Modeling COVID-19 Prevention from Influenza Symptoms Using Kalman Filter Approach

• Published in: ICSPIS 2023 - Proceedings of the 9th International Conference on Signal Processing and Intelligent Systems
• Main Author: Putra Y.H.; Rahman N.A.; Zukarnain Z.A.; Wahdiniwaty R.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184849450&doi=10.1109%2fICSPIS59665.2023.10402787&partnerID=40&md5=43f43c725b499e9fe9fe6ecd5d58a508
• DOI: 10.1109/ICSPIS59665.2023.10402787

Several countries have stopped community restriction program activities in dealing with COVID-19, including in Indonesia which has stopped a similar program at the end of 2022. Each country is starting a new era, namely the COVID-19 prevention program, but not all countries have accurate data regarding the type symptoms that could be indicators of prevention. This inaccuracy will be overcome using the behavior of the Kalman Filter while the presumption that influenza symptoms can be use to approach the COVID-19 symptoms. Various Kalman Filter models will be tried which represent the level of concern for prevention, which we call the COVID-19 Pandemic Precaution Level (PCP). The data for this study were obtained from a number of symptoms encountered that resemble the symptoms of COVID-19 after 2022. And provide the results of several Kalman Filter models for normal worries and extreme worries. © 2023 IEEE.