A simple correction for COVID-19 sampling bias

@article{DazPachn2020ASC,
  title={A simple correction for COVID-19 sampling bias},
  author={Daniel Andr{\'e}s D{\'i}az-Pach{\'o}n and J. Sunil Rao},
  journal={Journal of Theoretical Biology},
  year={2020},
  volume={512},
  pages={110556 - 110556}
}

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References

SHOWING 1-10 OF 16 REFERENCES

A sample approach

  • 2020

Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app

Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations.

Probability of symptoms and critical disease after SARS-CoV-2 infection

Contacts of SARS-CoV-2 index cases detected in Lombardy, Italy were analyzed, and positive subjects were ascertained via nasal swabs and serological assays and the risk of symptoms increased with age, with males at significantly higher risk.

Generalized active information: extensions to unbounded domains

D Disequilibrium from maximum entropy, measured as active information, can be evaluated from baselines with unbounded support, and this is the purpose of this paper.

A sample approach to the estimation of the critical parameters of the SARS-CoV-2 epidemics: an operational design with a focus on the Italian health system

A sample design to build up a continuous-time surveillance system for pandemic diffusion of the Covid-19 infection is proposed, thought having in mind the SAR-CoV-2 diffusion in Italy during the Spring of 2020.

Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020

On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking, and the delay-adjusted asymptomatic proportion of infections, along with the infections’ timeline were derived.

Estimating Prevalence Using an Imperfect Test

The standard estimate of prevalence is the proportion of positive results obtained from the application of a diagnostic test to a random sample of individuals drawn from the population of interest.

Identification of and Correction for Publication Bias

Two approaches for identifying the conditional probability of publication as a function of a study’s results are proposed, the first based on systematic replication studies and the second based on meta-studies.

Basic methods for sensitivity analysis of biases.

  • S. Greenland
  • Medicine
    International journal of epidemiology
  • 1996
This paper reviews basic methods for examining the sensitivity of study results to biases, with a focus on methods that can be implemented without computer programming.

Information Theory and Statistical Mechanics

Treatment of the predictive aspect of statistical mechanics as a form of statistical inference is extended to the density-matrix formalism and applied to a discussion of the relation between