COVID-19 AGENT-BASED MODEL: AN EPIDEMIOLOGICAL SIMULATOR APPLIED IN VACCINATION SCENARIOS FOR QUEZON CITY, PHILIPPINES
- 1Department of Computer Science, College of Engineering, University of the Philippines Diliman, Quezon City, Philippines
- 2College of Medicine, University of the Philippines Manila, Manila, Philippines
- 3College of Social Work and Development, University of the Philippines Diliman, Quezon City, Philippines
- 4Center for Informatics, University of San Agustin, Iloilo City, Iloilo, Philippines
Keywords: COVID-19, Vaccine Distribution, Agent-Based Model, Linear Programming
Abstract. COVID-19 vaccines are rolling out in the Philippines but the supply remains limited; there is a need to optimize the distribution. In this study, we developed a COVID-19 agent-based model for Quezon City, a COVID-19 hotspot in the country. This model, in conjunction with a multi-objective linear programming model for equitable vaccine distribution, was then used to simulate four vaccination scenarios. Experiments were conducted with the front-line workers always added to the groups: mobile workers, elderly and low-income. Main results are: prioritizing the mobile workers minimizes infections the most (by 4.34%), while prioritizing the low-income groups minimizes deaths the most (by 1.93%). These results demonstrate that protecting the population with the most interactions (mobile workers) effectively reduces future infections. On the other hand, protecting the most vulnerable population (low income and elderly) decreases the likelihood of death. These results may guide the policy-makers in Quezon City.