Dengue Cases in Colombia: Mathematical Forecasts for 2018-2022

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Dengue, a mosquito-borne viral disease, poses a significant global health challenge, exacerbated by climate change.
• Colombia faces a serious dengue situation, with high incidence and mortality rates reported.
• Mathematical and statistical models are crucial for understanding dengue transmission dynamics and informing control strategies.

Purpose of the Study:

• To forecast dengue case numbers in Colombia from 2018 to 2022 using the Auto-Regressive Integrated Moving Average (ARIMA) model.
• To determine the basic reproduction number for dengue in the year with the highest predicted cases by integrating ARIMA forecasts with an ordinary differential equations (ODE) model.

Main Methods:

• An ecological time series study utilized dengue case data from Colombia's National Health Institute (2009-2017).
• The stochastic ARIMA model was applied for forecasting dengue incidence.
• Nonlinear least squares regression was used to adjust ODE model parameters and calculate vectorial capacity.

Main Results:

• The ARIMA model forecasted the highest dengue incidence in Colombia for 2019 (88,221 cases), with other years also showing significant numbers.
• Estimated parameters for dengue transmission in 2019 indicated peak cases in the second quarter.
• The basic reproduction number was consistently above 1 throughout 2019, suggesting disease persistence.

Conclusions:

• The ARIMA model predicts 2019 as the peak year for dengue incidence in Colombia between 2018-2022.
• Integrating ARIMA and ODE models provides projections for dengue case variations and persistence.
• The basic reproduction number exceeding 1 in 2019 indicates that dengue will likely persist in Colombia throughout the year.