Exploratory assessment: Nurse-led community health worker delivered HCV intervention for people experiencing homelessness.

BACKGROUND: Getting and maintaining Hepatitis C Virus (HCV) cure is challenging among people experiencing homelessness (PEH) as a result of critical social determinants of health such as unstable housing, mental health disorders, and drug and alcohol use. OBJECTIVES: The purpose of this exploratory pilot study was to compare a registered nurse/community health worker (RN/CHW)-led HCV intervention tailored for PEH, "I am HCV Free," with a clinic-based standard of care (cbSOC) for treating HCV. Efficacy was measured by sustained virological response at 12 weeks after stopping antivirals (SVR12), and improvement in mental health, drug and alcohol use, and access to healthcare. METHODS: An exploratory randomized controlled trial design was used to assign PEH recruited from partner sites in the Skid Row Area of Los Angeles, California, to the RN/CHW or cbSOC programs. All received direct-acting antivirals. The RN/CHW group received directly observed therapy in community-based settings, incentives for taking HCV medications, and wrap-around services, including connection to additional healthcare services, housing support, and referral to other community services. For all PEH, drug and alcohol use and mental health symptoms were measured at month 2 or 3 and 5 or 6 follow-up, depending on HCV medication type, while SVR12 was measured at month 5 or 6 follow-up. RESULTS: Among PEH in the RN/CHW group, 75% (3 of 4) completed SVR12 and all three attained undetectable viral load. This was compared with 66.7% (n = 4 of 6) of the cbSOC group who completed SVR12; all four attained undetectable viral load. The RN/CHW group, as compared to the cbSOC, also showed greater improvements in mental health, and significant improvement in drug use, and access to healthcare services. DISCUSSION: While this study shows significant improvements in drug use and health service access among the RN/-CHW group, the sample size of the study limits the validity and generalizability of the results. Further studies using larger sample sizes are necessitated.

Using genetic data to identify transmission risk factors: Statistical assessment and application to tuberculosis transmission.

Identifying host factors that influence infectious disease transmission is an important step toward developing interventions to reduce disease incidence. Recent advances in methods for reconstructing infectious disease transmission events using pathogen genomic and epidemiological data open the door for investigation of host factors that affect onward transmission. While most transmission reconstruction methods are designed to work with densely sampled outbreaks, these methods are making their way into surveillance studies, where the fraction of sampled cases with sequenced pathogens could be relatively low. Surveillance studies that use transmission event reconstruction then use the reconstructed events as response variables (i.e., infection source status of each sampled case) and use host characteristics as predictors (e.g., presence of HIV infection) in regression models. We use simulations to study estimation of the effect of a host factor on probability of being an infection source via this multi-step inferential procedure. Using TransPhylo-a widely-used method for Bayesian estimation of infectious disease transmission events-and logistic regression, we find that low sensitivity of identifying infection sources leads to dilution of the signal, biasing logistic regression coefficients toward zero. We show that increasing the proportion of sampled cases improves sensitivity and some, but not all properties of the logistic regression inference. Application of these approaches to real world data from a population-based TB study in Botswana fails to detect an association between HIV infection and probability of being a TB infection source. We conclude that application of a pipeline, where one first uses TransPhylo and sparsely sampled surveillance data to infer transmission events and then estimates effects of host characteristics on probabilities of these events, should be accompanied by a realistic simulation study to better understand biases stemming from imprecise transmission event inference.

Human papillomavirus genotypes in women with invasive cervical cancer with and without human immunodeficiency virus infection in Botswana.

Cervical cancer remains a significant cause of morbidity and mortality in women worldwide and is the leading cause of cancer-related death in Botswana. It is well established that women with HIV have a higher risk of persistent HPV infection leading to cervical cancer. We assessed HPV prevalence and genotype distribution in 126 tissue specimens from confirmed invasive cervical cancer cases using Abbott real-time PCR assay. Overall, 88 (69.8%) women were HIV-infected. Fifty-seven (64.8%) of the HIV-infected women had a baseline CD4+ count ≥350 cells/µl, and 82 (93.2%) were on antiretroviral therapy at the time of cervical cancer diagnosis. The median age of HIV-infected patients was significantly younger than that of HIV-uninfected patients (p < 0.001). HPV DNA was detected in all of 126 (100%) of tissues analyzed in our study. The HPV genotypes identified included the HPV-16 (75.4%), HPV-18 (28.6%) and other high-risk (hr) HPV genotypes (16.7%). HIV infection was positively associated with the presence of the HPV-16 genotype (p = 0.036), but not with HPV-18 or with other high-risk (hr)-HPV genotypes. Thirty-three percent of the patients had multiple hr-HPV genotypes, with higher rates in HIV-infected women. These results highlight the importance and potential impact of large-scale HPV vaccination programs covering HPV-16 and HPV-18 genotypes in countries like Botswana with high burden of HIV infection.