Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19
- Title
- Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19
- Creator
- Alluhaidan A.S.; Poonia R.C.; Prabu P.; Alluhaidan M.S.
- Description
- 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.
- Source
- ACM International Conference Proceeding Series, pp. 77-80.
- Date
- 2022-01-01
- Publisher
- Association for Computing Machinery
- Subject
- COVID-19; Mathematical Model; SEIR; Vaccine Inefficacy
- Coverage
- 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
- Rights
- Restricted Access
- Relation
- ISBN: 978-145039763-6
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Alluhaidan A.S.; Poonia R.C.; Prabu P.; Alluhaidan M.S., “Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20052.