Mobility-guided Modeling of the COVID-19 Pandemic in Metro Manila

Abstract

Coronavirus disease 2019 (COVID-19) is a novel respiratory disease first identified in Wuhan, China, that is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To better understand the dynamics of the COVID-19 pandemic in the Philippines, we have used real-time mobility data to modify the DELPHI epidemiological model recently developed at the Massachusetts Institute of Technology (MIT) and to simulate the pandemic in Metro Manila. We have chosen to focus on the National Capital Region (NCR), not only because it is the nation’s demographic heart where over a tenth of the country’s population lives, but also because it has been the epidemiological epicenter of the Philippine pandemic. Our UST CoV-2 model suggests that the government-imposed enhanced community quarantine (ECQ) has successfully limited the spread of the pandemic. It is clear that the initial wave of the pandemic is flattening, though suppression of viral spread has been delayed by the local pandemics in the City of Manila and Quezon City. Our data also reveals that replacing the ECQ with a general community quarantine (GCQ) will increase the forecasted number of deaths in the nation’s capital unless rig