A mathematical model for equitable in-country COVID-19 vaccine allocation

Name: A mathematical model for equitable in-country COVID-19 vaccine allocation
Author: Koyuncu, Burcu Balçık, Yücesoy, Ecem, Akça, Berna, Karakaya, Sırma, Kaplan, Asena Ayse, Baharmand, H., Sgarbossa, F.

İsim	A mathematical model for equitable in-country COVID-19 vaccine allocation
Yazar	Koyuncu, Burcu Balçık, Yücesoy, Ecem, Akça, Berna, Karakaya, Sırma, Kaplan, Asena Ayse, Baharmand, H., Sgarbossa, F.
Basım Tarihi:	2022
Basım Yeri	- Taylor and Francis
Konu	Case study, COVID-19, Equity, Integer programming, Vaccine allocation
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0020-7543
Kayıt Numarası	cd532df6-4208-4ee4-a51f-5abed1e278ee
Lokasyon	Industrial Engineering
Tarih	2022
Notlar	Norges Forskningsråd
Örnek Metin	Given the scarcity of COVID-19 vaccines, equitable (fair) allocation of limited vaccines across the main administrative units of a country (e.g. municipalities) has been an important concern for public health authorities worldwide. In this study, we address the equitable allocation of the COVID-19 vaccines inside countries by developing a novel, evidence-based mathematical model that accounts for multiple priority groups (e.g. elderly, healthcare workers), multiple vaccine types, and regional characteristics (e.g. storage capacities, infection risk levels). Our research contributes to the literature by developing and validating a model that proposes equitable vaccine allocation alternatives in a very short time by (a) minimising deviations from the so-called ‘fair coverage’ levels that are computed based on weighted pro-rata rations, and (b) imposing minimum coverage thresholds to control the allocation of vaccines to higher priority groups and regions. To describe the merits of our model, we provide several equity and effectiveness metrics, and present insights on different allocation policies. We compare our methodology with similar models in the literature and show its better performance in achieving equity. To illustrate the performance of our model in practice, we perform a comprehensive numerical study based on actual data corresponding to the early vaccination period in Turkey.
DOI	10.1080/00207543.2022.2110014
Cilt	60

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A mathematical model for equitable in-country COVID-19 vaccine allocation

Yazar Koyuncu, Burcu Balçık, Yücesoy, Ecem, Akça, Berna, Karakaya, Sırma, Kaplan, Asena Ayse, Baharmand, H., Sgarbossa, F.

Basım Tarihi 2022

Basım Yeri - Taylor and Francis

Konu Case study, COVID-19, Equity, Integer programming, Vaccine allocation

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0020-7543

Kayıt Numarası cd532df6-4208-4ee4-a51f-5abed1e278ee

Lokasyon Industrial Engineering

Tarih 2022

Notlar Norges Forskningsråd

Örnek Metin Given the scarcity of COVID-19 vaccines, equitable (fair) allocation of limited vaccines across the main administrative units of a country (e.g. municipalities) has been an important concern for public health authorities worldwide. In this study, we address the equitable allocation of the COVID-19 vaccines inside countries by developing a novel, evidence-based mathematical model that accounts for multiple priority groups (e.g. elderly, healthcare workers), multiple vaccine types, and regional characteristics (e.g. storage capacities, infection risk levels). Our research contributes to the literature by developing and validating a model that proposes equitable vaccine allocation alternatives in a very short time by (a) minimising deviations from the so-called ‘fair coverage’ levels that are computed based on weighted pro-rata rations, and (b) imposing minimum coverage thresholds to control the allocation of vaccines to higher priority groups and regions. To describe the merits of our model, we provide several equity and effectiveness metrics, and present insights on different allocation policies. We compare our methodology with similar models in the literature and show its better performance in achieving equity. To illustrate the performance of our model in practice, we perform a comprehensive numerical study based on actual data corresponding to the early vaccination period in Turkey.

DOI 10.1080/00207543.2022.2110014

Cilt 60