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Estimating a Time-to-Event Distribution from Right-Truncated Data in an Epidemic: a Review of Methods

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:0 publications

Grant number: C19-IUC-537

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Key facts

  • Disease

    COVID-19

  • Start & end year

    N/A

  • Funder

    UK Research and Innovation (UKRI)

  • Principal Investigator

    Dr. Shaun Seaman

  • Research Location

    United Kingdom

  • Lead Research Institution

    MRC Biostatistics Unit

  • Research Priority Alignment

    N/A

  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease surveillance & mapping

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Time-to-event data are right-truncated if only individuals who have experienced the event by a certain time can be included in the sample. For example, we may be interested in estimating the distribution of time from onset of disease symptoms to death and only have data on individuals who have died. This may be the case at the beginning of an epidemic. Right truncation causes the distribution of times to event in the sample to be biased towards shorter times compared to the population distribution. We have reviewed statistical methods that deal with this bias, particularly in the context of CoVID-19.