• Corpus ID: 218674079

Bayesian adjustment for preferential testing in estimating the COVID-19 infection fatality rate: Theory and methods

@article{Campbell2020BayesianAF,
  title={Bayesian adjustment for preferential testing in estimating the COVID-19 infection fatality rate: Theory and methods},
  author={Harlan Campbell and Perry de Valpine and Lauren Maxwell and Valentijn MT de Jong and Thomas P.A. Debray and Thomas Guenter Janisch and Paul Gustafson},
  journal={arXiv: Methodology},
  year={2020}
}
A key challenge in estimating the infection fatality rate (IFR) is determining the total number of cases. The total number of cases is not known because not everyone is tested but also, more importantly, because tested individuals are not representative of the population at large. We refer to the phenomenon whereby infected individuals are more likely to be tested than non-infected individuals, as ''preferential testing.'' An open question is whether or not it is possible to reliably estimate… 
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S0950268821002405jra 1..14
  • 2021
Bayesian analysis of tests with unknown specificity and sensitivity
  • A. Gelman, B. Carpenter
  • Biology
    Journal of the Royal Statistical Society: Series C (Applied Statistics)
  • 2020
TLDR
H hierarchical regression and post‐stratification models with code in Stan are demonstrated and their application to a controversial recent study of SARS‐CoV‐2 antibodies in a sample of people from the Stanford University area is discussed.
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References

SHOWING 1-10 OF 69 REFERENCES
Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modelling study in Hubei, China and northern Italy
TLDR
A mechanistic approach is developed to correct the crude CFR for bias due to right-censoring and preferential ascertainment and provide adjusted estimates of mortality due to SARS-CoV-2 infection by age group, specific to the situation in Hubei, China and northern Italy during these periods.
Oxford COVID-19 Government Response Tracker
Using simulation studies to evaluate statistical methods
TLDR
This tutorial provides a structured approach for planning and reporting simulation studies, which involves defining aims, data‐generating mechanisms, estimands, methods, and performance measures (“ADEMP”).
Sampling Methods for Wallenius' and Fisher's Noncentral Hypergeometric Distributions
  • A. Fog
  • Mathematics
    Commun. Stat. Simul. Comput.
  • 2008
TLDR
Several methods for generating variates with univariate and multivariate Walleniu' and Fisher's noncentral hypergeometric distributions are developed, useful for Monte Carlo simulation of models of biased sampling and models of evolution and for calculating moments and quantiles of the distributions.
A systematic review and meta-analysis of published research data on COVID-19 infection-fatality rates
TLDR
A systematic review and meta-analysis of published evidence on COVID-19 until the end of April, 2020 shows a point-estimate of IFR of 0.75% (0.49-1.01%) with significant heterogeneity, however, it is difficult to know if this represents the "true" point estimate due to very high heterogeneity in the meta- analysis.
An Empirical Estimate of the Infection Fatality Rate of COVID-19 from the First Italian Outbreak
TLDR
Empirical estimates based on population level data show a sharp difference in fatality rates between young and old people and firmly rule out overall fatality ratios below 0·5% in populations with more than 30% over 60 years old.
An empirical estimate of the infection fatality rate of COVID-19 from the first Italian outbreak
TLDR
Empirical estimates based on population level data show a sharp difference in fatality rates between young and old people and firmly rule out overall fatality ratios below 0.5% in populations with more than 30% over 60 years old.
Bayesian analysis of tests with unknown specificity and sensitivity
  • A. Gelman, B. Carpenter
  • Biology
    Journal of the Royal Statistical Society: Series C (Applied Statistics)
  • 2020
TLDR
H hierarchical regression and post‐stratification models with code in Stan are demonstrated and their application to a controversial recent study of SARS‐CoV‐2 antibodies in a sample of people from the Stanford University area is discussed.
Bayesian network analysis of Covid-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported
Abstract Widely reported statistics on Covid-19 across the globe fail to take account of both the uncertainty of the data and possible explanations for this uncertainty. In this article, we use a
COVID-19 Antibody Seroprevalence in Santa Clara County, California
TLDR
The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases.
...
1
2
3
4
5
...