Spatial Prioritization Model of COVID-19 Vaccine Allocation in Neighborhoods of Mashhad Using AHP and Fuzzy Logic

Reyhane  Jalali; Hossein   Etemadfard; Hamed  Kharaghani; Rouzbeh   Shad; Vahid   Sadeghi

doi:10.18502/tbj.v20i4.7817

Reyhane Jalali M.Sc. Student of GIS, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran
Hossein Etemadfard Assistant Professor, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran.
Hamed Kharaghani M.Sc. Student of GIS, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran
Rouzbeh Shad Associate Professor, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran
Vahid Sadeghi Assistant Professor, Surveying and Geomatics Engineering department, Civil Engineering faculty, University of Tabriz, Tabriz, Iran.

DOI: https://doi.org/10.18502/tbj.v20i4.7817

Keywords: Corona; Vaccine Allocation; AHP; Fuzzy Logic; COVID-19

Abstract

Introduction: With the global outbreak of the COVID-19 and the high mortality rate of this disease, indicates the decision-making and finding a solution to control its spread. One of the most effective ways is to use the COVID-19 vaccine. Due to the limited supply of corona vaccines, the distribution of this vaccine is generally prioritized and is done allocation among individuals.

Methods: In this descriptive correlational study, GIS, AHP tools, and fuzzy logic were used to achieve the goal of prioritizing and allocating corona vaccine in Mashhad neighborhoods. Neighborhoods prioritization in four scenarios was analyzed; Includes scenario AHP, scenario the WHO guideline, scenario guideline of the Ministry of Health and Medical Education of Iran, and scenario localized collective wisdom.

Results: The output of neighborhood prioritization of the four mentioned scenarios has been determined and categorized into five classes. In the AHP scenario, the lowest percentage (8.89%) while the localized collective wisdom highest percentage (42.22%) allocate to priority 1 neighborhoods. There is generally no high correlation between the results and only the scenario of the Ministry of Health and Medical Education and the localized collective wisdom correlates 0.82.

Conclusion: Considering the COVID-19 vaccine shortage, spatial allocation based on the presented guidelines is a reliable method that can meet the basic criteria for allocating limited treatment resources. In This research, the spatial allocation was conducted and 180 neighborhoods throughout the city of Mashhad were identified and prioritized in different scenarios that can assist decision-makers.