/AMR_ABM

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

Antimicrobial Resistant Organisms: Estimation of Community Prevalence and Nosocomial Transmission

This is the repo for replicate analysis, and figures in the manuscript titled: Dynamic Modeling of Antimicrobial Resistant Organisms: Estimation of Community Prevalence and Nosocomial Transmission

Authors: Jaime Cascante Vega$^1$, Tal Robin$^1$, Jason Zucker$^2$, Anne-Catrin Uhlemann$^2$, Sen Pei$^1$ and Jeffrey Shaman$^1$.

  1. Department of Environmental Health Sciences, Columbia Mailman School of Public Health, Columbia University, 722 W. 168th St, New York, NY 10032, USA
  2. Division of Infectious Diseases, Irving Medical Center, Columbia University, 722 W. 168th St, New York, NY 10032, USA

Information

This repository contains the code necessary to replicate the analysis in the original manuscript entitled Dynamic Modeling of Antimicrobial Resistant Organisms: Estimation of Community Prevalence and Nosocomial Transmission by the authors listed above. In particular the code contains an agent based model within an Iterated Filtering framework to estimate importation rates and nosocomial contact rates using patient movement between hospital facility wards, admissions and discharge.

Citation

If you're using the code or analysis used in this repository consider citing our reseach project. The license is indicated below.

  • Preprint: xxxx
  • Print: xxxx

Packages

In the directory code there's a file with the packages and versions used for this manuscript. Follow the steps below installing a conda environment and replicating all the results.

Replicating the paper

We provide Jupyter notebooks to replicate what would you need to create the Figure in the main manuscript. They follow the names FigureX.ipynb for x $\in [1,\text{Number of Figures}]$. Aditionally we provide examples on how to use the agent based model and the basic structure of the data use to track the movement of the patients.

Contact

Please reach if you have any question regards the modeling or the inference algorithm. We provide an anonymized data to replicate the resutls but for some Figures it might not be sufficient to repliate it. Any correspondence should be sent to jc56470@cumc.columbia.edu

License

All code in this repository is Copyright © 2022.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.