scholarly journals COVID-19: Metaheuristic Optimization-Based Forecast Method on Time-Dependent Bootstrapped Data

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Livio Fenga ◽  
Carlo Del Castello
Keyword(s):  
Turning Point ◽  
Operation Research ◽  
Time Dependent ◽  
Forecast Method ◽  
Epidemic Curve ◽  
Metaheuristic Optimization ◽  
Bootstrap Techniques

A compounded method—exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques—is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the COVID-19 virus in Italy. Future lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.

scholarly journals CoViD–19: Meta-heuristic optimization based forecast method on time dependent bootstrapped data

2020 ◽  
Author(s):  
Livio Fenga ◽  
Carlo Del Castello
Keyword(s):  
Turning Point ◽  
Operation Research ◽  
Time Dependent ◽  
Heuristic Optimization ◽  
Forecast Method ◽  
Epidemic Curve ◽  
Bootstrap Techniques

AbstractA compounded method – exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques – is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the CoViD–19 virus in Italy. Futures lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.

scholarly journals Is the South African business cycle time dependent?

2001 ◽  
Vol 4 (1) ◽  
pp. 204-215 ◽  
Author(s):  
Ashley G. Frank
Keyword(s):  
Business Cycle ◽  
South African ◽  
Cycle Time ◽  
Confidence Level ◽  
Hazard Function ◽  
Turning Point ◽  
Time Dependent ◽  
Economic Downturn ◽  
The South ◽  
Over Time

This study is concerned with the South African business cycle and makes use of the hazard function to determine the importance of duration for its analysis. This function gives the conditional probability that a state sustained through a previous period will end in the current one. The study estimates this probability for both economic downturn and expansion. At the 95 per cent confidence level, there is no statistical underpinning found for conventional ideas about the likelihood of an upturn or downturn in the economy over time. The duration of a business cycle does not help predict the turning point

scholarly journals Effectiveness of mRNA COVID-19 Vaccines among Employees in an American Healthcare System

2021 ◽  
Author(s):  
Nabin K. Shrestha ◽  
Amy S Nowacki ◽  
Patrick C Burke ◽  
Paul Terpeluk ◽  
Steven M Gordon
Keyword(s):  
Cumulative Incidence ◽  
Proportional Hazards ◽  
Cleveland Clinic ◽  
Vaccine Dose ◽  
Cox Proportional Hazards ◽  
Vaccine Effectiveness ◽  
Time Dependent ◽  
Great Promise ◽  
Epidemic Curve ◽  
The Usa

Background. The mRNA SARS-CoV-2 vaccines have shown great promise in clinical trials. The purpose of this study was to evaluate the effectiveness of these vaccines under real-world conditions in the USA. Methods. Employees of the Cleveland Clinic Health System, previously not infected with SARS-CoV-2, and working in Ohio on Dec 16, 2020, the day COVID-19 vaccination began, were included. The cumulative incidence of SARS-CoV-2 infection, over the next 5 months, was compared among those who received the vaccine and those who did not, by modeling vaccination as a time-dependent covariate in Cox proportional hazards regression analyses adjusted for the slope of the epidemic curve as a continuous time-dependent covariate. Results. Of the 46866 included employees, 28223 (60%) were vaccinated by the end of the study period. The cumulative incidence of SARS-CoV-2 infection was much higher among those not vaccinated than those vaccinated. Only 15 (0.7%) of the 2154 SARS-CoV-2 infections during the study occurred among those vaccinated. After adjusting for the slope of the epidemic curve, age, and job type, vaccination was associated with a significantly reduced risk of SARS-CoV-2 infection (HR 0.03, 95% C.I. 0.02 - 0.06, p < 0.001), corresponding to a vaccine effectiveness rate of 97.1% (95% CI 94.3 - 98.5). Vaccine effectiveness was 89.2% at 7 days and 95.0% at 14 days after the first vaccine dose. Conclusions. The mRNA SARS-CoV-2 vaccines are over 97% protective against COVID-19 in the working-age population, with substantial protection possibly apparent within a few days of the first dose.

scholarly journals Nowcasting the COVID-19 pandemic in Bavaria

2020 ◽  
Author(s):  
Felix Günther ◽  
Andreas Bender ◽  
Katharina Katz ◽  
Helmut Küchenhoff ◽  
Michael Höhle
Keyword(s):  
Bayesian Model ◽  
Reproduction Number ◽  
Disease Onset ◽  
Daily Basis ◽  
Time Dependent ◽  
Disease Spread ◽  
Hierarchical Bayesian Model ◽  
Epidemic Curve ◽  
Reporting Delays ◽  
Reporting Delay

AbstractTo assess the current dynamic of an epidemic it is central to collect information on the daily number of newly diseased cases. This is especially important in real-time surveillance, when one aims at evaluating the effects of interventions on disease spread. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamic of an epidemic when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred-but-not-yet-reported events. Here, we present a novel application of nowcasting to data on the current COVID-19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution associated with the week and weekday of reporting and assumes a smooth epidemic curve. Furthermore, we present a way to estimate the time-dependent case reproduction number R(t) based on predictions of the nowcast. We provide methodological details of the developed approach, illustrate results based on data of the current epidemic, discuss limitations and alternative estimation strategies, and provide code for reproduction or adaption of the nowcasting to data from different regions. Results of the nowcasting approach are reported to the Bavarian health authority and published on a webpage on a daily basis.

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