scholarly journals Covid-19 Vaccine Efficacy: Accuracy, Uncertainty and Projection of Cases

2020 ◽  
Author(s):  
Wenjiang Fu ◽  
Jieni Li ◽  
Paul Scheet
Keyword(s):  
Confidence Intervals ◽  
Vaccine Efficacy ◽  
Accuracy Assessment ◽  
Point Estimate ◽  
Societal Impact ◽  
Limited Information ◽  
Interim Report ◽  
Vaccine Candidates ◽  
Vaccine Trials ◽  
Point Estimates

ABSTRACTBackgroundTwo vaccine candidates for coronavirus disease 2019 (Covid-19) have been announced by Pfizer-BioNTech and Moderna with above 90% efficacy. The efficacy of each vaccine changes between reports with no accuracy assessment.MethodsWe examined data in both vaccine trials, provided 95% confidence intervals, and projected the cases that would be prevented in communities of multi-million population.ResultsThe 95% confidence intervals reveal that the true vaccine efficacy could be as low as 86% for stated efficacy of 94.4% in an interim report, indicating the inaccuracy and uncertainty of efficacy point estimate. Both vaccines achieve an efficacy above 89% by the 95% confidence interval in updated reports. The Moderna vaccine would prevent more than 50,260 cases in communities of 1 million people with 1 year exposure.ConclusionsPoint estimates of vaccine efficacy transmit limited information. Corresponding statements of uncertainty, such as confidence intervals, should be provided and included in discussions of societal impact. The Covid-19 vaccines announced to date would prevent a substantial number of cases even at lower ends of the intervals.

scholarly journals Is it Possible to Find a Good Point Estimate of a Calibrated Radiocarbon Date?

Radiocarbon ◽  
2007 ◽  
Vol 49 (2) ◽  
pp. 393-401 ◽  
Author(s):  
Adam Michczyński
Keyword(s):  
Computer Simulation ◽  
Confidence Intervals ◽  
Single Point ◽  
Radiocarbon Date ◽  
Point Estimate ◽  
Local Mode ◽  
True Value ◽  
Point Estimates ◽  
Good Point ◽  
Accepted Practice

The result from probabilistic calibration of a radiocarbon date is given in the form of a probability density function. Consequently, reporting a 68% or 95% confidence interval has became a commonly accepted practice. However, many users of 14C dates still try to present the results of calibration as a single point. This manner of presentation is often applied during the construction of age-depth models due to its convenience and simplicity. In this paper, the author tests whether it is possible to find a good point estimate of a calibrated 14C date. The idea of the tests is to compare, using computer simulation, the true value of the calendar age with the age calculated based on the probabilistic calibration of the 14C date and the method of finding the point estimate. The test is carried out for the following point estimates: mode, median, average, the central point of the confidence intervals, and the local mode inside the confidence intervals. The results show that none of these may be considered as a good estimate.

scholarly journals The O-Ag Antibody Response to Francisella Is Distinct in Rodents and Higher Animals and Can Serve as a Correlate of Protection

Pathogens ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1646
Author(s):  
Lauren E. Shoudy ◽  
Prachi Namjoshi ◽  
Gabriela Giordano ◽  
Sudeep Kumar ◽  
Jennifer D. Bowling ◽  
...  
Keyword(s):  
Vaccine Efficacy ◽  
Low Dose ◽  
High Sensitivity ◽  
High Dose ◽  
Live Vaccine Strain ◽  
Plasma Samples ◽  
Vaccine Candidates ◽  
Correlates Of Protection ◽  
Vaccine Trials ◽  
Bona Fide

Identifying correlates of protection (COPs) for vaccines against lethal human (Hu) pathogens, such as Francisella tularensis (Ft), is problematic, as clinical trials are currently untenable and the relevance of various animal models can be controversial. Previously, Hu trials with the live vaccine strain (LVS) demonstrated ~80% vaccine efficacy against low dose (~50 CFU) challenge; however, protection deteriorated with higher challenge doses (~2000 CFU of SchuS4) and no COPs were established. Here, we describe our efforts to develop clinically relevant, humoral COPs applicable to high-dose, aerosol challenge with S4. First, our serosurvey of LVS-vaccinated Hu and animals revealed that rabbits (Rbs), but not rodents, recapitulate the Hu O-Ag dependent Ab response to Ft. Next, we assayed Rbs immunized with distinct S4-based vaccine candidates (S4ΔclpB, S4ΔguaBA, and S4ΔaroD) and found that, across multiple vaccines, the %O-Ag dep Ab trended with vaccine efficacy. Among S4ΔguaBA-vaccinated Rbs, the %O-Ag dep Ab in pre-challenge plasma was significantly higher in survivors than in non-survivors; a cut-off of >70% O-Ag dep Ab predicted survival with high sensitivity and specificity. Finally, we found this COP in 80% of LVS-vaccinated Hu plasma samples as expected for a vaccine with 80% Hu efficacy. Collectively, the %O-Ag dep Ab response is a bona fide COP for S4ΔguaBA-vaccinated Rb and holds significant promise for guiding vaccine trials with higher animals.

scholarly journals Analyzing Vaccine Trials in Epidemics with Mild and Asymptomatic Infection

2018 ◽  
Author(s):  
Rebecca Kahn ◽  
Matt Hitchings ◽  
Rui Wang ◽  
Steven Bellan ◽  
Marc Lipsitch
Keyword(s):  
Vaccine Efficacy ◽  
Cox Model ◽  
Vaccine Trial ◽  
Asymptomatic Infection ◽  
Limited Information ◽  
Susceptibility To Infection ◽  
Vaccine Trials ◽  
Interval Censored ◽  
Congenital Zika Syndrome ◽  
Biased Estimates

ABSTRACTVaccine efficacy against susceptibility to infection (VES), regardless of symptoms, is an important endpoint of vaccine trials for pathogens with a high proportion of asymptomatic infection, as such infections may contribute to onward transmission and outcomes such as Congenital Zika Syndrome. However, estimating VESis resource-intensive. We aim to identify methods to accurately estimate VEswhen limited information is available and resources are constrained. We model an individually randomized vaccine trial by generating a network of individuals and simulating an epidemic. The disease natural history follows a Susceptible, Exposed, Infectious and Symptomatic or Infectious and Asymptomatic, Recovered model. We then use seven approaches to estimate VES, and we also estimate vaccine efficacy against progression to symptoms (VEP). A corrected relative risk and an interval censored Cox model accurately estimate VESand only require serologic testing of participants once, while a Cox model using only symptomatic infections returns biased estimates. Only acquiring serological endpoints in a 10% sample and imputing the remaining infection statuses yields unbiased VESestimates across values of R0and accurate estimates of VEPfor higher values. Identifying resource-preserving methods for accurately estimating VESis important in designing trials for diseases with a high proportion of asymptomatic infection.

scholarly journals Summary Plots With Adjusted Error Bars: The superb Framework With an Implementation in R

2021 ◽  
Vol 4 (3) ◽  
pp. 251524592110351
Author(s):  
Denis Cousineau ◽  
Marc-André Goulet ◽  
Bradley Harding
Keyword(s):  
Experimental Design ◽  
Open Access ◽  
Confidence Intervals ◽  
Repeated Measures ◽  
Statistical Tests ◽  
Effect Sizes ◽  
Limited Information ◽  
Sampling Methodology ◽  
Point Estimates ◽  
Error Bars

Plotting the data of an experiment allows researchers to illustrate the main results of a study, show effect sizes, compare conditions, and guide interpretations. To achieve all this, it is necessary to show point estimates of the results and their precision using error bars. Often, and potentially unbeknownst to them, researchers use a type of error bars—the confidence intervals—that convey limited information. For instance, confidence intervals do not allow comparing results (a) between groups, (b) between repeated measures, (c) when participants are sampled in clusters, and (d) when the population size is finite. The use of such stand-alone error bars can lead to discrepancies between the plot’s display and the conclusions derived from statistical tests. To overcome this problem, we propose to generalize the precision of the results (the confidence intervals) by adjusting them so that they take into account the experimental design and the sampling methodology. Unfortunately, most software dedicated to statistical analyses do not offer options to adjust error bars. As a solution, we developed an open-access, open-source library for R— superb—that allows users to create summary plots with easily adjusted error bars.

scholarly journals Contrasting Adult and Infant Immune Responses to HIV Infection and Vaccination

2015 ◽  
Vol 23 (2) ◽  
pp. 84-94 ◽  
Author(s):  
David R. Martinez ◽  
Sallie R. Permar ◽  
Genevieve G. Fouda
Keyword(s):  
Immune Responses ◽  
Hiv Infection ◽  
Vaccine Efficacy ◽  
Neutralizing Antibody ◽  
Hiv Vaccine ◽  
Antibody Responses ◽  
Hiv Vaccines ◽  
Vaccine Candidates ◽  
Protective Antibodies ◽  
Pediatric Populations

ABSTRACTExtensive studies have demonstrated that infant immune responses are distinct from those of adults. Despite these differences, infant immunization can elicit protective immune responses at levels comparable to or, in some cases, higher than adult immune responses to many vaccines. To date, only a few HIV vaccine candidates have been tested in infant populations, and none of them evaluated vaccine efficacy. Recent exciting studies showing that HIV-infected infants can develop broad neutralizing antibody responses and that some HIV vaccine regimens can elicit high levels of potentially protective antibodies in infants provide support for the development and testing of HIV vaccines in pediatric populations. In this review, we discuss the differences in adult and infant immune responses in the setting of HIV infection and vaccination.

Hollywood Rules

2017 ◽  
pp. 1-9
Author(s):  
Karl Schmedders ◽  
Charlotte Snyder ◽  
Ute Schaedel
Keyword(s):  
Confidence Intervals ◽  
Statistical Methods ◽  
Regression Models ◽  
Functional Form ◽  
Hedge Fund ◽  
Fund Manager ◽  
Wall Street ◽  
Independent Variables ◽  
Point Estimates ◽  
Hedge Fund Manager

Wall Street hedge fund manager Kim Meyer is considering investing in an SFA (slate financing arrangement) in Hollywood. Dave Griffith, a Hollywood producer, is pitching for the investment and has conducted a broad analysis of recent movie data to determine the important drivers of a movie’s success. In order to convince Meyer to invest in an SFA, Griffith must anticipate possible questions to maximize his persuasiveness.Students will analyze the factors driving a movie’s revenue using various statistical methods, including calculating point estimates, computing confidence intervals, conducting hypothesis tests, and developing regression models (in which they must both choose the relevant set of independent variables as well as determine an appropriate functional form for the regression equation). The case also requires the interpretation of the quantitative findings in the context of the application.

scholarly journals Earthquake forecasting: statistics and information

2016 ◽  
Vol 58 (6) ◽  
Author(s):  
Vladimir Gertsik ◽  
Mark Kelbert ◽  
Anatoly Krichevets
Keyword(s):  
Confidence Intervals ◽  
Decision Rule ◽  
Random Fields ◽  
Axiomatic Approach ◽  
Earthquake Forecasting ◽  
Alarm System ◽  
Conditional Probabilities ◽  
Mathematical Basis ◽  
Strong Earthquakes ◽  
Point Estimates

<div class="abstract"><div class="abstract_item"><p>The paper presents a decision rule forming a mathematical basis of earthquake forecasting problem. We develop an axiomatic approach to earthquake forecasting in terms of multicomponent random fields on a lattice. This approach provides a method for constructing point estimates and confidence intervals for conditional probabilities of strong earthquakes under conditions on the levels of precursors. Also, it provides an approach for setting a multilevel alarm system and hypothesis testing for binary alarms. We use a method of comparison for different algorithms of earthquake forecasts in terms of the increase of Shannon information. ‘Forecasting’ (the calculation of the probabilities) and ‘prediction’ (the alarm declaring) of earthquakes are equivalent in this approach.</p></div></div>

scholarly journals Two-Stage Single-Arm Trials Are Rarely Analyzed Effectively or Reported Adequately

2021 ◽  
pp. 1813-1820
Author(s):  
Michael J. Grayling ◽  
Adrian P. Mander
Keyword(s):  
Final Stage ◽  
Interim Analysis ◽  
Primary Outcome ◽  
Point Estimate ◽  
Two Stage ◽  
Stage Design ◽  
Patient Subgroup ◽  
Future Studies ◽  
Point Estimates ◽  
Outcome Trial

PURPOSE Two-stage single-arm designs have historically been the most common design used in phase II oncology. They remain a mainstay today, particularly for trials in rare subgroups. Consequently, it is imperative such studies be designed, analyzed, and reported effectively. We comprehensively review such trials to examine whether this is the case. METHODS Oncology trials that used Simon's two-stage design over a 5-year period were identified and reviewed. They were evaluated for whether they reported sufficient design (eg, required sample size) and analysis (eg, CI) details. Articles that did not adjust their inference for the incorporation of an interim analysis were also reanalyzed. RESULTS Four-hundred twenty-five articles were included. Of these, just 47.5% provided the five components that ensure design reproducibility. Only 1.2% and 2.1% reported an adjusted point estimate or CI, respectively. Just 55.3% provided the final stage rejection bound, indicating many trials did not test a hypothesis for their primary outcome. Trial reanalyses suggested reported point estimates underestimated treatment effects and reported CIs were too narrow. CONCLUSION Key design details of two-stage single-arm trials are often unreported. Their inference is rarely performed such as to remove bias introduced by the interim analysis. These findings are particular alarming when considered against the growing trend in which nonrandomized trials make up a large proportion of all evidence on a treatment's effectiveness in a rare biomarker-defined patient subgroup. Future studies must improve the way they are analyzed and reported.

Null Hypothesis Significance Testing: Ramifications, Ruminations and Recommendations

2005 ◽  
Vol 35 (1) ◽  
pp. 1-20 ◽  
Author(s):  
G. K. Huysamen
Keyword(s):  
Sample Size ◽  
Confidence Intervals ◽  
Effect Size ◽  
Null Hypothesis ◽  
Significance Testing ◽  
Population Parameter ◽  
Size Estimation ◽  
Null Hypothesis Significance Testing ◽  
Point Estimates ◽  
Size Estimates

Criticisms of traditional null hypothesis significance testing (NHST) became more pronounced during the 1960s and reached a climax during the past decade. Among others, NHST says nothing about the size of the population parameter of interest and its result is influenced by sample size. Estimation of confidence intervals around point estimates of the relevant parameters, model fitting and Bayesian statistics represent some major departures from conventional NHST. Testing non-nil null hypotheses, determining optimal sample size to uncover only substantively meaningful effect sizes and reporting effect-size estimates may be regarded as minor extensions of NHST. Although there seems to be growing support for the estimation of confidence intervals around point estimates of the relevant parameters, it is unlikely that NHST-based procedures will disappear in the near future. In the meantime, it is widely accepted that effect-size estimates should be reported as a mandatory adjunct to conventional NHST results.

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