Predicting Number of Accumulative Cases of Covid-19 Using the Iteration Method

• Published in: Computational and experimental research in materials and renewable energy Vol. 6; no. 2; pp. 102 - 112
• Main Authors: Zakaria, Christina T., Mursalin, Mursalin, Jahja, Mohamad
• Format: Journal Article
• Language: English
• Published: Physics Department, Faculty of Mathematics and Natural Sciences University of Jember 29.11.2023
• ISSN: 2747-173X; 2747-173X
• DOI: 10.19184/cerimre.v6i2.44205

The COVID-19 pandemic, first identified in Wuhan, China in December 2019, has rapidly spread to various countries, including India and Indonesia. This study utilizes data from the cumulative cases in India and Indonesia, espand specific provinces within Indonesia, such as DKI Jakarta and Gorontalo, spanning a period of approximately two years. The proposed method incorporates factors such as expected recovery and mortality rates to determine the maximum daily growth, which deviates from exponential growth and tends towards stability or decline. RStudio software was employed to estimate future trends based on the current available data. The results indicate that Indonesia, Jakarta, and Gorontalo exhibit a sloping average growth rate over the past 30 days, while India demonstrates linear movement compared to the previous period. A 20% increase in growth rate in Jakarta leads to a significant rise in new cases compared to the other regions. Conversely, a 0% growth rate reduction in India and Gorontalo results in a notable deviation of cumulative case numbers from the actual data. This method can be applied to analyze similar problems if in the future there is another spread of pandemic diseases.Keywords: COVID-19, Iteration Method, Exponential Growth, Gorontalo and DKI Jakarta.