Integrated Dengue Prediction Dataset with Clinical Biomarkers, Weather Variables, and Risk Indicators (2023–2025)

This dataset contains dengue-related clinical, environmental, and epidemiological records collected from January 2023 to 2025 for predictive analysis and machine learning research. The dataset integrates diagnostic biomarkers such as NS1, IgG, and IgM test results, platelet count, patient outcomes, and infection type along with environmental factors including rainfall, temperature, humidity, and lag-based weather indicators. Additionally, engineered features such as platelet risk, daily case count, case growth, vector index, and seasonal risk levels are included to support predictive modeling, disease surveillance, and public health analytics. This dataset is suitable for: Dengue prediction modeling Classification tasks Risk assessment analysis Public health research Climate-based disease forecasting Dataset format: XLSX Total records: 1500+ Features: 19 columns