Abstract: The present invention relates to a method and system for early detection of COVID-19. Existing methods require data from multiple sensors for training a prediction model whose output is considered as final prediction which is actually the prediction for a particular day or time instance. However, this prediction doesn't detect actual infection of COVID-19 since it requires monitoring the change in health of the user over consecutive days. Embodiments of present disclosure overcome these challenges by a prediction model for COVID-19 which requires only data from Photoplethysmography (PPG) sensor seamlessly collected from a wearable device still able to provide accurate COVID-19 prediction with application of a post processing technique on the predictions of the prediction model. Since COVID-19 symptoms have an effect on heartrate and oxygen saturation which are effectively captured by PPG sensor data, studying these dynamics during infection period gives insights to perform early detection of COVID-19.