COVID 19 Data

COVID-19 data analysis focuses on leveraging diverse datasets—including epidemiological time series, patient demographics, environmental factors, and social media posts—to understand the pandemic's dynamics, predict its trajectory, and improve public health responses. Current research employs a range of machine learning techniques, such as deep neural networks (including CNNs and LSTMs), natural language processing models (like BERT and Transformers), and statistical methods (including Bayesian approaches and SARIMA models), to analyze these data. These efforts aim to enhance disease surveillance, improve forecasting accuracy, optimize resource allocation, and combat misinformation, ultimately contributing to more effective pandemic management and preparedness.