COVID-19 Mathematical Epidemic Model for Impact Analysis of Large Scale Social Restriction: The Case Study of Indonesia

Abstract

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2. There have been 218,382 confirmed cases of COVID-19, including 8,723 deaths in Indonesia till September 15, 2020. To fight Covid-19, the Indonesian Government modified the lockdown policy to become a large-scale social restriction (LSSR) according to the pandemic level in each region. The LSSR was implemented in DKI Jakarta on April 10, 2020, the epicenter of the Covid-19 outbreak in Indonesia. In this article, we propose the Susceptible-Infected-Hospitalized-Recovered (SIHR) epidemic model for impact analysis of LSSR on epidemic conditions and predict the long-term dynamic COVID-19 in Indonesia. This study extends the SIR model by adding a hospitalized compartment. Finally, we analyze the results of our mathematical model, estimate the model of essential parameters, and predict the disease by considering the real Indonesian cases from March 2 to September 6, 2020. Based on the result, LSSR has a good enough impact on solving the pandemic in Indonesia. One of the factors is because there is a significant difference in transmission rate (β) values. The new normal transmission rate is 75% higher than the LSSR’s.