Regression Modeling of Dengue Incidence Using Time-Lagged Meteorological Factors


  • Rosenel T. Dahipon ⋅ PH National Institute of Physics, University of the Philippines Diliman, Quezon City, Philippines
  • Daniel Vincent M. Navalta ⋅ PH Department of Physical Sciences, Polytechnic University of the Philippines, Manila, Philippines
  • Rhenish C. Simon ⋅ PH Physics Department, De La Salle University, Manila, Philippines


We develop simple models using three regression techniques — LM, PM, and GLM — to investigate the influence of C with d in the National Capital Region (NCR). We use the C with various time lags to determine the highest coefficient of determination r2, which we employed to develop the models. Subsequently, we determined which model, utilizing C data from stations SG, N, and PA, best described the distribution of dengue incidences in the NCR based on their corresponding r2 values. Our results show that linear model LM with the data from N station can best explains the variability of dengue cases in the NCR.


Article ID



Poster Session B (Complex Systems, Computational Physics, and Astrophysics)



How to Cite

RT Dahipon, DVM Navalta, and RC Simon, Regression Modeling of Dengue Incidence Using Time-Lagged Meteorological Factors, Proceedings of the Samahang Pisika ng Pilipinas 42, SPP-2024-PB-14 (2024). URL: