The generation interval is the interval between the time that an individual is infected by an infector and the time this infector was infected. Its distribution underpins estimates of the reproductive number and hence informs public health strategies. Empirical generation-interval distributions are often derived from contact-tracing data. But linking observed generation intervals to the underlying generation interval required for modeling purposes is surprisingly not straightforward, and misspecifications can lead to incorrect estimates of the reproductive number, with the potential to misguide interventions to stop or slow an epidemic. Here, we clarify the theoretical framework for three conceptually different generation-interval distributions: the "intrinsic'' one typically used in mathematical models and the "forward'' and "backward'' ones typically observed from contact tracing data, looking respectively forward or backward in time. We explain how the relationship between these distributions changes as an epidemic progresses and discuss how empirical generation-interval data can be used to correctly inform mathematical models.

# Data from: Intrinsic and realized generation intervals in infectious-disease transmission Dataset DOI: [10.5061/dryad.4dd3s](https://doi.org/10.5061/dryad.4dd3s) ## Description of the data and file structure See README.md in the zipped file. ### Files and variables #### File: GenerationInterval_Champredon_RSPB_v2.zip **Description:** Code to replicate simulations and results ## Code/software Computing language is R. ## Access information Other publicly accessible locations of the data: * N/A Data was derived from the following sources: * N/A

Source code to replicate all results and figures Unzip then read "README.md" for instructions generationInterval_Champredon_RSPB.zip