Model development and validation
COPD
VIRUS, EVENT, COPD, REGRESSION, INFLUENZA
All moderate to severe exacerbation were used as outcome variable, and the number of claims were used as individual event to analyze exacerbations. Based on each number of claims, participants of KOCOSS cohort were divided into training and internal validation dataset. We chose demographic data including age and sex, spirometry data, COPD related medications including inhaler treatment and systemic steroids and hospital visit for AE, air pollution data and meteorological data, and influenza virus data as relevant risk factors for the final model for prediction of moderate and/or severe exacerbation. Then, six machine learning and logistic regression tools were used to evaluate the performance of the model. Formula of prediction equation generated by GEE analysis was detailed in the supplementary methods.The model will be reliable only if validated using data from other dataset. We validated our model using the KNHANES cohort; KNHANES conducts an annual, nationally representative study regarding the health and nutritional status of the South Korean population. We used data concerning 2151 individuals with FEV