This is the repo (1) for the paper: Naylor, Nichola R. and Hasso-Agopsowicz, Mateusz and Kim, Chaelin and Ma, Yixuan and Frost, Isabel and Abbas, Kaja and Aguilar, Gisela and Fuller, Naomi M. and Robotham, Julie V. and Jit, Mark, The Global Economic Burden of Antibiotic Resistant Infections and the Potential Impact of Bacterial Vaccines: A Modelling Study. Available at SSRN: https://ssrn.com/abstract=4676946 or http://dx.doi.org/10.2139/ssrn.4676946
This work feeds into repo (2), which combines the outputs of this repository with epidemiology data, the combination work can be found here: https://github.com/NikkiR08/VAF_AMR_EconBurden
This repo uses evidence synthesis, collation and analyses to compile unit costs of antimicrobial resistance (associated and attributable burden). An inverse variance meta-analysis with random effects is used to estimate excess hospital costs per case. Average values across key literature sources are utilised for antibiotic unit cost estimation, whilst international databases are consulted for economic data. Productivity losses are estimated through human capital and production function approaches. Inflation and exchange rate data are used to preserve local currency units and local economic shifts throughout, where possible. All cost results are then presented in 2019 USD.
Note the accompanying paper is going through review processes and therefore this repository is subject to change until publication.
| Folder | Description |
|---|---|
| antibiotic | R scripts and outputs estimating antibiotic unit costs |
| cost_per_case | R scripts and outputs estimating associated and attributable burden related to hospital length of stay and costs |
| data_all | data files that are used throughout the repository (note within individual folders there are more specific data files to that module) |
| general_functions | functions used across the repository (namely inflation) |
| labour_productivity | R scripts and outputs estimating labour productivity burden |
Nichola R. Naylor, The Antimicrobial Resistance Unit Cost Repository (AMR-UCR). GitHub (https://github.com/NikkiR08/AMR-UCR/tree/main) [Access Date: ]
For large intermediate files, a link to a Dropbox folder storing these are available upon request ([email protected]).
Please feel free to raise an issue on this GitHub, using the Issues functionality on the GitHub Repository, though the grant funding this project has been finished so responses and capacity for changes may be limited.