Methods, Challenges, and Practical Issues of COVID-19 Projection: A Data Science Perspective

The coronavirus disease 2019 (COVID-19) pandemic caused by the novel severe acute respiratory syndrome 2 (SARS-CoV-2) has placed epidemic modeling at center of attention public policymaking. Predicting severity and speed transmission COVID-19 is crucial to resource management developing strategies deal with this epidemic. Based on available data from current previous outbreaks, many efforts have been made develop epidemiological models, including statistical computer simulations, mathematical representations virus its impacts, more. Despite their usefulness, forecasting spread remains a challenge. In article, we give an overview unique features issues how they impact projection. addition, illustrate various models could be connected each other. Moreover, provide new science perspectives challenges forecasting, collection, curation, validation limitations as well uncertainty forecast. Finally, discuss some practices that are more robust accurate forecasting.