COVID-19 Vaccine: A neutrosophic MCDM approach for determining the priority groups
Since the outbreak of COVID-19, most of the countries around the world have been confronting the loss of lives,
struggling with several economical parameters, i.e. low GDP growth, increasing unemployment rate, and others.
It’s been 11 months since we are struggling with COVID-19 and some of the countries already facing the second
wave of COVID-19. To get rid of these problems, inventions of a vaccine and its optimum distribution is a key
factor. Many companies are trying to find a vaccine, but for nearly 8 billion people it would be impossible to find
a vaccine. Thus, the competition arises, and this competition would be too intense to satisfy all the people of a
country with the vaccine. Therefore, at first, governments must identify priority groups for allocating COVID-19
vaccine doses. In this work, we identify four main criteria and fifteen sub-criteria based on age, health status, a
woman’s status, and the kind of job. The main and sub-criteria will be evaluated using a neutrosophic Analytic
Hierarchy Process (AHP). Then, the COVID-19 vaccine alternatives will be ranked using a neutrosophic TOPSIS
method. All the results obtained indicate that the healthcare personnel, people with high-risk health, elderly
people, essential workers, pregnant and lactating mothers are the most prioritized people to take the vaccine
dose first. Also, the results indicate that the most appropriate vaccine for patients and health workers have
priority over other alternative vaccines.
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In this work, we propose a new dynamic mathematical model framework governed
by a system of differential equations that integrates both COVID-19 and cholera
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