In Room Air Filter Scale Up GitHub Repository

A scale up simulation of various in room filtration systems that could protect critical workers in the event of a catastrophic pandemic.

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Overview

This git repository holds the code for the In Room Air Filtration ANU Capstone group in partnership with ALLFED. It contains the data processing and analysis of our simulations of scale up in room systems as well as our critical worker estimation given an extreme pandemic scenario. For more information, visit the ANU Capstone team's repositiory and landing page.

Landing Page: https://sites.google.com/view/anu-capstone-air-filtration/home

Repository: https://drive.google.com/drive/folders/1PC_QixM3_B3nh0tNhnJJnPxHECVEsJI7

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Project Structure

• Data
• Results
• Scripts
• SRC

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Installation

Clone the repository and install dependencies:

git clone https://github.com/SPROOK/InRoomAirFilterScaleUp.git 
cd InRoomAirFilterScaleUp
pip install -r requirements.txt

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Data

The data folder contains all source datasets used in our scale-up estimation and analysis. This includes data for our Critical Worker Analysis, CR Box Analysis, and Coal Baghouse Analysis.

Critical Worker Analysis

• ILO_ISCO_08_GLB.csv
• Indoors_Environmentally_Controlled_data.csv
• ISCO_SOC_Crosswalk.csv
• ISCO-08 OpinionPollCensus.xlsx
• LFData_WB_plus.xlsx

CR Box Analysis

• CR_Box_Countries_MS.csv

Coal Baghouse Analysis

• BaghouseAirflow.csv

Additionally, the dataset STANDARD_COUNTRY_LIST.csv is used throughout the project to standardize the list of countries included in our scale-up estimation and simulations.

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Results

The results folder contains all outputs from our scale-up estimation and simulation processes.

Output Images

Stored in a dedicated subfolder containing static visualizations and figures.

Interactive Outputs

.html files demonstrate interactive simulations and visualizations generated as part of the analysis.

Quantitative Results

Raw numerical results are stored in .csv files.
When uncertainty values (ufloats) are included, a corresponding .pkl file is provided. These .pkl files preserve the uncertainty data structure so that results can be reloaded into code environments without loss of precision or data integrity.

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Scripts

The scripts folder contains all source code used to process data and generate results.
It is organized into two main categories:

• Processing Scripts - handle data, transformation, and scale-up computations.
• Visualizer Scripts - generate plots, charts, and interactive dashboards.

Each script is named to reflect the specific section of the analysis it supports and ends with a suffix