MMAING-AESOP
MMAING-AESOP it is an early outbreak detection model based on the combination of:
- Rt (Time-Dependent Reproduction Number - NGM)
- Ensemble of Machine Learning models (Isolation Forest, LOF, OCSVM, COPOD)
The model generates Early Warning Signals (EWS) based on weekly primary care time series.
If you use MMAING-AESOP in your research, please cite:
Borges, D.G.F., Coutinho, E.R., Cerqueira-Silva, T. et al. Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records. BMC Med Res Methodol 25, 99 (2025). https://doi.org/10.1186/s12874-025-02542-0
Installation and usage
The mmaing_aesop package is available on PyPi. To install it, use the following command:
pip install mmaing_aesop
After installation, you can import the package in your Python script with:
```bash
from mmaing_aesop import MMAING
## Example
```modelo = MMAING(
#enseble
vote_threshold=3,
#outlies
contamination=0.4,
#rt
limiar_rt=1.25,
window_rt=5,
gamma=0.2,
#limites
alpha=0.05,
window_limit=5,
baseline_years=[2017, 2018, 2019],
start_year_detection=2020
)
modelo.fit(df_real[df_real['co_ibge'] == xxxxxx])
modelo.plot(co_ibge=xxxxxx)
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