COVID-19 Modeling and Non-Pharmaceutical Interventions in a Dialysis Unit

Paper: Jang H, Polgreen PM, Segre AM, Pemmaraju SV (2021) COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit. PLoS Comput Biol 17(7): e1009177. https://doi.org/10.1371/journal.pcbi.1009177

This document provides a step-by-step guide to replicate results in the paper.

Installation

The Python packages used in this project are installed in a conda environment. Create environment from these files (*.yml). Once this is done, no additional installation of packages is needed.

conda env create -f Dialysis_COVID19.yml
conda env create -f igraph.yml

Requirements

If for some reason you fail to create conda environments with above *.yml files, install the following libraries. Python3 is used.

• numpy
• pandas
• matplotlib
• networkx
• python-igraph

Data

• Download data from the following data repository: Healthcare Personnel Movement Data
• Place the data in the dialysis/data/

Run the simulations to generate results in the main paper

• Use Dialysis_COVID19 for the conda environment

source activate Dialysis_COVID19

• Prepare contact arrays that are used in simulation (Day10)

cd dialysis
./prepare_contact_networks.sh

• Compute alpha (scaling parameter for shedding models) The shedding models used in the paper are exp/exp (20%) and exp/exp (60%), which correspond to D2 and D3 in the script.

cd ..
python compute_alpha_v2.py

• Run baseline COVID-19 simulations (no interventions)

You can run baseline simulations to check if everything set up correctly. The following script runs on 12 sets of simulations (2 scenarios, 2 shedding models, 3 target R0s), each setting with 500 replicates. Change the value of cpu to the number of CPU available in your device. For each intervention setting, disease model, R0, and infection source (patient or HCP), we keep track of the following: (i) daily infection count, (ii) transmission routes, (iii) daily population (in case for addition HCP to unit), (iv) R0, and (v) the generation time. Results are saved in dialysis/results/day10/ directory with filenames of baseline_scenario0.npz (Scenario 1 in the paper) and baseline_scenario1.npz (Scenario 2 in the paper)

python COVID19_dialysis_baseline.py -cpu 60

• Run COVID-19 simulation (for all the interventions introduced in the paper) This takes roughly one day to run using Vinci server (used 60 cores). Results are saved in dialysis/results/day10/ directory with filenames of final_scenario0.npz (Scenario 1 in the paper) and final_scenario1.npz (Scenario 2 in the paper).

python COVID19_dialysis_final.py -cpu 60

• Draw figures Initially, we explored 4 shedding models (D0 - D3), but we only use two shedding models D2:exp/exp(20%) and D3:exp/exp(60%) in the simulation. This generates warning when drawing figures at this stage. Simply ignore the warnings and use results for D2 and D3. Figures are saved in dialysis/tiff/plots/day10/. Note that -s 0 correspond to Scenario 1 and -s 1 correspond to Scenario 2.

python -W ignore COVID19_dialysis_plots_tiff.py -s 0
python -W ignore COVID19_dialysis_plots_tiff.py -s 1

• Generate tables COVID19_dialysis_tables_final.py generates many tables from the simulation result. Tables are saved in dialysis/tables/day10/

python -W ignore COVID19_dialysis_tables_final.py -s 0
python -W ignore COVID19_dialysis_tables_final.py -s 1

Draw the contact network and generate network statistics

• Generating network statistics Results are saved in tables/statistics/

python generate_statistics.py
python generate_instantaneous_statistics.py

• Draw the contact network This script uses python-igraph package. (this package uses the Cairo library for plotting) Deactivate Dialysis_COVID19 environment and activate igraph environment. The contact network is saved in plots/contact_network/

source deactivate
source activate igraph
cd dialysis
python draw_contact_network.py

Generate results on the other days

• Use Dialysis_COVID19 for the conda environment

source deactivate
source activate Dialysis_COVID19

• Prepare contact arrays for other days (Day2, Day6, Day7, Day8, Day9)

./prepare_contact_networks_other_days.sh

• Run COVID-19 simulation Run on four sets of interventions: Baseline, Baseline+, Baseline++, Baseline+++ (refer to the paper for details).

cd ..
./COVID19_dialysis_other_days.sh

• Draw figures

./COVID19_dialysis_plots_tiff_other_days.sh

• Draw contact networks

source deactivate
source activate igraph
cd dialysis
./draw_contact_networks_other_days.sh

Cite

Please cite our paper if you use the code or the dataset.

@article{jang2021covid,
  title={COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit},
  author={Jang, Hankyu and Polgreen, Philip M. and Segre, Alberto M. and Pemmaraju, Sriram V.},
  journal={PLoS Computational Biology},
  year={2021}
}