USING PYTHON TECHNOLOGIES FOR FORECASTING THE SPREAD OF INFECTIOUS DISEASES
Keywords:
infectious diseases, epidemiological forecasting, Python, time series analysis, data analytics, monitoring systems.Abstract
This paper investigates the application of Python-based technologies for forecasting the spread of infectious diseases. The study focuses on methods for collecting, preprocessing, visualizing, and modeling epidemiological data using modern data analysis tools. Time-series analysis and regression-based forecasting algorithms were implemented using Python libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn. The results demonstrate that Python technologies provide an effective and flexible framework for epidemiological monitoring, short-term forecasting of disease dynamics, and decision support in public health systems.
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