSs is associated with increased HIV and HCV incidence among IDUs.
High dead-space syringes; Hepatitis C virus; HIV; Injecting drug users; Risk factors
Mathematical models that describe the global spread of infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) often consider a sample of international airports as a network supporting disease spread. However, there is no consensus on how many cities should be selected or on how to select those cities. Using airport flight data that commercial airlines reported to the Official Airline Guide (OAG) in 2000, we have examined the network characteristics of network samples obtained under different selection rules. In addition, we have examined different size samples based on largest flight volume and largest metropolitan populations. We have shown that although the bias in network characteristics increases with the reduction of the sample size, a relatively small number of areas that includes the largest airports, the largest cities, the most-connected cities, and the most central cities is enough to describe the dynamics of the global spread of influenza. The analysis suggests that a relatively small number of cities (around 200 or 300 out of almost 3000) can capture enough network information to adequately describe the global spread of a disease such as influenza. Weak traffic flows between small airports can contribute to noise and mask other means of spread such as the ground transportation.
Research on the neurocognitive characteristics of heroin addiction is sparse and studies that do exist include polydrug abusers; thus, they are unable to distinguish neurocognitive effects of heroin from those of other drugs. To identify neurocognitive correlates specific to heroin addiction, the present study was conducted in St. Petersburg, Russia where individuals typically abuse and/or become addicted to only one substance, generally alcohol or heroin. Heroin addicts were recruited from an inpatient treatment facility in St. Petersburg. Three comparison groups included alcoholics, addicts who used both alcohol and heroin, and non-abusers. Psychiatric, background, and drug history evaluations were administered after detoxification to screen for exclusion criteria and characterize the sample. Executive Cognitive Functions (ECF) that largely activate areas of the prefrontal cortex and its circuitry measured include complex visual pattern recognition (Paired Associates Learning), working memory (Delayed Matching to Sample), problem solving (Stockings of Cambridge), executive decision making (Cambridge Decision Making Task), cognitive flexibility (Stroop Color-Word Task) and response shifting (Stop Change Task). In many respects, the heroin addicts were similar to alcohol and alcohol\heroin dependent groups in neurocognitive deficits relative to controls. The primary finding was that heroin addicts exhibited significantly more disadvantageous decision making and longer deliberation times while making risky decisions than the other groups. Because the nature and degree of recovery from drug abuse are likely a function of the type or pattern of neurocognitive impairment, differential drug effects must be considered.
heroin addiction; cognition; neuropsychology; alcoholism; Russia
Planning for a possible influenza pandemic is an extremely high priority, as social and economic effects of an unmitigated pandemic would be devastating. Mathematical models can be used to explore different scenarios and provide insight into potential costs, benefits, and effectiveness of prevention and control strategies under consideration.
Methods and Findings
A stochastic, equation-based epidemic model is used to study global transmission of pandemic flu, including the effects of travel restrictions and vaccination. Economic costs of intervention are also considered. The distribution of First Passage Times (FPT) to the United States and the numbers of infected persons in metropolitan areas worldwide are studied assuming various times and locations of the initial outbreak. International air travel restrictions alone provide a small delay in FPT to the U.S. When other containment measures are applied at the source in conjunction with travel restrictions, delays could be much longer. If in addition, control measures are instituted worldwide, there is a significant reduction in cases worldwide and specifically in the U.S. However, if travel restrictions are not combined with other measures, local epidemic severity may increase, because restriction-induced delays can push local outbreaks into high epidemic season. The per annum cost to the U.S. economy of international and major domestic air passenger travel restrictions is minimal: on the order of 0.8% of Gross National Product.
International air travel restrictions may provide a small but important delay in the spread of a pandemic, especially if other disease control measures are implemented during the afforded time. However, if other measures are not instituted, delays may worsen regional epidemics by pushing the outbreak into high epidemic season. This important interaction between policy and seasonality is only evident with a global-scale model. Since the benefit of travel restrictions can be substantial while their costs are minimal, dismissal of travel restrictions as an aid in dealing with a global pandemic seems premature.
The contribution of birth defects, including cleft lip and palate, to neonatal and infant mortality and morbidity is substantial. As other mortality and morbidity causes including infections, hygiene, prematurity, and nutrition are eradicated in less developed countries, the burden of birth defects will increase proportionally.
We are using cleft lip and palate as a sentinel birth defect to evaluate its burden on neonatal and infant health and to assess the effectiveness of systematic pediatric care during the first month and first two years of life in decreasing this burden. The neonatal intervention, consisting of weekly pediatric evaluation and referral to appropriate care, is delivered to about 696 infants born with cleft lip and/or palate in 47 hospitals in South America. Neonatal mortality in this group will be compared to that in a retrospective control group of about 464 infants born with cleft lip and/or palate in the same hospitals. The subgroup of infants with isolated clefts of both the lip and palate (about 264) is also randomized into two groups, intervened and non-intervened, and further followed up over 2 years. Intervened cases are evaluated by pediatricians every three months and referred for appropriate care. The intervened and non-intervened cases will be compared over study outcomes to evaluate the intervention effectiveness. Non-intervened cases are matched and compared to healthy controls to assess the burden of cleft lip and palate. Outcomes include child's neurological and physical development and family social and economic conditions.
Large-scale clinical trials to improve infant health in developing countries are commonly suggested, making it important to share the methods used in ongoing studies with other investigators implementing similar research. We describe here the content of our ongoing pediatric care study in South America. We hope that this may help researchers targeting this area to plan their studies more effectively and encourage the development of similar research efforts to target other birth defects or infant outcomes such as prematurity and low birth weight.