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              <text>Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19</text>
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              <text>COVID-19; Mathematical Model; SEIR; Vaccine Inefficacy</text>
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              <text>The uncertainty in life plans, restrictions on physical classrooms, loss of jobs, large number of infections and deaths due to COVID-19 are some significant causes of concern for the public as well as Governments all over the globe. Moreover, the exponential increase in the number of infected people in a short time is responsible for the collapse of the health industry during the pandemic caused by COVID-19. The health experts recommended that the quick and early diagnosis followed by treatment of patients in isolation is a way to minimize its spread and save lives. The objective of this research is to propose a customized SEIR model to predict the trends of vaccination in the USA. The experimental results prove that the Moderna vaccine reports the efficacy of 93%, which is higher than the Pfizer and Johnson and Johnson vaccines.  2022 ACM.</text>
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              <text>Alluhaidan A.S.; Poonia R.C.; Prabu P.; Alluhaidan M.S.</text>
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              <text>ACM International Conference Proceeding Series, pp. 77-80.</text>
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              <text>Association for Computing Machinery</text>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1145/3589437.3589450" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1145/3589437.3589450&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISBN: 978-145039763-6</text>
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              <text>Alluhaidan A.S., Department of Information Systems, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia; Poonia R.C., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Prabu P., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Alluhaidan M.S., Ministry of Defense, Riyadh, Saudi Arabia</text>
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