A Mixed-Integer Programming Model for Optimal Allocation of COVID-19 Vaccines in Davao City

  • Juremae T. Pesidas University of the Philippines Mindanao
  • Giovanna Fae R. Oguis University of the Philippines Mindanao
  • Eliezer O. Diamante University of the Philippines Mindanao
  • Zython Paul T. Lachica University of Oxford and University of the Philippines Mindanao
  • May Anne E. Mata University of the Philippines Mindanao


With the emergence of COVID-19 in Davao City, the need to acquire herd immunity through vaccination is paramount in averting the further spread of the disease in addition to complying with health and safety protocols. This study presents a reformulation of Smalley et al.’s (2015) oral cholera vaccine—mixed-integer programming model (OCV-MIP) to fit the context of the COVID-19 vaccination campaign in the city for 5 years, with consideration of the possible need for annual revaccination, given limited supply and budget resources, to minimize COVID-19 cases further. The population is divided into subgroups with associated incidence rates serving as the basis for the optimal allocation of vaccines. Different ways of population stratification by some combinations of risk areas and age group divisions were explored. The results revealed that it is optimal to prioritize the vaccination of subgroups with the highest incidence rates.

Keywords: forecasting · COVID-19 · Davao City · LINGO · Mixed-Integer Programming · Optimization · Philippines · SARS-CoV-2 · Vaccinet

Interdisciplinary Studies on Health (in partnership with AMDABiDSS-Health)