Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.5%) to scientific vocabulary
Repository
Sampling growth rates vs Rt
Basic Info
- Host: GitHub
- Owner: SamuelBrand1
- License: unlicense
- Language: TeX
- Default Branch: main
- Size: 8.65 MB
Statistics
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 30
- Releases: 0
Metadata Files
README.md
Evaluating infection-generating processes for infectious disease situational awareness
This repository contains the code, data, and manuscript for our research evaluating whether the inclusion of a renewal process in the latent generative model improves estimation of the effective reproduction number (Rt) and other situational awareness signals for infectious disease surveillance.
Project overview
We systematically evaluate how different infection-generating processes perform across multiple epidemiological outcomes, explicitly examining the decoupling between generative processes and target measures. Our approach:
- Develops a flexible framework (EpiAware) for Rt estimation that allows different latent infection models
- Tests models across simulated scenarios with known outcomes
- Compares performance across different epidemiological outcomes and settings
- Assesses impact of generation interval misspecification
- Provides evidence-based recommendations for model selection
Repository structure
- EpiAware: Julia-based modelling framework with composable components
- Pipeline: Scripts for model fitting, forecasting, and performance evaluation
- Manuscript: Quarto document detailing findings and implications
Paper
The full manuscript is available in main.qmd. We address a critical gap in understanding how different modelling approaches perform across various surveillance tasks, providing evidence-based recommendations for model selection in public health surveillance.
Analysis code
The analysis code is organized in the Rt-without-renewal directory, which contains:
- Model definitions and components
- Simulation infrastructure
- Evaluation metrics and visualizations
Citation
If you use this code or methodology, please cite:
@article{sampling_rt_vs_rt,
title={Evaluating infection-generating processes for infectious disease situational awareness: Is the renewal process necessary?},
author={Brand, Samuel P. C. and Abbott, Sam},
year={2023},
note={Manuscript in preparation}
}
Owner
- Name: Samuel Brand
- Login: SamuelBrand1
- Kind: user
- Location: London, United Kingdom
- Company: Centre for Forecasting and Outbreak Analytics (CDC/CFA)
- Repositories: 16
- Profile: https://github.com/SamuelBrand1
A contracted analyst for CFA/CDC. Formerly a PDRA at Zeeman Institute for Systems Biology and Infectious Disease Epidemiological Research (SBIDER).
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
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getwriting A Minimal Latex Template for Journal
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use the metadata from this file.
type: software
authors:
- given-names: Mukta G.
family-names: Palshikar
affiliation: University of Rochester
orcid: 'https://orcid.org/0000-0002-1179-7903'
GitHub Events
Total
- Issues event: 18
- Push event: 14
- Pull request event: 1
- Create event: 1
Last Year
- Issues event: 18
- Push event: 14
- Pull request event: 1
- Create event: 1
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- seabbs (18)
Pull Request Authors
- seabbs (1)