Modeling Social, Health, and Vaccines Intervention in Time of Covid-19 Pandemic Impacted in Jakarta - Indonesia

Abstrak

Since the first outbreak of SARS-CoV-2 worldwide, research on modeling and simulation has grown, particularly to estimate the peak and end time of the pandemic which has been exceeded in some cases. This study aims to model the current virus spread with discrete event simulation, using the case of Jakarta. About 2 million of Jakarta's susceptible population was used for the the model's input which ran for a year. The data was obtained from past records and were divided into three main timelines (i.e. initial stage, large scale restriction and new normal) in order to validate the model with real cases step by step. Scenario analysis was then performed by evaluating five possible interventions such as: existing scenarios, social and health intervention, mass vaccination and hybrid intervention. The results show that the model represents real cases with a variation of less than 5% during the timeline. Furthermore, scenario analysis showed that mass vaccination, hybrid and social intervention provide the least positive cases in the system. This study recommends that hybrid intervention should be used while the vaccine is being mass produced, and the implementation of social intervention should be highlighted.