Immune Correlates Analysis of a Single Ad26.COV2.S Dose in the ENSEMBLE COVID-19 Vaccine Efficacy Clinical Trial

Anti-spike IgG binding antibody, anti-receptor binding domain IgG antibody, and pseudovirus neutralizing antibody measurements four weeks post-vaccination were assessed as correlates of risk of moderate to severe-critical COVID-19 outcomes through 83 days post-vaccination and as correlates of protection following a single dose of Ad26.COV2.S COVID-19 vaccine in the placebo-controlled phase of ENSEMBLE, an international, randomized efficacy trial. Each marker had evidence as a correlate of risk and of protection, with strongest evidence for 50% inhibitory dilution (ID50) neutralizing antibody titer. The outcome hazard ratio was 0.49 (95% confidence interval 0.29, 0.81; p=0.006) per 10-fold increase in ID50; vaccine efficacy was 60% (43, 72%) at nonquantifiable ID50 (< 2.7 IU50/ml) and rose to 89% (78, 96%) at ID50 = 96.3 IU50/ml. Comparison of the vaccine efficacy by ID50 titer curves for ENSEMBLE-US, the COVE trial of the mRNA-1273 vaccine, and the COV002-UK trial of the AZD1222 vaccine supported consistency of the ID50 titer correlate of protection across trials and vaccine types.

A Cluster-based Method to Quantify Individual Heterogeneity in Tuberculosis Transmission

BACKGROUND

Recent evidence suggests transmission of Mycobacterium tuberculosis (Mtb) may be characterized by extreme individual heterogeneity in secondary cases (i.e., few cases account for the majority of transmission). Such heterogeneity implies outbreaks are rarer but more extensive and has profound implications in infectious disease control. However, discrete person-to-person transmission events in tuberculosis (TB) are often unobserved, precluding our ability to directly quantify individual heterogeneity in TB epidemiology.

METHODS

We used a modified negative binomial branching process model to quantify the extent of individual heterogeneity using only observed transmission cluster size distribution data (i.e., the simple sum of all cases in a transmission chain) without knowledge of individual-level transmission events. The negative binomial parameter k quantifies the extent of individual heterogeneity (generally, indicates extensive heterogeneity, and as transmission becomes more homogenous). We validated the robustness of the inference procedure considering common limitations affecting cluster size data. Finally, we demonstrate the epidemiologic utility of this method by applying it to aggregate US molecular surveillance data from the US Centers for Disease Control and Prevention.

RESULTS

The cluster-based method reliably inferred k using TB transmission cluster data despite a high degree of bias introduced into the model. We found that the TB transmission in the United States was characterized by a high propensity for extensive outbreaks (; 95% confidence interval = 0.09, 0.10).

CONCLUSIONS

The proposed method can accurately quantify critical parameters that govern TB transmission using simple, more easily obtainable cluster data to improve our understanding of TB epidemiology.

Immune correlates analysis of the mRNA-1273 COVID-19 vaccine efficacy clinical trial

In the coronavirus efficacy (COVE) phase 3 clinical trial, vaccine recipients were assessed for neutralizing and binding antibodies as correlates of risk for COVID-19 disease and as correlates of protection. These immune markers were measured at the time of second vaccination and 4 weeks later, with values reported in standardized World Health Organization international units. All markers were inversely associated with COVID-19 risk and directly associated with vaccine efficacy. Vaccine recipients with postvaccination 50% neutralization titers 10, 100, and 1000 had estimated vaccine efficacies of 78% (95% confidence interval, 54 to 89%), 91% (87 to 94%), and 96% (94 to 98%), respectively. These results help define immune marker correlates of protection and may guide approval decisions for messenger RNA (mRNA) COVID-19 vaccines and other COVID-19 vaccines.

Authorship trends in infectious diseases society of America affiliated journal articles conducted in low-income countries, 1998-2018

An increasing amount of infectious diseases research is conducted in low-income countries (LIC) given their high burden of disease; however, the contribution of LIC investigators as measured by authorship metrics, specifically to infectious diseases research, has not been thoroughly studied. We performed a literature search for primary research conducted either within LICs or using samples from LIC participants published between 1998-2017 in the Infectious Disease Society of America-affiliated journals Clinical Infectious Diseases, Journal of Infectious Diseases, and Open Forum Infectious Diseases. Primary outcomes included proportion of LIC-affiliated first and last authors (i.e. lead authors) per year and authorship trends over time. Secondary outcomes included proportion of LIC-affiliated authorship by geographic distribution and disease focus. Among 1308 publications identified, 50% had either a first or last LIC-affiliated author. Among these authors, 48% of LIC-affiliated first authors and 52% of LIC-affiliated last authors also reported a non-LIC institutional affiliation. While the absolute number of articles by LIC-affiliated lead authors increased over the 20-year period, the proportion of articles with LIC-affiliated lead authors decreased. There is a growing literature for infectious disease research conducted in LICs yet authorship trends in a small subset of these publications demonstrate a pronounced and worsening exclusion of LIC-affiliated investigators from publishing as lead authors.

Phase 3 Safety and Efficacy of AZD1222 (ChAdOx1 nCoV-19) Covid-19 Vaccine

BACKGROUND

The safety and efficacy of the AZD1222 (ChAdOx1 nCoV-19) vaccine in a large, diverse population at increased risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the United States, Chile, and Peru has not been known.

METHODS

In this ongoing, double-blind, randomized, placebo-controlled, phase 3 clinical trial, we investigated the safety, vaccine efficacy, and immunogenicity of two doses of AZD1222 as compared with placebo in preventing the onset of symptomatic and severe coronavirus disease 2019 (Covid-19) 15 days or more after the second dose in adults, including older adults, in the United States, Chile, and Peru.

RESULTS

A total of 32,451 participants underwent randomization, in a 2:1 ratio, to receive AZD1222 (21,635 participants) or placebo (10,816 participants). AZD1222 was safe, with low incidences of serious and medically attended adverse events and adverse events of special interest; the incidences were similar to those observed in the placebo group. Solicited local and systemic reactions were generally mild or moderate in both groups. Overall estimated vaccine efficacy was 74.0% (95% confidence interval [CI], 65.3 to 80.5; P<0.001) and estimated vaccine efficacy was 83.5% (95% CI, 54.2 to 94.1) in participants 65 years of age or older. High vaccine efficacy was consistent across a range of demographic subgroups. In the fully vaccinated analysis subgroup, no severe or critical symptomatic Covid-19 cases were observed among the 17,662 participants in the AZD1222 group; 8 cases were noted among the 8550 participants in the placebo group (<0.1%). The estimated vaccine efficacy for preventing SARS-CoV-2 infection (nucleocapsid antibody seroconversion) was 64.3% (95% CI, 56.1 to 71.0; P<0.001). SARS-CoV-2 spike protein binding and neutralizing antibodies increased after the first dose and increased further when measured 28 days after the second dose.

CONCLUSIONS

AZD1222 was safe and efficacious in preventing symptomatic and severe Covid-19 across diverse populations that included older adults. (Funded by AstraZeneca and others; ClinicalTrials.gov number, NCT04516746.).

Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes

Time is of the essence in evaluating potential drugs and biologics for the treatment and prevention of COVID-19. There are currently 876 randomized clinical trials (phase 2 and 3) of treatments for COVID-19 registered on clinicaltrials.gov. Covariate adjustment is a statistical analysis method with potential to improve precision and reduce the required sample size for a substantial number of these trials. Though covariate adjustment is recommended by the U.S. Food and Drug Administration and the European Medicines Agency, it is underutilized, especially for the types of outcomes (binary, ordinal, and time-to-event) that are common in COVID-19 trials. To demonstrate the potential value added by covariate adjustment in this context, we simulated two-arm, randomized trials comparing a hypothetical COVID-19 treatment versus standard of care, where the primary outcome is binary, ordinal, or time-to-event. Our simulated distributions are derived from two sources: longitudinal data on over 500 patients hospitalized at Weill Cornell Medicine New York Presbyterian Hospital and a Centers for Disease Control and Prevention preliminary description of 2449 cases. In simulated trials with sample sizes ranging from 100 to 1000 participants, we found substantial precision gains from using covariate adjustment-equivalent to 4-18% reductions in the required sample size to achieve a desired power. This was the case for a variety of estimands (targets of inference). From these simulations, we conclude that covariate adjustment is a low-risk, high-reward approach to streamlining COVID-19 treatment trials. We provide an R package and practical recommendations for implementation.

Immune Correlates Analysis of the mRNA-1273 COVID-19 Vaccine Efficacy Trial

BACKGROUND

In the Coronavirus Efficacy (COVE) trial, estimated mRNA-1273 vaccine efficacy against coronavirus disease-19 (COVID-19) was 94%. SARS-CoV-2 antibody measurements were assessed as correlates of COVID-19 risk and as correlates of protection.

METHODS

Through case-cohort sampling, participants were selected for measurement of four serum antibody markers at Day 1 (first dose), Day 29 (second dose), and Day 57: IgG binding antibodies (bAbs) to Spike, bAbs to Spike receptor-binding domain (RBD), and 50% and 80% inhibitory dilution pseudovirus neutralizing antibody titers calibrated to the WHO International Standard (cID50 and cID80). Participants with no evidence of previous SARS-CoV-2 infection were included. Cox regression assessed in vaccine recipients the association of each Day 29 or 57 serologic marker with COVID-19 through 126 or 100 days of follow-up, respectively, adjusting for risk factors.

RESULTS

Day 57 Spike IgG, RBD IgG, cID50, and cID80 neutralization levels were each inversely correlated with risk of COVID-19: hazard ratios 0.66 (95% CI 0.50, 0.88; p=0.005); 0.57 (0.40, 0.82; p=0.002); 0.42 (0.27, 0.65; p<0.001); 0.35 (0.20, 0.61; p<0.001) per 10-fold increase in marker level, respectively, multiplicity adjusted P-values 0.003-0.010. Results were similar for Day 29 markers (multiplicity adjusted P-values <0.001-0.003). For vaccine recipients with Day 57 reciprocal cID50 neutralization titers that were undetectable (<2.42), 100, or 1000, respectively, cumulative incidence of COVID-19 through 100 days post Day 57 was 0.030 (0.010, 0.093), 0.0056 (0.0039, 0.0080), and 0.0023 (0.0013, 0.0036). For vaccine recipients at these titer levels, respectively, vaccine efficacy was 50.8% (-51.2, 83.0%), 90.7% (86.7, 93.6%), and 96.1% (94.0, 97.8%). Causal mediation analysis estimated that the proportion of vaccine efficacy mediated through Day 29 cID50 titer was 68.5% (58.5, 78.4%).

CONCLUSIONS

Binding and neutralizing antibodies correlated with COVID-19 risk and vaccine efficacy and likely have utility in predicting mRNA-1273 vaccine efficacy against COVID-19.

TRIAL REGISTRATION NUMBER

COVE ClinicalTrials.gov number, NCT04470427.

A Deferred-Vaccination Design to Assess Durability of COVID-19 Vaccine Effect After the Placebo Group Is Vaccinated

Multiple candidate vaccines to prevent COVID-19 have entered large-scale phase 3 placebo-controlled randomized clinical trials, and several have demonstrated substantial short-term efficacy. At some point after demonstration of substantial efficacy, placebo recipients should be offered the efficacious vaccine from their trial, which will occur before longer-term efficacy and safety are known. The absence of a placebo group could compromise assessment of longer-term vaccine effects. However, by continuing follow-up after vaccination of the placebo group, this study shows that placebo-controlled vaccine efficacy can be mathematically derived by assuming that the benefit of vaccination over time has the same profile for the original vaccine recipients and the original placebo recipients after their vaccination. Although this derivation provides less precise estimates than would be obtained by a standard trial where the placebo group remains unvaccinated, this proposed approach allows estimation of longer-term effect, including durability of vaccine efficacy and whether the vaccine eventually becomes harmful for some. Deferred vaccination, if done open-label, may lead to riskier behavior in the unblinded original vaccine group, confounding estimates of long-term vaccine efficacy. Hence, deferred vaccination via blinded crossover, where the vaccine group receives placebo and vice versa, would be the preferred way to assess vaccine durability and potential delayed harm. Deferred vaccination allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain them on placebo, yet still allows important insights about immunologic and clinical effectiveness over time.

Super LeArner Prediction of NAb Panels (SLAPNAP): A Contain-erized Tool for Predicting Combination Monoclonal Broadly Neu-tralizing Antibody Sensitivity

MOTIVATION

A single monoclonal broadly neutralizing antibody (bnAb) regimen was recently evaluated in two randomized trials for prevention efficacy against HIV-1 infection. Subsequent trials will evaluate combination bnAb regimens (e.g., cocktails, multi-specific antibodies), which demonstrate higher potency and breadth in vitro compared to single bnAbs. Given the large number of potential regimens, methods for down-selecting these regimens into efficacy trials are of great interest.

RESULTS

We developed Super LeArner Prediction of NAb Panels (SLAPNAP), a software tool for training and evaluating machine learning models that predict in vitro neutralization sensitivity of HIV Envelope (Env) pseudoviruses to a given single or combination bnAb regimen, based on Env amino acid sequence features. SLAPNAP also provides measures of variable importance of sequence features. By predicting bnAb coverage of circulating sequences, SLAPNAP can improve ranking of bnAb regimens by their potential prevention efficacy. In addition, SLAPNAP can improve sieve analysis by defining sequence features that impact bnAb prevention efficacy.

AVAILABILITY

SLAPNAP is a freely available docker image that can be downloaded from DockerHub (https://hub.docker.com/r/slapnap/slapnap). Source code and documentation are available at GitHub (respectively, https://github.com/benkeser/slapnap and https://benkeser.github.io/slapnap/).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Helping individuals with firearm injuries: A cluster randomized trial

BACKGROUND

Patients with firearm injuries are at high risk of subsequent arrest and injury following hospital discharge. We sought to evaluate the effect of a 6-month joint hospital- and community-based low-intensity intervention on risk of arrest and injury among patients with firearm injuries.

METHODS

We conducted a cluster randomized controlled trial, enrolling patients with firearm injuries who received treatment at Harborview Medical Center, the level 1 trauma center in Seattle, Washington, were 18 years or older at the time of injury, spoke English, were able to provide consent and a method of contact, and lived in one of the five study counties. The intervention consisted of hospital-based motivational interviewing, followed by a 6-month community-based intervention, and multiagency support. The primary outcome was the risk of subsequent arrest. The main secondary outcome was the risk of death or subsequent injury requiring treatment in the emergency department or hospitalization.

RESULTS

Neither assignment to or engagement with the intervention, defined as having at least 1 contact point with the support specialist, was associated with risk of arrest at 2 years post-hospital discharge (relative risk for intervention assignment, 1.15; 95% confidence interval, 0.90-1.48; relative risk for intervention engagement, 1.07; 95% confidence interval, 0.74-2.19). There was similarly no association observed for subsequent injury.

CONCLUSIONS

This study represents one of the first randomized controlled trials of a joint hospital- and community-based intervention delivered exclusively among patients with firearm injuries. The intervention was not associated with changes in risk of arrest or injury, a finding most likely due to the low intensity of the program.

LEVEL OF EVIDENCE

Care management, level II.

Vaccine Efficacy of ALVAC-HIV and Bivalent Subtype C gp120-MF59 in Adults

BACKGROUND

A safe, effective vaccine is essential to eradicating human immunodeficiency virus (HIV) infection. A canarypox-protein HIV vaccine regimen (ALVAC-HIV plus AIDSVAX B/E) showed modest efficacy in reducing infection in Thailand. An analogous regimen using HIV-1 subtype C virus showed potent humoral and cellular responses in a phase 1-2a trial in South Africa. Efficacy data and additional safety data were needed for this regimen in a larger population in South Africa.

METHODS

In this phase 2b-3 trial, we randomly assigned 5404 adults without HIV-1 infection to receive the vaccine (2704 participants) or placebo (2700 participants). The vaccine regimen consisted of injections of ALVAC-HIV at months 0 and 1, followed by four booster injections of ALVAC-HIV plus bivalent subtype C gp120-MF59 adjuvant at months 3, 6, 12, and 18. The primary efficacy outcome was the occurrence of HIV-1 infection from randomization to 24 months.

RESULTS

In January 2020, prespecified criteria for nonefficacy were met at an interim analysis; further vaccinations were subsequently halted. The median age of the trial participants was 24 years; 70% of the participants were women. The incidence of adverse events was similar in the vaccine and placebo groups. During the 24-month follow-up, HIV-1 infection was diagnosed in 138 participants in the vaccine group and in 133 in the placebo group (hazard ratio, 1.02; 95% confidence interval, 0.81 to 1.30; P = 0.84).

CONCLUSIONS

The ALVAC-gp120 regimen did not prevent HIV-1 infection among participants in South Africa despite previous evidence of immunogenicity. (HVTN 702 ClinicalTrials.gov number, NCT02968849.).

Schistosoma mansoni Infection Is Associated With a Higher Probability of Tuberculosis Disease in HIV-Infected Adults in Kenya

BACKGROUND

Helminth infections can modulate immunity to Mycobacterium tuberculosis (Mtb). However, the effect of helminths, including Schistosoma mansoni (SM), on Mtb infection outcomes is less clear. Furthermore, HIV is a known risk factor for tuberculosis (TB) disease and has been implicated in SM pathogenesis. Therefore, it is important to evaluate whether HIV modifies the association between SM and Mtb infection.

SETTING

HIV-infected and HIV-uninfected adults were enrolled in Kisumu County, Kenya, between 2014 and 2017 and categorized into 3 groups based on Mtb infection status: Mtb-uninfected healthy controls, latent TB infection (LTBI), and active TB disease. Participants were subsequently evaluated for infection with SM.

METHODS

We used targeted minimum loss estimation and super learning to estimate a covariate-adjusted association between SM and Mtb infection outcomes, defined as the probability of being Mtb-uninfected healthy controls, LTBI, or TB. HIV status was evaluated as an effect modifier of this association.

RESULTS

SM was not associated with differences in baseline demographic or clinical features of participants in this study, nor with additional parasitic infections. Covariate-adjusted analyses indicated that infection with SM was associated with a 4% higher estimated proportion of active TB cases in HIV-uninfected individuals and a 14% higher estimated proportion of active TB cases in HIV-infected individuals. There were no differences in estimated proportions of LTBI cases.

CONCLUSIONS

We provide evidence that SM infection is associated with a higher probability of active TB disease, particularly in HIV-infected individuals.

Clinical Endpoints for Evaluating Efficacy in COVID-19 Vaccine Trials

Several vaccine candidates to protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (COVID-19) have entered or will soon enter large-scale, phase 3, placebo-controlled randomized clinical trials. To facilitate harmonized evaluation and comparison of the efficacy of these vaccines, a general set of clinical endpoints is proposed, along with considerations to guide the selection of the primary endpoints on the basis of clinical and statistical reasoning. The plausibility that vaccine protection against symptomatic COVID-19 could be accompanied by a shift toward more SARS-CoV-2 infections that are asymptomatic is highlighted, as well as the potential implications of such a shift.

Assessing Durability of Vaccine Effect Following Blinded Crossover in COVID-19 Vaccine Efficacy Trials

BACKGROUND

Several candidate vaccines to prevent COVID-19 disease have entered large-scale phase 3 placebo-controlled randomized clinical trials and some have demonstrated substantial short-term efficacy. Efficacious vaccines should, at some point, be offered to placebo participants, which will occur before long-term efficacy and safety are known.

METHODS

Following vaccination of the placebo group, we show that placebo-controlled vaccine efficacy can be derived by assuming the benefit of vaccination over time has the same profile for the original vaccine recipients and the placebo crossovers. This reconstruction allows estimation of both vaccine durability and potential vaccine-associated enhanced disease.

RESULTS

Post-crossover estimates of vaccine efficacy can provide insights about durability, identify waning efficacy, and identify late enhancement of disease, but are less reliable estimates than those obtained by a standard trial where the placebo cohort is maintained. As vaccine efficacy estimates for post-crossover periods depend on prior vaccine efficacy estimates, longer pre-crossover periods with higher case counts provide better estimates of late vaccine efficacy. Further, open-label crossover may lead to riskier behavior in the immediate crossover period for the unblinded vaccine arm, confounding vaccine efficacy estimates for all post-crossover periods.

CONCLUSIONS

We advocate blinded crossover and continued follow-up of trial participants to best assess vaccine durability and potential delayed enhancement of disease. This approach allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain participants on placebo, yet still allows important insights about immunological and clinical effectiveness over time.

Clinical Outcomes Among Patients With Drug-resistant Tuberculosis Receiving Bedaquiline- or Delamanid-Containing Regimens

BACKGROUND

Bedaquiline and delamanid are newly available drugs for treating multidrug-resistant tuberculosis (MDR-TB); however, there are limited data guiding their use and no comparison studies.

METHODS

We conducted a prospective, observational study among patients with MDR-TB in Georgia who were receiving a bedaquiline- or delamanid-based treatment regimen. Monthly sputum cultures, minimal inhibitory concentration testing, and adverse event monitoring were performed. Primary outcomes were culture conversion rates and clinical outcomes. Targeted maximum likelihood estimation and super learning were utilized to produce a covariate-adjusted proportion of outcomes for each regimen.

RESULTS

Among 156 patients with MDR-TB, 100 were enrolled and 95 were receiving a bedaquiline-based (n = 64) or delamanid-based (n = 31) regimen. Most were male (82%) and the median age was 38 years. Rates of previous treatment (56%) and cavitary disease (61%) were high. The most common companion drugs included linezolid, clofazimine, cycloserine, and a fluoroquinolone. The median numbers of effective drugs received among patients on bedaquiline-based (4; interquartile range [IQR], 4-4) and delamanid-based (4; IQR, 3.5-5) regimens were similar. Rates of acquired drug resistance were significantly higher among patients receiving delamanid versus bedaquiline (36% vs 10%, respectively; P < .01). Adjusted rates of sputum culture conversion at 2 months (67% vs 47%, respectively; P = .10) and 6 months (95% vs 74%, respectively; P < .01), as well as more favorable clinical outcomes (96% vs 72%, respectively; P < .01), were higher among patients receiving bedaquiline versus delamanid.

CONCLUSIONS

Among patients with MDR-TB, bedaquiline-based regimens were associated with higher rates of sputum culture conversion, more favorable outcomes, and a lower rate of acquired drug resistance versus delamanid-based regimens.

Design and analysis considerations for a sequentially randomized HIV prevention trial

TechStep is a randomized trial of a mobile health interventions targeted towards transgender adolescents. The interventions include a short message system, a mobile-optimized web application, and electronic counseling. The primary outcomes are self-reported sexual risk behaviors and uptake of HIV preventing medication. In order that we may evaluate the efficacy of several different combinations of interventions, the trial has a sequentially randomized design. We use a causal framework to formalize the estimands of the primary and key secondary analyses of the TechStep trial data. Targeted minimum loss-based estimators of these quantities are described and studied in simulation.

A machine learning-based approach for estimating and testing associations with multivariate outcomes

We propose a method for summarizing the strength of association between a set of variables and a multivariate outcome. Classical summary measures are appropriate when linear relationships exist between covariates and outcomes, while our approach provides an alternative that is useful in situations where complex relationships may be present. We utilize machine learning to detect nonlinear relationships and covariate interactions and propose a measure of association that captures these relationships. A hypothesis test about the proposed associative measure can be used to test the strong null hypothesis of no association between a set of variables and a multivariate outcome. Simulations demonstrate that this hypothesis test has greater power than existing methods against alternatives where covariates have nonlinear relationships with outcomes. We additionally propose measures of variable importance for groups of variables, which summarize each groups' association with the outcome. We demonstrate our methodology using data from a birth cohort study on childhood health and nutrition in the Philippines.

Technology-Based Stepped Care to Stem Transgender Adolescent Risk Transmission: Protocol for a Randomized Controlled Trial (TechStep)

BACKGROUND

Transgender youth demonstrate significantly higher rates of engagement in sexual risk behaviors relative to their cisgender or gender-conforming counterparts, including high rates of condomless anal intercourse and engagement in sex work. In addition, transgender youth experience increased physical or sexual abuse, victimization, substance use, mental health disorders, incarceration, and homelessness. Owing to these syndemic health disparities, transgender youth are at substantially increased risk of HIV infection.

OBJECTIVE

This protocol aims to describe a randomized controlled trial (RCT), Adolescent Medicine Trials Network 160 TechStep (N=250), which assesses the differential immediate and sustained effects of each of 3 conditions (text messaging, WebApp, or information-only control) for reducing sexual risk behaviors and increasing pre-exposure prophylaxis (PrEP) uptake among high-risk, HIV-negative transgender youth and young adults (aged 15-24 years).

METHODS

Participants will be recruited through web-based (targeted social media sites and apps) and offline (print ads and flyers) advertisements, peer and clinic referrals, and street- and venue-based outreach, and by contacting potential participants who have requested contact for future studies. Participants will be randomized into 1 of the 3 conditions: (1) text messaging, (2) WebApp, or (3) information-only control for 6 months. Assessments will occur at baseline and at 3, 6, and 9 months. Participants who do not show improvements in sexual risk or PrEP uptake at the 3-month assessment will be rerandomized to receive weekly electronic coaching (eCoaching) sessions in addition to their assigned text messaging or WebApp intervention, or remain in the original text messaging or WebApp intervention using a 2:1 ratio. Participants originally assigned to the information-only condition are not eligible for rerandomization.

RESULTS

Funding for TechStep was awarded in June 2017. Phase 1 was approved by the Institutional Review Board (IRB) in April 2018. Recruitment began in November 2018 for phase 1, the formative phase. Initial phase 2 IRB approval came in June 2019. The data collection for phase 2, the RCT, is expected to be completed in April 2021. As of March 2020, 54 participants have been enrolled in TechStep. The final results are anticipated in May 2021.

CONCLUSIONS

By providing culturally responsive, technology-based interventions, TechStep aims to improve sexual health outcomes among HIV-negative transgender youth and young adults at high risk of HIV. TechStep will evaluate the efficacy of technology-based interventions for reducing HIV sexual risk behaviors and increasing PrEP initiation, adherence, and persistence. The suite of technology-based interventions developed in TechStep, and assessed for efficacy in a 3-condition RCT, represents an important advancement in intervention science toward developing tailored and scalable interventions for transgender youth and young adults.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04000724; http://clinicaltrials.gov/ct2/show/NCT04000724.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/18326.

Assessing trends in vaccine efficacy by pathogen genetic distance

Preventive vaccines are an effective public health intervention for reducing the burden of infectious diseases, but have yet to be developed for several major infectious diseases. Vaccine sieve analysis studies whether and how the efficacy of a vaccine varies with the genetics of the infectious pathogen, which may help guide future vaccine development and deployment. A standard statistical approach to sieve analysis compares the effect of the vaccine to prevent infection and disease caused by pathogen types defined dichotomously as genetically near or far from a reference pathogen strain inside the vaccine construct. For example, near may be defined by amino acid identity at all amino acid positions considered in a multiple alignment and far defined by at least one amino acid difference. An alternative approach is to study the efficacy of the vaccine as a function of genetic distance from a pathogen to a reference vaccine strain where the distance cumulates over the set of amino acid positions. We propose a nonparametric method for estimating and testing the trend in the effect of a vaccine across genetic distance. We illustrate the operating characteristics of the estimator via simulation and apply the method to a recent preventive malaria vaccine efficacy trial.

Assessing differential impacts of COVID-19 on black communities

Purpose

Given incomplete data reporting by race, we used data on COVID-19 cases and deaths in U.S. counties to describe racial disparities in COVID-19 disease and death and associated determinants.

Methods

Using publicly available data (accessed April 13, 2020), predictors of COVID-19 cases and deaths were compared between disproportionately (≥13%) black and all other (<13% black) counties. Rate ratios were calculated, and population attributable fractions were estimated using COVID-19 cases and deaths via zero-inflated negative binomial regression model. National maps with county-level data and an interactive scatterplot of COVID-19 cases were generated.

Results

Nearly 90% of disproportionately black counties (656/677) reported a case and 49% (330/677) reported a death versus 81% (1987/2465) and 28% (684/2465), respectively, for all other counties. Counties with higher proportions of black people have higher prevalence of comorbidities and greater air pollution. Counties with higher proportions of black residents had more COVID-19 diagnoses (Rate Ratio (RR): 1.24, 95% confidence interval: 1.17-1.33) and deaths (RR: 1.18, 95% confidence interval: 1.00-1.40), after adjusting for county-level characteristics such as age, poverty, comorbidities, and epidemic duration. COVID-19 deaths were higher in disproportionally black rural and small metro counties. The population attributable fraction of COVID-19 diagnosis due to lack of health insurance was 3.3% for counties with less than 13% black residents and 4.2% for counties with greater than or equal to 13% black residents.

Conclusions

Nearly 20% of U.S. counties are disproportionately black, and they accounted for 52% of COVID-19 diagnoses and 58% of COVID-19 deaths nationally. County-level comparisons can both inform COVID-19 responses and identify epidemic hot spots. Social conditions, structural racism, and other factors elevate risk for COVID-19 diagnoses and deaths in black communities.

Assessing differential impacts of COVID-19 on black communities

PURPOSE

Given incomplete data reporting by race, we used data on COVID-19 cases and deaths in U.S. counties to describe racial disparities in COVID-19 disease and death and associated determinants.

METHODS

Using publicly available data (accessed April 13, 2020), predictors of COVID-19 cases and deaths were compared between disproportionately (≥13%) black and all other (<13% black) counties. Rate ratios were calculated, and population attributable fractions were estimated using COVID-19 cases and deaths via zero-inflated negative binomial regression model. National maps with county-level data and an interactive scatterplot of COVID-19 cases were generated.

RESULTS

Nearly 90% of disproportionately black counties (656/677) reported a case and 49% (330/677) reported a death versus 81% (1987/2465) and 28% (684/2465), respectively, for all other counties. Counties with higher proportions of black people have higher prevalence of comorbidities and greater air pollution. Counties with higher proportions of black residents had more COVID-19 diagnoses (Rate Ratio (RR): 1.24, 95% confidence interval: 1.17-1.33) and deaths (RR: 1.18, 95% confidence interval: 1.00-1.40), after adjusting for county-level characteristics such as age, poverty, comorbidities, and epidemic duration. COVID-19 deaths were higher in disproportionally black rural and small metro counties. The population attributable fraction of COVID-19 diagnosis due to lack of health insurance was 3.3% for counties with less than 13% black residents and 4.2% for counties with greater than or equal to 13% black residents.

CONCLUSIONS

Nearly 20% of U.S. counties are disproportionately black, and they accounted for 52% of COVID-19 diagnoses and 58% of COVID-19 deaths nationally. County-level comparisons can both inform COVID-19 responses and identify epidemic hot spots. Social conditions, structural racism, and other factors elevate risk for COVID-19 diagnoses and deaths in black communities.