Code
Serial intervals from genomic data
Serial intervals (the length of time fron symptom onset in infector infectee) are often estimated with contact tracing data, which has several limitations in terms of cost,
data accessibility and extrapolation to non-close-contact settings. Instead, we explored an approach using routinely-collected pathogen genomic data to estimate the
distribution of the serial interval, that does not require detailed information of who infected who and takes into account that not all cases will be sampled. We applied
this method to case clusters of COVID-19 from Victoria, Australia. Alongside our paper Stockdale et al, 2023
published in Nature Communications, supporting code is available for application of our moethodology to other settings. A linked paper
Susvitasari et al, 2023 contains an R package for the method, developed by Kurnia Susvitasari (SFU).
cr0eso
As part of a 2022 project analysing outbreaks of COVID-19 in British Columbia long-term healthcare facilties,
we developed the R package 'cr0eso' for estimation of the basic reproduction number R0 in multiple outbreaks using an
SEIR model. This package, developed with Mike Irvine (BCCDC) and Sean Anderson (Fisheries and Oceans Canada), fits a Bayesian hierarchical
model to a collection of outbreaks in RStan. It is primarily designed for outbreaks
occurring in the same population but different facilities, e.g. healthcare, schools, workplaces or prisons. As well as
R0, it can also be used to estimate the effect of outbreak intervention strategies.