In joelewis101/blantyreESBL: Data and Code Repository For a Study Describing Antimicrobial Resistance in Blantyre, Malawi

knitr::opts_chunk$set(
  collapse = TRUE,
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library(blantyreESBL)

Introduction

This document provides instructions on how to locate the Stan code for the models used in the publication:

Dynamics of gut mucosal colonisation with extended spectrum beta-lactamase producing Enterobacterales in Malawi

Joseph M Lewis^1,2,3,4^, , Madalitso Mphasa^1^, Rachel Banda^1^, Matthew Beale^4^, Eva Heinz^2^, Jane Mallewa^5^, Christopher Jewell^6^, Nicholas R Thomson^4^, Nicholas A Feasey^1,2^

1. Malawi Liverpool Wellcome Clinical Research Programme, Blantyre, Malawi
2. Liverpool School of Tropical Medicine, Liverpool, UK
3. Department of Clinical Infection, Microbiology and Immunology, University of Liverpool, Liverpool, UK
4. Wellcome Sanger Institute, Hinxton, UK
5. College of Medicine, University of Malawi, Malawi
6. University of Lancaster, Lanaster, UK
7. London School of Tropical Medicine and Hygiene, London, UK

Locating Stan code

The stan model has the filename ESBLmod_finalV1.0_rk45.stan are present in the `extdata/ directory of the installed package, which can be located with the following command:

system.file("extdata", 
            "ESBLmod_finalV1.0_rk45.stan", 
            package = "blantyreESBL")

Model specification

The model can include covariates that are:

• Non time varying
• Time varying with stepwise constant effect (equivalent to the models fitted by the R package msm)
• Time varying with exponential decay following exposure

See the manuscript for details

Passing data to the model

The model expects the following data as input; each item is passed as a named item in a list to the rstan stan command to fit the model. Each

• N [integer]

  • Number of rows of data, each row consisting of two ESBL observations separated by a time t for one patient. Each patient can have multiple rows of data.

• n_covs [integer vector of length 3]

  • This specifies the number of covariates to be fitted in the model.
  • It should be formatted: [number of nontimevarying covariates, number of stepwise constant covariates, number of exp decay covariates ]

• covs_type [integer vector of length(number of covariates)]

  • Each position encodes the type of variable in the order they are presented in covs_mat (all the exp decay variables must always go first):
    • 3 = time varying with exponential decay of effect
    • 2 = time varying with piecewise constant
    • 1 = non time varying

• t [integer vector of length N]

  • Time separating beginning and end ESBL observations for each row of data

• cov_mat [real matrix with 3*(number of covariate) columns and N rows]

  • Start and stop times of covariates, ordered as per covs_type
  • Each covariate needs three columns, in this order
    • start_time: time that covariate exposure started
      • if there is no exposure in this row, code as -999
    • stop time: time that covariate exposure stopped
      • if there is no exposure in this row, code as -999
    • prev_stop time:
      • if covariate has exp. decay, this is the previous stop time (before current row e.g. -10 for 10 days ago)
      • If no previous exposure, code as 999
      • If non time varying exposure, code as 999 = present, -999 absent

• start state [ matrix with N rows and two columns ]

  • each row is start state for that time period in format (ESBL-, ESBL+) ie esbl positive coded as [0,1] and ESBL negative coded as [1,0]

• end state: [integer]

  • final state; ESBL+ = 1, ESBL- = 0

The included data btESBL_stanmodeldata is set up to fit the model used in the manuscript.

Fitting the model

The following code (not run in this vignette) will fit the model as in the manuscript:

library(rstan)
library(blantyreESBL)

stan(
  file = system.file("extdata", 
                     "ESBLmod_finalV1.0_rk45.stan", 
                     package = "blantyreESBL")
  data = btESBL_stanmodeldata,
  warmup = 500,
  iter = 1000,
  chains = 4
) -> stanfit

Simulating from the model

The script simulate_from_posterior.R will generate the simulations used in the analysis. It is included in the package install and again can be located by:

system.file("extdata", 
            "simulate_from_posterior.R", 
            package = "blantyreESBL")

Or it is located (along withe stan model) in the inst/extdata/ folder on the github repo.

joelewis101/blantyreESBL documentation built on Nov. 1, 2023, 1:43 p.m.