Statistical techniques to estimate the SARS-CoV-2 infection fatality rate
Abstract
The determination of the infection fatality rate (IFR) for the novel SARS-CoV-2 coronavirus is a key aim for many of the field studies that are currently being undertaken in response to the pandemic. The IFR together with the basic reproduction number , are the main epidemic parameters describing severity and transmissibility of the virus, respectively. The IFR can be also used as a basis for estimating and monitoring the number of infected individuals in a population, which may be subsequently used to inform policy decisions relating to public health interventions and lockdown strategies. The interpretation of IFR measurements requires the calculation of confidence intervals. We present a number of statistical methods that are relevant in this context and develop an inverse problem formulation to determine correction factors to mitigate time-dependent effects that can lead to biased IFR estimates. We also review a number of methods to combine IFR estimates from multiple independent studies, provide example calculations throughout this note and conclude with a summary and "best practice" recommendations. The developed code is available online.
Cite
@article{arxiv.2012.02100,
title = {Statistical techniques to estimate the SARS-CoV-2 infection fatality rate},
author = {Mikael Mieskolainen and Robert Bainbridge and Oliver Buchmueller and Louis Lyons and Nicholas Wardle},
journal= {arXiv preprint arXiv:2012.02100},
year = {2020}
}
Comments
50 pages, 13 figures