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https://github.com/babak2/outbreak_analyser
https://github.com/babak2/outbreak_analyser
infectious-disease-models matplotlib numpy outbreak-data-analysis outbreak-detection python3
Last synced: 30 days ago
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- Host: GitHub
- URL: https://github.com/babak2/outbreak_analyser
- Owner: babak2
- License: mit
- Created: 2024-01-11T20:06:25.000Z (10 months ago)
- Default Branch: master
- Last Pushed: 2024-01-28T21:55:10.000Z (10 months ago)
- Last Synced: 2024-01-28T22:38:07.196Z (10 months ago)
- Topics: infectious-disease-models, matplotlib, numpy, outbreak-data-analysis, outbreak-detection, python3
- Language: Python
- Homepage:
- Size: 254 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Outbreak Analyser
This project provides an investigation tool for analysing the outbreak of infectious diseases based on reported cases and a gridded representation of the population.
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Getting Started](#getting-started)
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Usage](#usage)
- [Model Output](#model-output)
- [Plot](#plot)
- [Future Extensions](#future-extensions)
- [License](#license)
- [Author](#Author)
## Introduction
The Outbreak Analyser is a Python-based tool designed to study the dynamics of an infectious disease outbreak within a population. Using reported cases and population data, the tool determines the outbreak centre, calculates affected populations, and visualizes the population distribution.
### Problem to Solve
In the context of infectious diseases, understanding the spatial and population dynamics of an outbreak is crucial for effective public health planning. This tool addresses key questions such as:
1. **Outbreak Center:** Where is the outbreak's centre, and what is the impact on the surrounding population?
2. **Affected Population:** What percentage of the population is affected by the outbreak?
3. **Population Visualization:** How can we visualize the population distribution and the outbreak centre?
### Features
- Analysis of infectious disease outbreaks based on reported case locations and population distribution.
- Determination of the outbreak centre.
- Calculation of affected population and percentage.
- Visualization of the population distribution with the outbreak centre.
## Getting Started
To get started with the Outbreak Analyser, follow these steps:
### Prerequisites
Before running the model, make sure you have the following installed:
- [Python](https://www.python.org/) (>=3.6)
- [NumPy](https://numpy.org/)
- [Matplotlib](https://matplotlib.org/)
### Installation
1. Clone the repository:
```bash
git clone https://github.com/babak2/outbreak_analyser.git
Navigate to the project directory:
`cd outbreak_analyser`
## Usage
If Python 3 is the only Python version installed on your machine, you can use the Python command. For example:
```python outbreak_analyser.py ```
If both Python 2 and 3 are installed, it's important to specify Python 3 using the python3 command. For example:
```python3 outbreak_analyser.py ```
## Model Output
After running the outbreak_analyser, you can expect to see the following output in the console:
These values provide information about the outbreak, including the geographical centre, total population, affected population, and the percentage of the population affected.
This information is important for understanding the impact and scope of the simulated outbreak.
## Plot
The plot of the result will be saved in the output directory (default name is outbreak_plot.png).
## Future Extensions
- **Customizable Output Formats:** Provide options to export model results in various formats for further analysis and reporting.
- **Interactive Visualization:** Create interactive visualization to explore better the dynamics of the outbreak.
- **Geographical Visualization:** Enhance visualization capabilities to include geographical maps with overlays of disease spread, population density, and other relevant information.
- **GIS Integration:** Integrate with Geographic Information System (GIS) data to obtain real-world geographical features such as roads, population density, and healthcare facilities.
- **Intervention Strategies:** Implement intervention strategies, such as vaccination campaigns, social distancing, or lockdowns, and analyze their impact on the spread of the disease.
- ...
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Author
Babak Mahdavi Ardestani