Analysis and Forecast of the Number of Deaths, Recovered Cases, and Confirmed Cases From COVID-19 for the Top Four Affected Countries Using Kalman Filter - Ahmadini, Abdullah Ali H.; Naeem, Muhammad; Aamir, Muhammad; Dewan, Raimi; Alshqaq, Shokrya Saleh A.; Mashwani, Wali Khan (Frontiers in Physics, 2021)
The COVID-19 that spread globally severe health complications and substantial economic impact in various parts of the world. The COVID-19 forecast on infections is a significant and crucial information that will help in executing policies to effectively reduces the number of cases. Filtering techniques be a considerable technique to model dynamic structures because they provide good valuations over the recursive Bayesian updates. Kalman filters being one of the filtering techniques are extensively useful in the learning of contagious infections. Kalman filter algorithm performs an important role in the development of an actual and comprehensive approach to inhibit, learn, react, and reduces spreadable disorder outbreaks in people. The purpose of this paper is to forecast the COVID-19 infections using Kalman filter method. The Kalman filter (KF) was applied for the three most affected countries, namely USA, India, and Brazil. Based on the results obtained, the KF method is capable in keeping track with the real COVID-19 data in nearly all scenario. Kalman filter in the archetype background to implement and produce decent COVID-19 predictions. The results of KF method provides benefit in supporting decision making process for short term strategies in handling the COVID-19 outbreak.