diff --git a/analyses/quantify_transmission/reproduction_number_cluster_size.qmd b/analyses/quantify_transmission/reproduction_number_cluster_size.qmd index d374799..a3a5b92 100644 --- a/analyses/quantify_transmission/reproduction_number_cluster_size.qmd +++ b/analyses/quantify_transmission/reproduction_number_cluster_size.qmd @@ -9,8 +9,18 @@ editor_options: date: last-modified toc: true toc_float: true +author: + - name: "Adam Kucharski" + orcid: "0000-0001-8814-9421" --- +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>" +) +``` + ## Ingredients - Use Bayesian estimation methods to estimate the reproduction number ($R$) and extent of superspreading, represented by the dispersion of a negative binomial distribution for individual-level seconday cases ($k$), from data on MERS-CoV- outbreak clusters. diff --git a/analyses/quantify_transmission/reproduction_number_serological_data.qmd b/analyses/quantify_transmission/reproduction_number_serological_data.qmd index f6ecb3a..eaba079 100644 --- a/analyses/quantify_transmission/reproduction_number_serological_data.qmd +++ b/analyses/quantify_transmission/reproduction_number_serological_data.qmd @@ -9,8 +9,18 @@ editor_options: date: last-modified toc: true toc_float: true +author: + - name: "Adam Kucharski" + orcid: "0000-0001-8814-9421" --- +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>" +) +``` + ## Ingredients - Social mixing data from `socialmixr` diff --git a/analyses/reconstruct_transmission/estimate_infections.qmd b/analyses/reconstruct_transmission/estimate_infections.qmd index 7999791..82d6de7 100644 --- a/analyses/reconstruct_transmission/estimate_infections.qmd +++ b/analyses/reconstruct_transmission/estimate_infections.qmd @@ -9,8 +9,18 @@ editor_options: date: last-modified toc: true toc_float: true +author: + - name: "Adam Kucharski" + orcid: "0000-0001-8814-9421" --- +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>" +) +``` + ## Ingredients - We want to estimate infection dynamics from incidence data on delayed outcomes such as hospitalisations or deaths. @@ -21,6 +31,11 @@ toc_float: true ## Steps in code + +### Example 1 + +Reconstruct SARS-CoV-2 infection dynamics in the UK from daily data on deaths, 2020 + ```{r} #| warning: false