A decision support system for the optimal allocation and distribution of COVID-19 vaccines using analytic hierarchy process (AHP) and integer programming (IP) model

Author:

Culaste Hannah Faye C.,Torres Noe Jay D.,Lachica Zython Paul T.,Lorono Honey Glenn P.,Inguillo Ross Fievanni,Mata May Anne E.,Namoco Rhoda A.

Abstract

IntroductionIn the Philippines, scheduling the COVID-19 vaccine rollout has been a challenging task. The local government units (LGUs) have to carefully work with limited resources to avoid underutilizing vaccines while considering prioritization schemes in the rollout. As the country continues to vaccinate its population to manage the spread of COVID-19, planning the prioritization of individuals becomes more apparent in the vaccination rollout with respect to the COVID-19 situation in their respective areas.MethodsOur study develops a location-allocation model that aims to optimally schedule the COVID-19 vaccine rollout of a municipality. Here we applied the analytic hierarchy process (AHP) to determine the prioritization of communities (i.e., barangays) in the vaccine rollout based on the number of COVID-19 cases, the population density, and the proximity of the community to the available vaccine sites. Consequently, an integer programming (IP) model was formulated to determine the assignment of individuals to the vaccine stations with respect to the prioritization of their community in the rollout, as well as the minimum number of vaccine stations to open.Results and discussionThe AHP-based IP model proposed in this study not only assigns individuals to vaccination centers, but is also capable of tailoring the vaccine rollout to prioritize individuals depending on the preferences of the LGUs, and the COVID-19 situation in their areas. Furthermore, the vaccine rollout framework in this work is applicable to other vaccine-preventable diseases (e.g., rabies, measles, etc.) should LGUs embark on adapting this approach.

Publisher

Frontiers Media SA

Subject

Applied Mathematics,Statistics and Probability

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