Fetching the paper…
Reading the bibliography…
In the recent COVID-19 pandemic, a wide range of epidemiological modelling approaches have been used to predict the effective reproduction number, R(t), and other COVID-19 related measures such as the daily rate of exponential growth, r(t).
Elements of Statistics
A L Bowley · 1920
Earlier work this paper cites.
Meta-analytic interval estimation for bivariate correlations
Douglas G. Bonett · 1939
Earlier work this paper cites.
Decisions with multiple objectives: Preferences and value tradeoffs
Ralph L. Keeney and Howard Raiffa · 1976
Earlier work this paper cites.
Group reaction time distributions and an analysis of distribution statistics
R. Ratcliff · 1979
Earlier work this paper cites.
Principles of statistics
Michael George Bulmer · 1979
Earlier work this paper cites.
On appropriate procedures for combining probability distributions within the same family
Ewart A. C. Thomas and B. Ross · 1980
Earlier work this paper cites.
Combining Probability Distributions: A Critique and an Annotated Bibliography
Christian Genest and James V. Zidek · 1986
Earlier work this paper cites.
Experts in uncertainty: Opinion and subjective probability in science
Roger Cooke · 1991
Earlier work this paper cites.
Stacked generalization
David H. Wolpert · 1992
Earlier work this paper cites.
Particle swarm optimization
James Kennedy and Russell Eberhart · 1995
Earlier work this paper cites.
Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data
C. P. Farrington, M. N. Kanaan, and N. J. Gay · 2001
Earlier work this paper cites.
A refined method for the meta-analysis of controlled clinical trials with binary outcome
J Hartung and G Knapp · 2001
Earlier work this paper cites.
A simple confidence interval for meta-analysis
Kurex Sidik and Jeffrey N. Jonkman · 2002
Earlier work this paper cites.
Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control Measures
Jacco Wallinga and Peter Teunis · 2004
Earlier work this paper cites.
Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation
Tilmann Gneiting, Adrian E Raftery, Anton H Westveld III, and Tom Goldman · 2005
Earlier work this paper cites.
How generation intervals shape the relationship between growth rates and reproductive numbers
J Wallinga and M Lipsitch · 2006
Earlier work this paper cites.
Uncertain Judgements: Eliciting Experts’ Probabilities , chapter 9, pages 179–192
O’Hagan A., Buck C.E., Daneshkhah A., Eiser J.R., Garthwaite P.H., Jenkinson D.J., Oakley J.E., and Rakow T · 2006
Earlier work this paper cites.
Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts
Veronica J. Berrocal, Adrian E. Raftery, and Tilmann Gneiting · 2007
Cited alongside, same era.
MOS Uncertainty Estimates in an Ensemble Framework
Bob Glahn, Matthew Peroutka, Jerry Wiedenfeld, John Wagner, Greg Zylstra, Bryan Schuknecht, and Bryan Jackson · 2009
Cited alongside, same era.
Combining probability forecasts
Roopesh Ranjan and Tilmann Gneiting · 2009
Cited alongside, same era.
Introduction to meta-analysis
Michael Borenstein, Larry V. Hedges, Julian P.T. Higgins, and Hannah R. Rothstein · 2009
Cited alongside, same era.
Meta-analytic interval estimation for standardized and unstandardized mean differences
Douglas G. Bonett · 2009
Cited alongside, same era.
A basic introduction to fixed-effect and random-effects models for meta-analysis
Michael Borenstein, Larry V. Hedges, Julian P.T. Higgins, and Hannah R. Rothstein · 2010
Methods to estimate the between-study variance and its uncertainty in meta-analysis
Areti Angeliki Veroniki, Dan Jackson, Wolfgang Viechtbauer, Ralf Bender, Jack Bowden, Guido Knapp, Oliver Kuss, Julian PT Higgins, Dean Langan, and Georgia Salanti · 2016
Later among the works it cites.
Prediction of infectious disease epidemics via weighted density ensembles
Evan L. Ray and Nicholas G. Reich · 2018
Later among the works it cites.
A comparison of heterogeneity variance estimators in simulated random-effects meta-analyses
Dean Langan, Julian P.T. Higgins, Dan Jackson, Jack Bowden, Areti Angeliki Veroniki, Evangelos Kontopantelis, Wolfgang Viechtbauer, and Mark Simmonds · 2019
Later among the works it cites.
R: A Language and Environment for Statistical Computing
R Core Team · 2019
Later among the works it cites.
Choosing effect measures and computing estimates of effect , chapter 6, pages 143–176
Julian PT Higgins, Tianjing Li, and Jonathan J Deeks · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Conducting meta-analyses in R with the metafor package
Wolfgang Viechtbauer · 2010
Cited alongside, same era.
Empirical vs natural weighting in random effects meta-analysis
Jonathan J. Shuster · 2010
Cited alongside, same era.
Locally Calibrated Probabilistic Temperature Forecasting Using Geostatistical Model Averaging and Local Bayesian Model Averaging
William Kleiber, Adrian E. Raftery, Jeffrey Baars, Tilmann Gneiting, Clifford F. Mass, and Eric Grimit · 2011
Cited alongside, same era.
pso: Particle Swarm Optimization , 2012
Claus Bendtsen · 2012
Cited alongside, same era.
Unraveling R0: Considerations for Public Health Applications
Benjamin Ridenhour, Jessica M. Kowalik, and David K. Shay · 2013
Cited alongside, same era.
Combining predictive distributions
Tilmann Gneiting and Roopesh Ranjan · 2013
Cited alongside, same era.
Reproduction number (R) and growth rate (r) of the COVID-19 epidemic in the UK: methods of estimation, data sources, causes of heterogeneity, and use as a guide in policy formulation, August 2020 [Last Accessed 06.10.2020]
The Royal Society · 2020
Later among the works it cites.
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe
Seth Flaxman, Swapnil Mishra, Axel Gandy, H. Juliette T. Unwin, Thomas A. Mellan, Helen Coupland, Charles Whittaker, Harrison Zhu, Tresnia Berah, Jeffrey W. Eaton, Mélodie Monod, Pablo N. Perez-Guzman, Nora Schmit, Lucia Cilloni, Kylie E. C. Ainslie, Marc Baguelin, Adhiratha Boonyasiri, Olivia Boyd, Lorenzo Cattarino, Laura V. Cooper, Zulma Cucunubá, Gina Cuomo-Dannenburg, Amy Dighe, Bimandra Djaafara, Ilaria Dorigatti, Sabine L. van Elsland, Richard G. FitzJohn, Katy A. M. Gaythorpe, Lily Geidelberg, Nicholas C. Grassly, William D. Green, Timothy Hallett, Arran Hamlet, Wes Hinsley, Ben Jeffrey, Edward Knock, Daniel J. Laydon, Gemma Nedjati-Gilani, Pierre Nouvellet, Kris V. Parag, Igor Siveroni, Hayley A. Thompson, Robert Verity, Erik Volz, Caroline E. Walters, Haowei Wang, Yuanrong Wang, Oliver J. Watson, Peter Winskill, Xiaoyue Xi, Patrick GT Walker, Azra C. Ghani, Christl A. Donnelly, Steven M. Riley, Michaela A. C. Vollmer, Neil M. Ferguson, Lucy C. Okell, Samir Bhatt, and Imperial College COVID-19 Response Team · 2020
Later among the works it cites.
Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study
Adam J Kucharski, Petra Klepac, Andrew J K Conlan, Stephen M Kissler, Maria L Tang, Hannah Fry, Julia R Gog, W John Edmunds, Jon C Emery, Graham Medley, James D Munday, Timothy W Russell, Quentin J Leclerc, Charlie Diamond, Simon R Procter, Amy Gimma, Fiona Yueqian Sun, Hamish P Gibbs, Alicia Rosello, Kevin van Zandvoort, Stéphane Hué, Sophie R Meakin, Arminder K Deol, Gwen Knight, Thibaut Jombart, Anna M Foss, Nikos I Bosse, Katherine E Atkins, Billy J Quilty, Rachel Lowe, Kiesha Prem, Stefan Flasche, Carl A B Pearson, Rein M G J Houben, Emily S Nightingale, Akira Endo, Damien C Tully, Yang Liu, Julian Villabona-Arenas, Kathleen O’Reilly, Sebastian Funk, Rosalind M Eggo, Mark Jit, Eleanor M Rees, Joel Hellewell, Samuel Clifford, Christopher I Jarvis, Sam Abbott, Megan Auzenbergs, Nicholas G Davies, and David Simons · 2020
Later among the works it cites.
The R value and growth rate
DHSC · 2020
Later among the works it cites.
Uncertainty quantification for epidemiological forecasts of COVID-19 through combinations of model predictions, 2020
D. S. Silk, V. E. Bowman, U. Dalrymple, and D. C. Woods · 2020
Later among the works it cites.
Short-term forecasts to inform the response to the covid-19 epidemic in the uk
S Funk, S Abbott, BD Atkins, M Baguelin, JK Baillie, P Birrell, J Blake, NI Bosse, J Burton, J Carruthers, NG Davies, D De Angelis, L Dyson, WJ Edmunds, RM Eggo, NM Ferguson, K Gaythorpe, E Gorsich, G Guyver-Fletcher, J Hellewell, EM Hill, A Holmes, TA House, C Jewell, M Jit, T Jombart, I Joshi, MJ Keeling, E Kendall, ES Knock, AJ Kucharski, KA Lythgoe, SR Meakin, JD Munday, PJM Openshaw, CE Overton, F Pagani, J Pearson, PN Perez-Guzman, L Pellis, F Scarabel, MG Semple, K Sherratt, M Tang, MJ Tildesley, E Van Leeuwen, LK Whittles, CMMID COVID-19 Working Group, Imperial College COVID-19 Response Team, and ISARIC4C Investigators · 2020
Later among the works it cites.
COVID-19 Infection Survey (Pilot): methods and further information
ONS · 2020
Later among the works it cites.
Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK
Christopher I. Jarvis, Kevin Van Zandvoort, Amy Gimma, Kiesha Prem, Megan Auzenbergs, Kathleen O’Reilly, Graham Medley, Jon C. Emery, Rein M. G. J. Houben, Nicholas Davies, Emily S. Nightingale, Stefan Flasche, Thibaut Jombart, Joel Hellewell, Sam Abbott, James D. Munday, Nikos I. Bosse, Sebastian Funk, Fiona Sun, Akira Endo, Alicia Rosello, Simon R. Procter, Adam J. Kucharski, Timothy W. Russell, Gwen Knight, Hamish Gibbs, Quentin Leclerc, Billy J. Quilty, Charlie Diamond, Yang Liu, Mark Jit, Samuel Clifford, Carl A. B. Pearson, Rosalind M. Eggo, Arminder K. Deol, Petra Klepac, G. James Rubin, W. John Edmunds, and C. M. M. I. D. C. O. V. I. D.-19 working group · 2020
Later among the works it cites.
Aggregating predictions from experts: A review of statistical methods, experiments, and applications
Thomas McAndrew, Nutcha Wattanachit, Graham C. Gibson, and Nicholas G. Reich · 2021
Closest in time.
Real-time Assessment of Community Transmission (REACT) Study
Imperial College London · 2021
Closest in time.
Reproduction number (R) and growth rate: methodology
DHSC · 2021
Closest in time.