A novel use of HIV surveillance and court data to understand and improve care among a population of people with HIV experiencing criminal charges in North Carolina 2017-2020.

Objectives Objectives: To enumerate the population of people with HIV (PWH) with criminal charges and to estimate associations between charges and HIV outcomes. Methods: We linked statewide North Carolina criminal court records to confidential HIV records (both 2017-2020) to identify a population of defendants with diagnosed HIV. We used generalized estimating equations to examine changes in viral suppression (outcome) pre-post criminal charges (exposure), adjusting for other demographic and legal system factors. Results: 9,534 PWH experienced criminal charges. Compared to others with charges, PWH were more likely to be male and report Black race. The median duration of unresolved charges was longer for PWH. When adjusting for demographic factors, the period following resolution of charges was modestly associated with an increased risk of viral suppression (aRR 1.03 (95% confidence interval 1.02-1.04) compared to the pre-charge period. Conclusions: A significant portion of PWH in NC had criminal charges during a three-year period, and these charges went unresolved for a longer time than those without HIV. These preliminary findings raise questions regarding whether PWH have appropriate access to legal services.

An HIV-1 risk assessment tool for women aged 15-49 in African countries: A pooled analysis across 15 nationally representative surveys.

BACKGROUND: Women in Africa disproportionately acquire HIV-1. Understanding which women are most likely to acquire HIV-1 can guide focused prevention with pre-exposure prophylaxis (PrEP). Our objective is to identify women at highest risk of HIV-1 and estimate PrEP efficiency at different sensitivity levels. METHODS: Nationally representative data were collected from 2015-2019 from 15 population-based household surveys. This analysis included women aged 15-49 who tested HIV-1 sero-negative or had recent HIV-1. Least absolute shrinkage and selection operator regression models were fit with 28 variables to predict recent HIV-1. Models were trained on the full population and internally cross-validated. Performance was evaluated using area under the receiver-operating-characteristic curve (AUC), sensitivity, and number needed to treat (NNT) with PrEP to avert one infection. RESULTS: Among 209,012 participants 248 had recent HIV-1 infection, representing 118 million women and 402,000 (95% CI: 309,000-495,000) new annual infections. Two variables were retained in the model: living in a subnational area with high HIV-1 viremia and having a sexual partner living outside the home. Full-population AUC was 0.80 (95% CI: 0.76-0.84); cross-validated AUC was 0.79 (95% CI: 0.75-0.84). At a sensitivity of 33%, up to 130,000 cases could be averted if 7.9 million women were perfectly adherent to PrEP; NNT would be 61. At a sensitivity of 67%, up to 260,000 cases could be averted if 25.1 million women were perfectly adherent to PrEP; the NNT would be 96. CONCLUSIONS: This risk assessment tool was generalizable, predictive, and parsimonious with tradeoffs between reach and efficiency.

Higher-order evidence.

Higher-order evidence is evidence about evidence. Epidemiologic examples of higher-order evidence include the settings where the study data constitute first-order evidence and estimates of misclassification comprise the second-order evidence (e.g., sensitivity, specificity) of a binary exposure or outcome collected in the main study. While sampling variability in higher-order evidence is typically acknowledged, higher-order evidence is often assumed to be free of measurement error (e.g., gold standard measures). Here we provide two examples, each with multiple scenarios where second-order evidence is imperfectly measured, and this measurement error can either amplify or attenuate standard corrections to first-order evidence. We propose a way to account for such imperfections that requires third-order evidence. Further illustrations and exploration of how higher-order evidence impacts results of epidemiologic studies is warranted.

Magnitude and Durability of the Antibody Response to mRNA-Based Vaccination Among SARS-CoV-2 Seronegative and Seropositive Health Care Personnel.

Few studies have described changes in SARS-CoV-2 antibody levels in response to infection and vaccination at frequent intervals and over extended follow-up periods. The purpose of this study was to assess changes in SARS-CoV-2-specific antibody responses among a prospective cohort of health care personnel over 18 months with up to 22 samples per person. Antibody levels and live virus neutralization were measured before and after mRNA-based vaccination with results stratified by (1) SARS-CoV-2 infection status prior to initial vaccination and (2) SARS-CoV-2 infection at any point during follow-up. We found that the antibody response to the first dose was almost 2-fold higher in individuals who were seropositive prior to vaccination, although neutralization titers were more variable. The antibody response induced by vaccination appeared to wane over time but generally persisted for 8 to 9 months, and those who were infected at any point during the study had slightly higher antibody levels over time vs those who remained uninfected. These findings underscore the need to account for SARS-CoV-2 natural infection as a modifier of vaccine responses, and they highlight the importance of frequent testing of longitudinal antibody titers over time. Together, our results provide a clearer understanding of the trajectories of antibody response among vaccinated individuals with and without prior SARS-CoV-2 infection.

HIV Prevention Among Men Who Have Sex With Men: Tenofovir Alafenamide Combination Preexposure Prophylaxis Versus Placebo.

BACKGROUND: While noninferiority of tenofovir alafenamide and emtricitabine (TAF/FTC) as preexposure prophylaxis (PrEP) for the prevention of human immunodeficiency virus (HIV) has been shown, interest remains in its efficacy relative to placebo. We estimate the efficacy of TAF/FTC PrEP versus placebo for the prevention of HIV infection. METHODS: We used data from the DISCOVER and iPrEx trials to compare TAF/FTC to placebo. DISCOVER was a noninferiority trial conducted from 2016 to 2017. iPrEx was a placebo-controlled trial conducted from 2007 to 2009. Inverse probability weights were used to standardize the iPrEx participants to the distribution of demographics and risk factors in the DISCOVER trial. To check the comparison, we evaluated whether risk of HIV infection in the shared tenofovir disoproxil fumarate and emtricitabine (TDF/FTC) arms was similar. RESULTS: Notable differences in demographics and risk factors occurred between trials. After standardization, the difference in risk of HIV infection between the TDF/FTC arms was near zero. The risk of HIV with TAF/FTC was 5.8 percentage points lower (95% confidence interval [CI], -2.0% to -9.6%) or 12.5-fold lower (95% CI, .02 to .31) than placebo standardized to the DISCOVER population. CONCLUSIONS: There was a reduction in HIV infection with TAF/FTC versus placebo across 96 weeks of follow-up. CLINICAL TRIALS REGISTRATION: NCT02842086 and NCT00458393.

Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling.

Studies designed to estimate the effect of an action in a randomized or observational setting often do not represent a random sample of the desired target population. Instead, estimates from that study can be transported to the target population. However, transportability methods generally rely on a positivity assumption, such that all relevant covariate patterns in the target population are also observed in the study sample. Strict eligibility criteria, particularly in the context of randomized trials, may lead to violations of this assumption. Two common approaches to address positivity violations are restricting the target population and restricting the relevant covariate set. As neither of these restrictions is ideal, we instead propose a synthesis of statistical and simulation models to address positivity violations. We propose corresponding g-computation and inverse probability weighting estimators. The restriction and synthesis approaches to addressing positivity violations are contrasted with a simulation experiment and an illustrative example in the context of sexually transmitted infection testing uptake. In both cases, the proposed synthesis approach accurately addressed the original research question when paired with a thoughtfully selected simulation model. Neither of the restriction approaches was able to accurately address the motivating question. As public health decisions must often be made with imperfect target population information, model synthesis is a viable approach given a combination of empirical data and external information based on the best available knowledge.

Fusing trial data for treatment comparisons: Single vs multi-span bridging.

While randomized controlled trials (RCTs) are critical for establishing the efficacy of new therapies, there are limitations regarding what comparisons can be made directly from trial data. RCTs are limited to a small number of comparator arms and often compare a new therapeutic to a standard of care which has already proven efficacious. It is sometimes of interest to estimate the efficacy of the new therapy relative to a treatment that was not evaluated in the same trial, such as a placebo or an alternative therapy that was evaluated in a different trial. Such dual-study comparisons are challenging because of potential differences between trial populations that can affect the outcome. In this article, two bridging estimators are considered that allow for comparisons of treatments evaluated in different trials, accounting for measured differences in trial populations. A "multi-span" estimator leverages a shared arm between two trials, while a "single-span" estimator does not require a shared arm. A diagnostic statistic that compares the outcome in the standardized shared arms is provided. The two estimators are compared in simulations, where both estimators demonstrate minimal empirical bias and nominal confidence interval coverage when the identification assumptions are met. The estimators are applied to data from the AIDS Clinical Trials Group 320 and 388 to compare the efficacy of two-drug vs four-drug antiretroviral therapy on CD4 cell counts among persons with advanced HIV. The single-span approach requires weaker identification assumptions and was more efficient in simulations and the application.

Estimating SARS-CoV-2 seroprevalence.

Governments and public health authorities use seroprevalence studies to guide responses to the COVID-19 pandemic. Seroprevalence surveys estimate the proportion of individuals who have detectable SARS-CoV-2 antibodies. However, serologic assays are prone to misclassification error, and non-probability sampling may induce selection bias. In this paper, non-parametric and parametric seroprevalence estimators are considered that address both challenges by leveraging validation data and assuming equal probabilities of sample inclusion within covariate-defined strata. Both estimators are shown to be consistent and asymptotically normal, and consistent variance estimators are derived. Simulation studies are presented comparing the estimators over a range of scenarios. The methods are used to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in New York City, Belgium, and North Carolina.

Estimation of SARS-CoV-2 Seroprevalence in Central North Carolina: Accounting for Outcome Misclassification in Complex Sample Designs.

BACKGROUND: Population-based seroprevalence studies are crucial to understand community transmission of COVID-19 and guide responses to the pandemic. Seroprevalence is typically measured from diagnostic tests with imperfect sensitivity and specificity. Failing to account for measurement error can lead to biased estimates of seroprevalence. Methods to adjust seroprevalence estimates for the sensitivity and specificity of the diagnostic test have largely focused on estimation in the context of convenience sampling. Many existing methods are inappropriate when data are collected using a complex sample design. METHODS: We present methods for seroprevalence point estimation and confidence interval construction that account for imperfect test performance for use with complex sample data. We apply these methods to data from the Chatham County COVID-19 Cohort (C4), a longitudinal seroprevalence study conducted in central North Carolina. Using simulations, we evaluate bias and confidence interval coverage for the proposed estimator compared with a standard estimator under a stratified, three-stage cluster sample design. RESULTS: We obtained estimates of seroprevalence and corresponding confidence intervals for the C4 study. SARS-CoV-2 seroprevalence increased rapidly from 10.4% in January to 95.6% in July 2021 in Chatham County, North Carolina. In simulation, the proposed estimator demonstrates desirable confidence interval coverage and minimal bias under a wide range of scenarios. CONCLUSION: We propose a straightforward method for producing valid estimates and confidence intervals when data are based on a complex sample design. The method can be applied to estimate the prevalence of other infections when estimates of test sensitivity and specificity are available.

Comparison of capillary blood self-collection using the Tasso-SST device with venous phlebotomy for anti-SARS-CoV-2 antibody measurement.

Measuring seroprevalence over time is a valuable epidemiological tool for improving our understanding of COVID-19 immunity. Due to the large number of collections required for population surveillance as well as concerns about potential infection risk to the collectors, self-collection approaches are being increasingly pursued. To advance this methodology, we collected paired venous and capillary blood samples by routine phlebotomy and Tasso-SST device respectively from 26 participants and measured total immunoglobulin (Ig) and IgG antibodies to the SARS-CoV-2 receptor binding domain (RBD) by enzyme-linked immunosorbent assay (ELISA) on both specimens. Qualitatively, no discrepancies were noted in binary results between Tasso and venipuncture-derived plasma. Furthermore, in vaccinated participants, correlation between Tasso and venous total Ig and IgG specific antibody quantitative levels was high (Total Ig: Spearman ρ = 0.72, 95% CI (0.39,0.90); IgG: Spearman ρ = 0.85, 95% CI (0.54, 0.96)). Our results support the use of Tasso at-home collection devices for antibody testing.

Reducing Bias in Estimates of Per Protocol Treatment Effects: A Secondary Analysis of a Randomized Clinical Trial.

This secondary analysis of a randomized clinical trial evaluates ways of reducing bias in estimates of per protocol treatment effects.

Sensitivity Analyses for Means or Proportions with Missing Outcome Data.

We describe an approach to sensitivity analysis introduced by Robins et al (1999), for the setting where the outcome is missing for some observations. This flexible approach focuses on the relationship between the outcomes and missingness, where data can be missing completely at random, missing at random given observed data, or missing not at random. We provide examples from HIV that include the sensitivity of the estimation of a mean and proportion under different missingness mechanisms. The approach illustrated provides a method for examining how the results of epidemiologic studies might shift as a function of bias due to missing data.

Pre-Heart Failure Longitudinal Change in a Hispanic/Latino Population-Based Study: Insights From the Echocardiographic Study of Latinos.

BACKGROUND: Pre-heart failure (pre-HF) is an entity known to progress to symptomatic heart failure (HF). OBJECTIVES: This study aimed to characterize pre-HF prevalence and incidence among Hispanics/Latinos. METHODS: The Echo-SOL (Echocardiographic Study of Latinos) assessed cardiac parameters on 1,643 Hispanics/Latinos at baseline and 4.3 years later. Prevalent pre-HF was defined as the presence of any abnormal cardiac parameter (left ventricular [LV] ejection fraction <50%; absolute global longitudinal strain <15%; grade 1 or more diastolic dysfunction; LV mass index >115 g/m2 for men, >95 g/m2 for women; or relative wall thickness >0.42). Incident pre-HF was defined among those without pre-HF at baseline. Sampling weights and survey statistics were used. RESULTS: Among this study population (mean age: 56.4 years; 56% female), HF risk factors, including prevalence of hypertension and diabetes, worsened during follow-up. Significant worsening of all cardiac parameters (except LV ejection fraction) was evidenced from baseline to follow-up (all P < 0.01). Overall, the prevalence of pre-HF was 66.7% at baseline and the incidence of pre-HF during follow-up was 66.3%. Prevalent and incident pre-HF were seen more with increasing baseline HF risk factor burden as well as with older age. In addition, increasing the number of HF risk factors increased the risk of prevalence of pre-HF and incidence of pre-HF (adjusted OR: 1.36 [95% CI: 1.16-1.58], and adjusted OR: 1.29 [95% CI: 1.00-1.68], respectively). Prevalent pre-HF was associated with incident clinical HF (HR: 10.9 [95% CI: 2.1-56.3]). CONCLUSIONS: Hispanics/Latinos exhibited significant worsening of pre-HF characteristics over time. Prevalence and incidence of pre-HF are high and are associated with increasing HF risk factor burden and with incidence of cardiac events.

Permethrin-treated baby wraps for the prevention of malaria in children: Protocol for a double-blind, randomized placebo-controlled controlled trial in western Uganda.

This article details the study protocol for a double-blind, randomized placebo-controlled trial to determine the effectiveness of permethrin-treated baby wraps to prevent Plasmodium falciparum malaria infection in children 6-24 months of age. Participating mother-infant dyads will be randomized to receive either a permethrin-treated or a sham-treated wrap, known locally as a "lesu." After a baseline home visit, during which time all participants will receive new long-lasting insecticidal nets, participants will attend scheduled clinic visits every two weeks for a period of 24 weeks. In the event of an acute febrile illness or other symptoms that may be consistent with malaria (e.g., poor feeding, headache, malaise), participants will be instructed to present to their respective study clinic for evaluation. The primary outcome of interest is the incidence of laboratory-confirmed, symptomatic malaria in participating children. Secondary outcomes of interest include: (1) change in children's hemoglobin levels; (2) change in children's growth parameters; (3) prevalence of asymptomatic parasitemia in children; (4) hospitalization for malaria in children; (5) change in the mother's hemoglobin level; and (6) clinical malaria in the mother. Analyses will be conducted using a modified intent-to-treat approach, with woman-infant dyads who attend one or more clinic visits analyzed according to the arm to which they were randomly assigned. This is the first use of an insecticide-treated baby wrap for prevention of malaria in children. The study began recruitment in June 2022 and is ongoing. ClinicalTrials.gov Identifier: NCT05391230, Registered 25 May 2022.

Comparison of Capillary Blood Self-Collection using the Tasso-SST Device with Venous Phlebotomy for anti-SARS-CoV-2 Antibody Measurement.

Measuring seroprevalence over time is a valuable epidemiological tool for improving our understanding of COVID-19 immunity. Due to the large number of collections required for population surveillance as well as concerns about potential infection risk to the collectors, self-collection approaches are being increasingly pursued. To advance this methodology, we collected paired venous and capillary blood samples by routine phlebotomy and Tasso-SST device respectively from 26 participants and measured total immunoglobulin (Ig) and IgG antibodies to the SARS-CoV-2 receptor binding domain (RBD) by enzyme-linked immunosorbent assay (ELISA) on both specimens. Qualitatively, no discrepancies were noted in binary results between Tasso and venipuncture-derived plasma. Furthermore, in vaccinated participants, correlation between Tasso and venous total Ig and IgG specific antibody quantitative levels was high (Total Ig: ρ = 0.72, 95% CI (0.39- 0.90); IgG: ρ = 0.85, 95% CI (0.54, 0.96)). Our results support the use of Tasso at-home collection devices for antibody testing.

It takes more than a machine: A pilot feasibility study of point-of-care HIV-1 viral load testing at a lower-level health center in rural western Uganda.

Barriers continue to limit access to viral load (VL) monitoring across sub-Saharan Africa adversely impacting control of the HIV epidemic. The objective of this study was to determine whether the systems and processes required to realize the potential of rapid molecular technology are available at a prototypical lower-level (i.e., level III) health center in rural Uganda. In this open-label pilot study, participants underwent parallel VL testing at both the central laboratory (i.e., standard of care) and on-site using the GeneXpert HIV-1 assay. The primary outcome was the number of VL tests completed each clinic day. Secondary outcomes included the number of days from sample collection to receipt of result at clinic and the number of days from sample collection to patient receipt of the result. From August 2020 to July 2021, we enrolled a total of 242 participants. The median number of daily tests performed on the Xpert platform was 4, (IQR = 2-7). Time from sample collection to result was 51 days (IQR = 45-62) for samples sent to the central laboratory and 0 days (IQR = 0-0.25) for the Xpert assay conducted at the health center. However, few participants elected to receive results by one of the expedited options, which contributed to similar time-to-patient between testing approaches (89 versus 84 days, p = 0.07). Implementation of a rapid, near point-of-care VL assay at a lower-level health center in rural Uganda appears feasible, but interventions to promote rapid clinical response and influence patient preferences about result receipt require further study. Trial registration: ClinicalTrials.gov Identifier: NCT04517825, Registered 18 August 2020. Available at: https://clinicaltrials.gov/ct2/show/NCT04517825.

When Does Differential Outcome Misclassification Matter for Estimating Prevalence?

BACKGROUND: When accounting for misclassification, investigators make assumptions about whether misclassification is "differential" or "nondifferential." Most guidance on differential misclassification considers settings where outcome misclassification varies across levels of exposure, or vice versa. Here, we examine when covariate-differential misclassification must be considered when estimating overall outcome prevalence. METHODS: We generated datasets with outcome misclassification under five data generating mechanisms. In each, we estimated prevalence using estimators that (a) ignored misclassification, (b) assumed misclassification was nondifferential, and (c) allowed misclassification to vary across levels of a covariate. We compared bias and precision in estimated prevalence in the study sample and an external target population using different sources of validation data to account for misclassification. We illustrated use of each approach to estimate HIV prevalence using self-reported HIV status among people in East Africa cross-border areas. RESULTS: The estimator that allowed misclassification to vary across levels of the covariate produced results with little bias for both populations in all scenarios but had higher variability when the validation study contained sparse strata. Estimators that assumed nondifferential misclassification produced results with little bias when the covariate distribution in the validation data matched the covariate distribution in the target population; otherwise estimates assuming nondifferential misclassification were biased. CONCLUSIONS: If validation data are a simple random sample from the target population, assuming nondifferential outcome misclassification will yield prevalence estimates with little bias regardless of whether misclassification varies across covariates. Otherwise, obtaining valid prevalence estimates requires incorporating covariates into the estimators used to account for misclassification.