A code for fitting multi-wave epidemic models

epidWaves is a Matlab/Python package designed to fit multi-wave statistical models to complex epidemic data. It is based on a parametric statistical framework that combines surveillance data, nonlinear regression, and information criteria to create a statistical model capable of describing multi-wave epidemic outbreaks.

Overview
Features
Usage
Documentation
Reproducibility
Authors
Citing epidWaves
License
Institutional Support
Funding

Overview

epidWaves was developed to address the need for robust modeling of multi-wave epidemic data. By integrating surveillance data with nonlinear regression and information criteria, the package offers a comprehensive solution for fitting complex epidemic models. This tool is particularly useful for researchers and public health officials working to understand and predict the dynamics of epidemic outbreaks.

This package emerged from the combination of several codes used by authors in different publications:

A. Cunha Jr, F. C. Batista, P. R. L. Gianfelice, R. S. Oyarzabal, J. M. V. Grzybowsk, and E. E. N. Macau, epidWaves: A code for fitting multi-wave epidemic models, 14:100391, 2022 DOI
P. R. L. Gianfelice, R. S. Oyarzabal, A. Cunha Jr, J. M. V. Grzybowsk, F. C. Batista, and E. E. N. Macau, The starting dates of COVID-19 multiple waves, Chaos, 32:031101, 2022 DOI
Pavlack et al., EPIDEMIC - Epidemiology Educational Code, Journal of Open Source Education, 5(50), 149, 2022 DOI
F. Batista, A. Cunha Jr., Inferência dos Estágios Iniciais da COVID-19 em Portugal, In: XXIII Congresso Brasileiro de Automática (CBA 2020), 2020, Congresso Virtual, Brazil. DOI

Features

Fits multi-wave statistical models to epidemic data
Combines surveillance data, nonlinear regression, and information criteria
Supports both Matlab and Python implementations
Educational style for ease of use
Includes example scripts for representative benchmark tests

Usage

To get started with epidWaves, follow these steps:

Matlab

Clone the repository:

git clone https://github.com/americocunhajr/epidWaves.git

Navigate to the code directory:

cd epidWaves/epidWaves-1.0/epidWaves_Matlab

For regression on epidemic wave xxx, execute:
```
Main_COVID19_RegressionMC_xxx_wave_RJ
```

Python

Clone the repository:

git clone https://github.com/americocunhajr/epidWaves.git

Navigate to the code directory:

cd epidWaves/epidWaves-1.0/epidWaves_Python

For regression on epidemic wave xxx, execute:

python Main_COVID19_RegressionMC_xxx_wave_RJ.py

Documentation

epidWaves routines are well-commented to explain their functionality. Each routine includes a description of its purpose and a list of inputs and outputs. Examples cases are provided to illustrate the code’s functionality.

Reproducibility

Curve fittings done with epidWaves in the Chaos paper are fully reproducible, as can be seen on this CodeOcean capsule

Authors

Americo Cunha Jr
Fernando da Conceição Batista
Paulo Roberto de Lima Gianfelice
Ricardo Sovek Oyarzabal
Jose Mario Vicensi Grzybowsk
Elbert E. N. Macau

Citing epidWaves

If you use epidWaves in your research, please cite the following manuscripts:

A. Cunha Jr, F. C. Batista, P. R. L. Gianfelice, R. S. Oyarzabal, J. M. V. Grzybowsk, and E. E. N. Macau, epidWaves: A code for fitting multi-wave epidemic models, 14:100391, 2022 https://doi.org/10.1016/j.simpa.2022.100391
P. R. L. Gianfelice, R. S. Oyarzabal, A. Cunha Jr, J. M. V. Grzybowsk, F. C. Batista, and E. E. N. Macau, The starting dates of COVID-19 multiple waves, Chaos, 32:031101, 2022 https://doi.org/10.1063/5.0079904

@article{epidWaves2022,
   author  = {A {Cunha~Jr} and F C Batista and P. R. L. Gianfelice and R S Oyarzabal and J M V Grzybowsk and E E N Macau},
   title   = "{epidWaves: A code for fitting multi-wave epidemic models}",
   journal = {Software Impacts},
   year    = {2022},
   volume  = {14},
   pages   = {100391},
   note    = {10.1016/j.simpa.2022.100391},
}

@article{Gianfelice2022p031101,
   author  = {P. R. L. Gianfelice and R S Oyarzabal and A {Cunha~Jr} and J M V Grzybowsk and F C Batista and E E N Macau},
   title   = "{The starting dates of COVID-19 multiple waves}",
   journal = {Chaos},
   year    = {2022},
   volume  = {32},
   pages   = {031101},
   note    = {10.1063/5.0079904},
}

License

epidWaves is released under the MIT license. See the LICENSE file for details. All new contributions must be made under the MIT license.

epidWaves