tomsumner/Variance_SA_TB
This contains the code used in "Variance-based sensitivity analysis of TB transmission models": Model_1_intervention_event.R <- function for model 1 (serial infected states) with intervention coded as an event (using package FME); Model_2_intervention_event.R <- function for model 2 (parallel infected states) with intervention coded as an event (using package FME); intervention_event.R <- fucntion to define the intervention as a event for use in the ODE models; SS_1_beta.R <- code to solve steady state solution for model 1 (serial infected states) for beta; SS_2_beta.R <- code to solve steady state solution for model 2 (parallel infected states) for beta; Par_dist_gen <- fits distributions to input quantiles taken from literature, uses package RRiskDistributions; Run_model <- code to run the model for each row in an input matrix and return the reductions in incidence and mortality over 1 and 10 years; Sobol_analysis_intervention_event_individual.R <- code to calculate the Sobol indicies for individual inputs and generate outputs, uses Sensobol package; Sobol_analysis_intervention_event_grouped.R <- code to calculate the Sobol indicies for grouped inputs and generate outputs, uses Sensobol package.
Keywords
Sensitivity analysis; Modelling; Tuberculosis| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Software R script |
| Capture method | Other |
| Date | 7 June 2022 |
| Language(s) of written materials | English |
| Creator(s) |
Sumner, T |
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
| Research Centre |
Centre for the Mathematical Modelling of Infectious Diseases TB Centre |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Funders |
Project Funder Grant Number Funder URI |
| Date Deposited | 06 Jul 2023 11:02 |
| Last Modified | 06 Jul 2023 11:02 |
| Publisher | GitHub |