Cost-effectiveness of sleeping sickness elimination campaigns in five settings of the Democratic Republic of Congo ======================= **Human African Trypanosomiasis Modeling and Economic Predictions for Policy** ([HATMEPP](https://go.warwick.ac.uk/hatmepp)) Administered by Marina Antillon, PhD. Collaborating centers: ___Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER)___ University of Warwick Coventry, UK ___Epidemiology and Public Health___ ___Swiss Tropical and Public Health (Swiss TPH) Institute___ (An affiliated institute of the University of Basel) Basel, Switzerland Contact: Marina Antillon marina.antillon@swisstph.ch. COPYRIGHT 2021, Swiss TPH and Warwick University --- @[toc](Contents) # Project Objective In the current study, we undertake an economic evaluation of four gHAT control and elimination strategies in five health zones of the Democratic Republic of Congo (DRC). We adopt a modelling framework in order to examine the interplay of epidemiological, economic and temporal factors in effective decision-making around gHAT strategies for elimination of transmission (EOT). We aim to answer the following questions - What are the resource implications of further pursuing gHAT EOT by 2030? - Which of the considered strategies has the highest probability of being cost-effective in these different settings? The publication is found [here](https://www.nature.com/articles/s41467-022-28598-w). The companion website is found [here](https://hatmepp.warwick.ac.uk/5HZCEA/v2/). A guide on how to use the companion website is found [here](https://warwick.ac.uk/fac/cross_fac/zeeman_institute/new_research/combatting_disease/hat/hatmepp/gui/gui_user_guide_cost_evaluations_v1.2_en.pdf). --- # Overview of analysis The analysis is broadly defined in four parts, each of these parts is executed in various R code files: I. Projecting health outcomes under alternative strategies of gHAT control. II. Costing: for clinical activities as well as screening and prevention (vector control) activities under alternative strategies. III. Cost-effectiveness analysis of alternative strategies. IV. Comparative analysis: A. Between health zones B. Within health zones, using alternative assumptions (for the purpose of sensitivity analyses). This model takes the output of the dynamic (SIR-type) model developed and operated by the Warwick team and projects the clinical outcomes and the accompanying costs of treating patients. The clinical and economic model is constituted by a probability tree model. In addition, alternative prevention campaigns (varying levels of active screening and vector control) are modeled and integrated into the analysis. The overall flow of models is diagrammed below and provided in high resolution [here](https://osf.io/5xzsu/):  ## Software considerations The tools for the economic model are coded in R. While we would highly recommend using the code within RStudio environment (in part because of it's features to manage the project with .RProj and renv) this is not strictly necessary and the benefits of renv are available from a classic R interface or a shell command line. Some of the results tables for the project are produced automatically within the code in the project via Rmarkdown (using knitr) and Latex. See the help links later in this document for more information. For detailed information, see: [Installation to-do list](https://osf.io/xbwte/wiki/Installation%20to-do%20list/) (all free) ## Hardware considerations **Hardware needs:** For optimal performance, the model was run for different places and different scenarios using a high-performance computing cluster at the University of Basel (scicore, http://scicore.unibas.ch/). Scicore is run with a slurm scheduler, and the bash file is included in this repository. However, a user could use a parallel computing package in R or any other automated task management solution, but no such implementation is presented here. **Duration:** For reference, a single run of the code for all strategies in one place takes about 12-15 minutes in a MacBook Pro (Mid-2014 model) with a 3 GHz Intel Core i7 processor and 16 GB of RAM. **Memory needed:** Intermediate simulations and graphs need about 600 MB of storage per health zone per scenario (the full analysis across scenarios and health zones adds up to 43 sets of results). --- # Preparation [Installation to-do list](https://osf.io/xbwte/wiki/Installation%20to-do%20list/) (all free) --- # How to run this analysis [Instructions to run the analysis](https://osf.io/xbwte/wiki/Instructions%20to%20run%20analysis/) For reference, the file structure of this repository is described here: [file structure](https://osf.io/xbwte/wiki/File%20structure%2C%20inputs%2C%20and%20outputs/) --- # Demo and sample results [Demo and sample results](https://osf.io/xbwte/wiki/Demo%20and%20expected%20results/) --- # Troubleshooting [Troubleshooting](https://osf.io/xbwte/wiki/Troubleshooting/)