Jakarta COVID-19 Forecast with Bayesian PIRD Multiwave Model

Christian Evan Chandra, Sarini Abdullah

Abstract


Governments have to consider both socioeconomic and health conditions in handling the COVID-19 pandemic. To help them in understanding possible scenarios behind the numbers and deciding optimum policy, this study proposed a Bayesian protected-infected-recovered-dead (PIRD) multi-wave model. Compounds of the Richards curve are used to understand how many pandemic waves possibly occur, how significant is the occurrence of every single wave, and dynamic in every single wave. The model also estimated the mortality rate due to the COVID-19 pandemic and the duration between infection to death, also infection to recovery. We fitted Jakarta’s COVID-19 data from 3 March 2020 to 25 November 2021 with help of OpenBUGS. We learned that their pandemic should consist of at least two waves, expected to have three waves already. By letting social restriction be looser together with decreasing number of new infection cases, Jakarta could have its fourth and even fifth pandemic wave that starts around mid-May to mid-July 2022 and reach its peak around January to February 2023. Vice versa, they could enter the endemic phase around the end of August 2022 until the beginning of February 2023 and finally have zero COVID-19 new infection around mid-January until mid-June 2023 by having stricter social restrictions.

Keywords


Bayesian inference; COVID-19 forecasting; Data analytics; Multiwave pandemic modeling; Nonlinear regression; Time series modelling

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References


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DOI: https://doi.org/10.17509/ajse.v3i3.47248

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