estimSI: Nonparametric serial interval estimation

In oswaldogressani/EpiLPS: A Fast and Flexible Bayesian Tool for Estimating Epidemiological Parameters

Nonparametric serial interval estimation

Description

The serial interval (SI) is defined as the time between illness onset in a primary case (infector) and illness onset in a secondary case (infectee). This routine estimates different features of the SI distribution based on transmission pair data. The input x should be a data frame with two columns containing the left and right boundary of the serial interval window for each transmission pair. A resampling technique (bootstrap) is used to draw samples from a nonparametric estimate of the cumulative distribution function of the serial interval.

Usage

estimSI(x, B = 5000, verbose = TRUE)

Arguments

x	A data frame with two columns based on transmission pair data. The number of rows is the number of transmission pairs (sample size). The first column should be the left boundary of the SI window and the second column should be the right boundary of the SI window. NA values are not permitted.
B	The number of bootstrap samples.
verbose	Print basic summary features of the SI distribution?

Value

A list containing basic summary features with point estimates and interval estimates.

Author(s)

Oswaldo Gressani [e-mail]

References

Gressani, O. and Hens, N. (2024). Nonparametric serial interval estimation. MedRxiv preprint.

Examples

data(influenza2009serial)
SIfit <- estimSI(x = influenza2009serial)

oswaldogressani/EpiLPS documentation built on Oct. 25, 2024, 8:15 p.m.