Understatement factor of a crude case fatality rate during exponential growth

Gives the approximate factor by which cumulative deaths divided by cumulative cases understates the case fatality rate when an epidemic grows exponentially and deaths are reported a fixed delay after cases. The exponent is the number of epidemic doubling times that pass between case reporting and death reporting, a heuristic given by Lipsitch and colleagues.

Signature

B = 2^(d / T_d)
Inputs
InputsDefinitionUnit
dDelay between a case being reported and its death being reportedtime, in the same unit as T_d
T_dTime taken for the number of cases to double during exponential growthtime, in the same unit as d, above zero
Output
BApproximate factor by which the crude case fatality rate understates the case fatality rateratio, 1 when there is no delay

Function

Case fatality rate estimation, outbreak bias and population mortality function

Maps counts of deaths, recoveries and cases to the case fatality rate (CFR), the proportion of cases meeting a case definition who die of the disease over a stated period, and relates it to the delay bias of crude estimates during exponential growth and to population mortality through the attack rate. The records follow the notation of the Case Fatality Rate article. Matching the period of a CFR to a model cycle uses HE-FM-TP-003, and the attack rate itself is HE-FM-ATR-001.

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Implementations

  • Excel

    Understatement factor from delay and doubling time

    Excel raises 2 to the ratio of the named cells holding the reporting delay and the doubling time, both in the same unit.

    =2^(ReportDelay/DoublingTime)

Assumptions

  • Constant exponential growth of reported cases

    Reported cases grow exponentially with a fixed doubling time over the delay. As growth slows or the epidemic declines, the factor no longer describes the bias.

  • One fixed delay from case report to death report

    Every death is reported the same time after its case. Real delays vary from case to case, so the factor indicates the size of the bias rather than giving an exact correction.

Worked examples

  • Three-week delay with a two-week doubling time

    In Lipsitch and colleagues' example a three-week delay and a two-week doubling time give 2 raised to the power 1.5, about 2.8, so the crude estimate is close to one third of the case fatality rate.

    d = 3; T_d = 2; B = 2.83
  • Delay equal to one doubling time

    When deaths are reported one doubling time after their cases, the crude estimate is about half the case fatality rate (computed here for illustration).

    d = 2; T_d = 2; B = 2

Common errors

  • Delay and doubling time in different units

    Entering the three-week delay as 21 days with a doubling time of 2 weeks gives 2 raised to the power 10.5, about 1,448, instead of about 2.8 (computed here for illustration). Both times are entered in days or both in weeks.

Sources

  • Delay heuristic for the crude case fatality rate in a growing epidemic

    Lipsitch M, Donnelly CA, Fraser C, Blake IM, Cori A, Dorigatti I, et al. Potential biases in estimating absolute and relative case-fatality risks during outbreaks. PLoS Neglected Tropical Diseases. 2015;9(7):e0003846. Figure 1 legend: with a three-week reporting delay and a two-week doubling time the crude CFR is underestimated by a factor of about 2 to the power 3/2, or 2.8, the exponent being the number of doubling times between case and death reporting.

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Canonical Identity

Understatement factor of a crude case fatality rate during exponential growth | HealthEconomics.wiki