OPTIMIZATION OF COVID-19 VACCINES DISTRIBUTION TO PRIMARY HEALTHCARE CENTERS (PHCCs) IN QATAR

Abstract

Large-scaled distribution of vaccines can be highly complex and dynamic. This thesis aims to propose an integrated framework that addresses the limitations of former literature in optimizing vaccines allocation for controlling the covid-19 outbreak in Qatar. First, we predicted the total positive cases in Doha for the upcoming 14 days using Autoregressive Integrated Moving Average modeling. The best fit model was ARIMA (4,2,4) based on BIC (Bayesian Information Criteria) with an overall MAPE of 4.86% and R^2of 0.9973 values. Then, we formulated a mathematical model to optimally allocate covid-19 vaccines to Primary Healthcare Centers (PHCCs) considering the total associated disease spread risk among the population, operational capacity limitations, and the transfer of ATP (Available to Promise) quantities between the centers. The obtained results provided managerial insights on how decision-makers can create efficient logistical capabilities for covid-19 vaccines allocation.

Date of Award	2022
Original language	American English
Awarding Institution	HBKU College of Science and Engineering