VOLUME 18 (Supplement)

Dengue incidence in Baguio City: An application of a compartmental model to Baguio City data for years 2011 to 2022

Baguio City's dengue incidence data for years 2011 to 2022 exhibit three-year cycles of increasing amplitudes. However, current epidemiological models do not capture this behavior. This study modifies the dengue disease model presented in the paper by de los Reyes and Escaner (2018), introducing two key modifications: (1) incorporating logistic growth in the human population and (2) including seasonality in mosquito population growth. With the observed multi-year cycles for disease progression in the city, the model is calibrated to Baguio data to estimate epidemiologically important parameters such as transition rate from susceptible to hospitalized humans, vector biting rate, transmission probability from human to vector and vector to human. A constrained-ODE optimization routine is used to determine model parameter values that produce model curves capturing the dynamics of dengue incidence in Baguio. Using these estimated parameters, simulations are presented with variations observed over cycles each spanning 3 years. Reproduction numbers are calculated, with values ranging from 1.39 (2011–2013) to 1.67 (2014–2016). Sensitivity analysis and parameter bootstrapping are also performed to determine confidence intervals. Results of the study yield city-specific parameter estimates which can guide policy makers in forecasting, in evaluating the impact of interventions, as well as in making decisions towards optimizing the timing and intensity of vector-control measures.