Empirical distributions of time intervals between COVID-19 cases and more severe outcomes in Scotland

Anthony Wood, Rowland Kao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

A critical factor in infectious disease control is the risk of an outbreak overwhelming local healthcare capacity. The overall demand on healthcare services will depend on disease severity, but the precise timing and size of peak demand also depends on the time interval (or clinical time delay) between initial infection, and development of severe disease. A broader distribution of intervals may draw that demand out over a longer period, but have a lower peak demand. These interval distributions are therefore important in modelling trajectories of e.g. hospital admissions, given a trajectory of incidence. Conversely, as testing rates decline, an incidence trajectory may need to be inferred through the delayed, but relatively unbiased signal of hospital admissions.
Healthcare demand has been extensively modelled during the COVID-19 pandemic, where localised waves of infection have imposed severe stresses on healthcare services. While the initial acute threat posed by this disease has since subsided with immunity buildup from vaccination and prior infection, prevalence remains high and waning immunity may lead to substantial pressures for years to come. In this work, then, we present a set of interval distributions, for COVID-19 cases and subsequent severe outcomes; hospital admission, ICU admission, and death. These may be used to model more realistic scenarios of hospital admissions and occupancy, given a trajectory of infections or cases.
We present a method for obtaining empirical distributions using COVID-19
outcomes data from Scotland between September 2020 and January 2022 (N = 31724 hospital admissions, N = 3514 ICU admissions, N = 8306 mortalities). We present separate distributions for individual age, sex, and deprivation of residing community.
While the risk of severe disease following COVID-19 infection is substantially higher for the elderly and those residing in areas of high deprivation, the length of stay shows no strong dependence, suggesting that severe outcomes are equally severe across risk groups. As Scotland and other countries move into a phase where testing is no longer abundant, these intervals may be of use for retrospective modelling of patterns of infection, given data on severe outcomes.
Original languageEnglish
Article numbere0287397
Pages (from-to)1-11
Number of pages11
JournalPLoS ONE
Issue number8
Early online date16 Aug 2023
Publication statusE-pub ahead of print - 16 Aug 2023

Keywords / Materials (for Non-textual outputs)

  • Aged
  • COVID-19/epidemiology
  • Hospitalization
  • Humans
  • Pandemics
  • Retrospective Studies
  • Scotland/epidemiology


Dive into the research topics of 'Empirical distributions of time intervals between COVID-19 cases and more severe outcomes in Scotland'. Together they form a unique fingerprint.

Cite this