Evaluating Performance of Mathematical Models to Generate Short-term Forecasts of Chlamydia and Gonorrhea in Georgia, 2017-2019

Disease modeling and forecasting can provide actionable insights for public health planning and intervention. ARIMA was most reliable for stable and increasing trends, while sub-epidemic models better captured declines, highlighting the need to select models based on recent epidemic behavior. GAM and GLM performed competitively in certain contexts but were less robust to sudden changes. Together, these findings support the utility of forecasting methods to improve preparedness and inform STI prevention strategies.