Since early 2020 Covid-19 has casted great shadow to everyone worldwide. Due to large number of infected and death cases, accurate predictions can help the government and medical divisions in pandemic preparedness and prevention. In this paper, we used the Prophet machine learning model to analyze the historical data of the past year to predict the future trend of confirmed, death, recovered total cases. To improve the prediction accuracy, we optimized the data by detecting "turning points"of confirmed cases and then redo predictions. From the result comparison of predictions using original data vs. optimized data it is shown that our optimization improves the prediction accuracy significantly. © 2021 ACM.
Improving Prediction Accuracy of Covid-19 Data Analysis