The present investigation was carried out to study the trends in COVID-19 infected cases and deaths based on the parametric, exponential smoothing and non-parametric regression models by using COVID-19 cumulative infected cases and deaths due to infections The statistically most suited parametric models are selected based on the highest adjusted R2, significant regression co-efficient and co-efficient of determination (R2). Appropriate model is selected based on the model performance measures such as, Root Mean Square Error, Mean Absolute Error, Mean Absolute Percentage Error, assumptions of normality and independence of residuals. Nonparametric estimates of underlying growth functions are computed at each and every time points.