• Corpus ID: 220546393

A simple correction for COVID-19 sampling bias

@article{DiazPachon2020ASC,
  title={A simple correction for COVID-19 sampling bias},
  author={Daniel Andr'es D'iaz-Pach'on and J. Sunil Rao},
  journal={ArXiv},
  year={2020}
}
COVID-19 testing has become a standard approach for estimating prevalence which then assist in public health decision making to contain and mitigate the spread of the disease. The sampling designs used are often biased in that they do not reflect the true underlying populations. For instance, individuals with strong symptoms are more likely to be tested than those with no symptoms. This results in biased estimates of prevalence (too high). Typical post-sampling corrections are not always… 

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