scholarly journals First indication of the effect of COVID-19 vaccinations on the course of the outbreak in Israel

2021 ◽  
Author(s):  
H. De-Leon ◽  
R. Calderon-Margalit ◽  
F. Pederiva ◽  
Y. Ashkenazy ◽  
D. Gazit
Keyword(s):  
Data Analysis ◽  
Elderly Population ◽  
Vaccine Coverage ◽  
Simulated Data ◽  
Vulnerable Population ◽  
Clinical Disease ◽  
Vaccination Program ◽  
Disease Dynamics ◽  
Observable Change

AbstractConcomitantly with rolling out its rapid COVID-19 vaccine program, Israel is experiencing its third, and so far largest, surge in morbidity. We aimed to estimate whether the high vaccine coverage among individuals aged over 60 years old creates an observable change in disease dynamics. Using observed and simulated data, we suggest that the shape of the outbreak as measured by daily new moderate and severe cases, and in particular of patients aged over 60, has changed because of vaccination, bringing the decline in new moderate and severe cases earlier than expected, by about a week. Our analyses is consistent with the assumption that vaccination lead to higher than 50% protection in preventing clinical disease and with at least some effectiveness in blocking transmission of elderly population, and supports the importance of prioritizing vulnerable population. This is the first indication of the effectivity of COVID-19 vaccine in changing the course of an ongoing pandemic outbreak.One Sentence SummaryWe show, by data analysis and modelling of the dynamics of COVID-19 pandemic in Israel, that the current nationwide outbreak, that had up to 0.1% of the population confirmed daily, is clearly affected by the vaccination program, that reached a coverage of more than 80% among people ≥ 60 years old.

scholarly journals Bayesian modeling and significant features exploration in wavelet power spectra

2007 ◽  
Vol 14 (1) ◽  
pp. 79-88 ◽  
Author(s):  
D. V. Divine ◽  
F. Godtliebsen
Keyword(s):  
Data Analysis ◽  
Traditional Approach ◽  
Statistical Significance ◽  
Power Spectra ◽  
Simulated Data ◽  
Scale Space ◽  
Independent Random Variables ◽  
Discrete Wavelet ◽  
Wavelet Coefficients ◽  
Testing Procedures

Abstract. This study proposes and justifies a Bayesian approach to modeling wavelet coefficients and finding statistically significant features in wavelet power spectra. The approach utilizes ideas elaborated in scale-space smoothing methods and wavelet data analysis. We treat each scale of the discrete wavelet decomposition as a sequence of independent random variables and then apply Bayes' rule for constructing the posterior distribution of the smoothed wavelet coefficients. Samples drawn from the posterior are subsequently used for finding the estimate of the true wavelet spectrum at each scale. The method offers two different significance testing procedures for wavelet spectra. A traditional approach assesses the statistical significance against a red noise background. The second procedure tests for homoscedasticity of the wavelet power assessing whether the spectrum derivative significantly differs from zero at each particular point of the spectrum. Case studies with simulated data and climatic time-series prove the method to be a potentially useful tool in data analysis.

Vaccine effectiveness of Pfizer-BioNTech and Oxford-AstraZeneca to prevent severe COVID-19 in Costa Rica: A nationwide, observational study of hospitalizations prevalence (Preprint)

2021 ◽  
Author(s):  
Luis Rosero-Bixby
Keyword(s):  
Single Dose ◽  
Costa Rica ◽  
Observational Study ◽  
Real World ◽  
Vaccine Coverage ◽  
Secondary Analysis ◽  
Vaccine Effectiveness ◽  
Costa Rican ◽  
Vaccination Program ◽  
Severe Illness

BACKGROUND The Costa Rican vaccination program uses Pfizer-BioNTech and Oxford-AstraZeneca vaccines. Real-world estimates of these vaccines effectiveness to prevent hospitalizations range from 90% to 98% for two doses and from 70% to 91% for a single dose. Almost all of these estimates predate the Delta variant. OBJECTIVE To estimate the dose-dependent effectiveness of coronavirus disease (COVID-19) vaccines to prevent severe illness in real-world conditions of Costa Rica, after the Delta variant became dominant. METHODS This observational study is a secondary analysis of hospitalizations prevalence. The participants are all 3.67 million adults residents in Costa Rica by mid-2021. The study is based on public aggregated data of 5978 COVID-19-related hospital records from 14th September to 20th October, 2021 and 6.1 million vaccination doses administered to determine hospitalization prevalence by dose-specific vaccination status. The intervention retrospectively evaluated is vaccination with Pfizer-BioNTech (78%) and Oxford-AstraZeneca (22%). The main outcome studied is being hospitalized. RESULTS Vaccine effectiveness to prevent hospitalization (VEH) was estimated as 93.4% (95% confidence interval [CI]: 93.0 to 93.9) for complete vaccination and 76.7% (CI: 75.0 to 78.3) for single-dose vaccination among adults of all ages. VEH was lower and more uncertain among older adults aged 58 years and above: 92% (CI: 91% to 93%) for those who had received full vaccination and 64% (CI: 58% to 69%) for those who had received partial vaccination. Single-dose VEH declined over time during the study period, especially in the older age group. Estimates were sensitive to possible errors in the population count used to determine the residual number of unvaccinated people when vaccine coverage is high. CONCLUSIONS The Costa Rican vaccination program that administered Pfizer and Oxford vaccines are highly effective to prevent COVID-19-related hospitalizations after the Delta variant had become dominant. Moreover, a single dose is reasonably effective, justifying the continuation of the national policy of postponing the application for the second dose of the Pfizer vaccine to accelerate the vaccination and increase the number of people being vaccinated. Timely monitoring of vaccine effectiveness is important to detect eventual failures and motivate the public based on information that the vaccinations are effective.

scholarly journals Cost-effectiveness of a bivalent human papillomavirus vaccination program in Japan

Sexual Health ◽  
2015 ◽  
Vol 12 (6) ◽  
pp. 520 ◽  
Author(s):  
Luke B. Connelly ◽  
Ha N. D. Le
Keyword(s):  
Cervical Cancer ◽  
Human Papillomavirus ◽  
Cost Effectiveness ◽  
Screening Program ◽  
Vaccine Coverage ◽  
Precancerous Lesions ◽  
Hpv Vaccination ◽  
Vaccination Program ◽  
Human Papillomavirus Vaccination ◽  
The Cost

Background Human papillomavirus (HPV) vaccines and their widespread adoption have the potential to relieve a large part of the burden of cervical cancer morbidity and mortality, particularly in countries that have low screening rates or, like Japan, lack a cohesive universal screening program. An economic evaluation was conducted to assess the cost-effectiveness of introducing a bivalent HPV vaccination program in Japan from a healthcare perspective. Methods: A Markov model of the natural history of HPV infection that incorporates both vaccination and screening was developed for Japan. The modelled intervention, a bivalent HPV vaccine with a 100% lifetime vaccine efficacy and 80% vaccine coverage, given to a cohort of 12-year-old Japanese girls in conjunction with the current screening program, was compared with screening alone in terms of costs and effectiveness. A discount rate of 5% was applied to both costs and utilities where relevant. Results: Vaccination alongside screening compared with screening alone is associated with an incremental cost-effectiveness ratio (ICER) of US$20 315 per quality-adjusted-life-year gained if 80% coverage is assumed. The ICER at 5% coverage with the vaccine plus screening, compared with screening alone, is US$1158. Conclusion: The cost-effectiveness results suggest that the addition of a HPV vaccination program to Japan’s cervical cancer screening program is highly likely to prove a cost-effective way to reduce the burden of cervical cancer, precancerous lesions and HPV16/18-related diseases.

scholarly journals Intragenic Conflict in Phylogenomic Data Sets

2020 ◽  
Vol 37 (11) ◽  
pp. 3380-3388
Author(s):  
Stephen A Smith ◽  
Nathanael Walker-Hale ◽  
Joseph F Walker
Keyword(s):  
Data Analysis ◽  
Empirical Data ◽  
Evolutionary History ◽  
Phylogenetic Signal ◽  
Phylogenetic Analyses ◽  
Simulated Data ◽  
Data Sets ◽  
Alignment Error ◽  
Biological Processes ◽  
Simple Method

Abstract Most phylogenetic analyses assume that a single evolutionary history underlies one gene. However, both biological processes and errors can cause intragenic conflict. The extent to which this conflict is present in empirical data sets is not well documented, but if common, could have far-reaching implications for phylogenetic analyses. We examined several large phylogenomic data sets from diverse taxa using a fast and simple method to identify well-supported intragenic conflict. We found conflict to be highly variable between data sets, from 1% to >92% of genes investigated. We analyzed four exemplar genes in detail and analyzed simulated data under several scenarios. Our results suggest that alignment error may be one major source of conflict, but other conflicts remain unexplained and may represent biological signal or other errors. Whether as part of data analysis pipelines or to explore biologically processes, analyses of within-gene phylogenetic signal should become common.

scholarly journals Damn You, Little h! (Or, Real-World Applications of the Hubble Constant Using Observed and Simulated Data)

2013 ◽  
Vol 30 ◽  
Author(s):  
Darren J. Croton
Keyword(s):  
Data Analysis ◽  
Galaxy Formation ◽  
Real World ◽  
Simulated Data ◽  
Theoretical Data ◽  
Hubble Constant ◽  
Uncertain Parameters ◽  
Modern Age ◽  
Real World Applications ◽  
Better Than

AbstractThe Hubble constant, H0, or its dimensionless equivalent, “little h”, is a fundamental cosmological property that is now known to an accuracy better than a few per cent. Despite its cosmological nature, little h commonly appears in the measured properties of individual galaxies. This can pose unique challenges for users of such data, particularly with survey data. In this paper we show how little h arises in the measurement of galaxies, how to compare like-properties from different datasets that have assumed different little h cosmologies, and how to fairly compare theoretical data with observed data, where little h can manifest in vastly different ways. This last point is particularly important when observations are used to calibrate galaxy formation models, as calibrating with the wrong (or no) little h can lead to disastrous results when the model is later converted to the correct h cosmology. We argue that in this modern age little h is an anachronism, being one of least uncertain parameters in astrophysics, and we propose that observers and theorists instead treat this uncertainty like any other. We conclude with a ‘cheat sheet’ of nine points that should be followed when dealing with little h in data analysis.

scholarly journals COVID-19 vaccination among elderly population in a rural area: coverage and hesitancy study

2021 ◽  
Vol 8 (12) ◽  
pp. 6179
Author(s):  
Satyajit Pattnaik ◽  
Dhananjaya Sharma ◽  
D. Murali M. Rao
Keyword(s):  
Rural Area ◽  
Rural Areas ◽  
Elderly Population ◽  
Vaccine Coverage ◽  
Senior Citizens ◽  
Area Coverage ◽  
Vaccine Hesitancy

COVID-19 vaccination was opened for senior citizens above 60 years on the 01 March 2021. By 25 June 2021, 2.29 crores senior citizens have received two doses and another 6.71 crores have received the first dose. A total of 9 crores citizens have been given two/one dose of vaccine out of the estimated 14.3 crores people above the age of 60 years. During this period two important roadblocks to the vaccination drive were vaccine hesitancy among certain segment of the population and vaccine coverage especially in the rural areas.

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