Variation in dengue virus plaque reduction neutralization testing: systematic review and pooled analysis.

BackgroundThe plaque reduction neutralization test (PRNT) remains the gold standard for the detection of serologic immune responses to dengue virus (DENV). While the basic concept of the PRNT remains constant, this test has evolved in multiple laboratories, introducing variation in materials and methods. Despite the importance of laboratory-to-laboratory comparability in DENV vaccine development, the effects of differing PRNT techniques on assay results, particularly the use of different dengue strains within a serotype, have not been fully characterized.MethodsWe conducted a systematic review and pooled analysis of published literature reporting individual-level PRNT titers to identify factors associated with heterogeneity in PRNT results and compared variation between strains within DENV serotypes and between articles using hierarchical models.ResultsThe literature search and selection criteria identified 8 vaccine trials and 25 natural exposure studies reporting 4,411 titers from 605 individuals using 4 different neutralization percentages, 3 cell lines, 12 virus concentrations and 51 strains. Of 1,057 titers from primary DENV exposure, titers to the exposure serotype were consistently higher than titers to non-exposure serotypes. In contrast, titers from secondary DENV exposures (n = 628) demonstrated high titers to exposure and non-exposure serotypes. Additionally, PRNT titers from different strains within a serotype varied substantially. A pooled analysis of 1,689 titers demonstrated strain choice accounted for 8.04% (90% credible interval [CrI]: 3.05%, 15.7%) of between-titer variation after adjusting for secondary exposure, time since DENV exposure, vaccination and neutralization percentage. Differences between articles (a proxy for inter-laboratory differences) accounted for 50.7% (90% CrI: 30.8%, 71.6%) of between-titer variance.ConclusionsAs promising vaccine candidates arise, the lack of standardized assays among diagnostic and research laboratories make unbiased inferences about vaccine-induced protection difficult. Clearly defined, widely accessible reference reagents, proficiency testing or algorithms to adjust for protocol differences would be a useful first step in improving dengue PRNT comparability and quality assurance

Urban Outbreak 2019 Pandemic Response: Select Research & Game Findings

This document is a summary of 16 key research and game findings focused specifically on the characteristics of civil-military response to a pandemic scenario. The numbered bullets below correspond to more detailed explanations of findings presented later in the document. While these findings are in no way definitive or complete, they are a sampling of relevant guidance based on research, gaming and expert opinion. It is our hope that these 16 findings will contribute to improving civilian and military effectiveness in humanitarian assistance and disaster response operationshttps://digital-commons.usnwc.edu/civmilresponse-program-sims-uo-2019/1001/thumbnail.jp

Immunologic Risk Factors for Early Mortality After Starting Antiretroviral Therapy in HIV-Infected Zambian Children

To explore immunologic risk factors for death within 90 days of highly active antiretroviral therapy (HAART) initiation, CD4+ and CD8+ T cell subsets were measured by flow cytometry and characterized by logistic regression in 149 Zambian children between 9 months and 10 years of age enrolled in a prospective, observational study of the impact of HAART on measles immunity. Of 21 children who died during follow-up, 17 (81%) had known dates of death and 16 (76%) died within 90 days of initiating HAART. Young age and low weight-for-age z-scores were associated with increased risks of mortality within 90 days of starting HAART, whereas CD4+ T cell percentage was not associated with mortality. After adjusting for these factors, each 10% increase in CD8+ effector T cells increased the odds of overall mortality [OR=1.43 (95% CI: 1.08, 1.90)] and was marginally associated with early mortality [OR=1.29 (95% CI: 0.97, 1.72)]. Conversely, each 10% increase in CD4+ central memory T cells decreased the odds of overall [OR=0.06 (95% CI: 0.01, 0.59)] and early mortality [OR=0.09 (95% CI: 0.01, 0.97)]. Logistic regression prediction models demonstrated areas under the receiver-operator characteristic curves of ≥85% for early and overall mortality, with bootstrapped sensitivities of 82–85% upon validation, supporting the predictive accuracy of the models. CD4+ and CD8+ T cell subsets may be more accurate predictors of early mortality than CD4+ T cell percentages and could be used to identify children who would benefit from more frequent clinical monitoring after initiating HAART

Variability in dengue titer estimates from plaque reduction neutralization tests poses a challenge to epidemiological studies and vaccine development.

BACKGROUND: Accurate determination of neutralization antibody titers supports epidemiological studies of dengue virus transmission and vaccine trials. Neutralization titers measured using the plaque reduction neutralization test (PRNT) are believed to provide a key measure of immunity to dengue viruses, however, the assay's variability is poorly understood, making it difficult to interpret the significance of any assay reading. In addition there is limited standardization of the neutralization evaluation point or statistical model used to estimate titers across laboratories, with little understanding of the optimum approach. METHODOLOGY/PRINCIPAL FINDINGS: We used repeated assays on the same two pools of serum using five different viruses (2,319 assays) to characterize the variability in the technique under identical experimental conditions. We also assessed the performance of multiple statistical models to interpolate continuous values of neutralization titer from discrete measurements from serial dilutions. We found that the variance in plaque reductions for individual dilutions was 0.016, equivalent to a 95% confidence interval of 0.45-0.95 for an observed plaque reduction of 0.7. We identified PRNT75 as the optimum evaluation point with a variance of 0.025 (log10 scale), indicating a titer reading of 1∶500 had 95% confidence intervals of 1∶240-1∶1000 (2.70±0.31 on a log10 scale). The choice of statistical model was not important for the calculation of relative titers, however, cloglog regression out-performed alternatives where absolute titers are of interest. Finally, we estimated that only 0.7% of assays would falsely detect a four-fold difference in titers between acute and convalescent sera where no true difference exists. CONCLUSIONS: Estimating and reporting assay uncertainty will aid the interpretation of individual titers. Laboratories should perform a small number of repeat assays to generate their own variability estimates. These could be used to calculate confidence intervals for all reported titers and allow benchmarking of assay performance

Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Very early combination antiretroviral therapy in infants: prospects for cure

PURPOSE OF REVIEW: A single case of sustained HIV control in the absence of antiretroviral therapy or HIV-specific immune responses ensued following 18 months of combination antiretroviral therapy initiated at 30 h of age in a perinatally HIV-infected child (the Mississippi child). This case provides proof-of-concept that delay in HIV viremic rebound may ensue following very early treatment (VET) in perinatal infection, likely through marked reduction of latent replication-competent HIV reservoirs. RECENT FINDINGS: The latent HIV reservoir remains the critical barrier to remission. Several studies indicate that the earlier effective combination antiretroviral therapy is initiated, the smaller the size of the HIV reservoir. The unique ability of perinatally infected neonates to initiate VET at the time of birth maximizes the potential benefits of limiting latent reservoir size and permitting reservoir decay, likely lengthening the duration of remission and limiting the capacity for re-establishment of viremia. SUMMARY: This article covers the rationale and feasibility of VET to achieve sustained virologic remission in perinatal infection. Recent studies highlighting the effects of VET on biomarkers of HIV persistence in perinatal HIV infection are reviewed as well as implications and challenges for cure research in pediatric populations