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Decision Sciences for COVID-19

Learning Through Case Studies

  • Book
  • © 2022

Overview

Editors:
  1. Said Ali Hassan

    1. Department of Operations Research and Decision Support, Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

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  2. Ali Wagdy Mohamed

    1. Department of Operations Research, Faculty of Graduate studies for Statistical Research, Cairo University, Giza, Egypt

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    You can also search for this editor in PubMed   Google Scholar

  3. Khalid Abdulaziz Alnowibet

    1. Department of Statistics and Operations Research, King Saud University, Riyadh, Saudi Arabia

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  • Presents latest COVID-19 related research and applications in decision sciences
  • Introduces various tools compatible with different applications
  • Includes numerous practical case studies and solutions

Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 320)

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Table of contents (25 chapters)

  1. Front Matter

    Pages i-xx
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  2. Artificial Intelligence

    1. Front Matter

      Pages 1-1
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    2. Application of Artificial Intelligence and Big Data for Fighting COVID-19 Pandemic

      • Joseph Bamidele Awotunde, Sakinat Oluwabukonla, Chinmay Chakraborty, Akash Kumar Bhoi, Gbemisola Janet Ajamu
      Pages 3-26

    3. An IOT-Based COVID-19 Detector Using K-Nearest Neighbor

      • T. M. Okediran, O. R. Vincent, A. A. Abayomi-Alli, O. J. Adeniran
      Pages 27-43

    4. Predictive Analytics for Early Detection of COVID-19 by Fuzzy Logic

      • V. Kakulapati, R. Sai Sandeep, V. Kranthikumar
      Pages 45-65

    5. Role of Artificial Intelligence in Diagnosis of Covid-19 Using CT-Scan

      • Karim Sherif, Yousef Emad Gadallah, Khalil Ahmed, Salma ELsayed, Ali Wagdy Mohamed
      Pages 67-77

    6. Predicting the Pandemic Effect of COVID 19 on the Nigeria Economic, Crude Oil as a Measure Parameter Using Machine Learning

      • Cecilia Ajowho Adenusi, Olufunke Rebecca Vincent, Jesufunbi Bolarinwa, Ologunye Oluwakemi
      Pages 79-93

  3. Forecasting Techniques

    1. Front Matter

      Pages 95-95
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    2. Time Series Analysis and Forecast of COVID-19 Pandemic

      • Pawan Thapa
      Pages 97-106

    3. A Multi-Step Predictive Model for COVID-19 Cases in Nigeria Using Machine Learning

      • Sakinat Oluwabukonla Folorunso, Ezekiel Adebayo Ogundepo, Joseph Bamidele Awotunde, Femi Emmanuel Ayo, Oluwatobi Oluwaseyi Banjo, Abass Ishola Taiwo
      Pages 107-136

    4. Nigerian COVID-19 Incidence Modeling and Forecasting with Univariate Time Series Model

      • Abass Ishola Taiwo, Adedayo Funmi Adedotun, Timothy Olabisi Olatayo
      Pages 137-150

    5. Predicting the Spread of COVID-19 in Africa Using Facebook Prophet and Polynomial Regression

      • Cecilia Ajowho Adenusi, Olufunke Rebecca Vincent, Abiodun Folurera Ajayi, Bukola Taibat Adebiyi
      Pages 151-163

    6. Comparing Predictive Accuracy of COVID-19 Prediction Models: A Case Study

      • Dmitriy Klyushin
      Pages 165-179

  4. Social Sciences

    1. Front Matter

      Pages 181-181
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    2. AIC Algorithm for Entrepreneurial Intention in Covid19 Pandemic

      • Nguyen Thi Ngan, Bui Huy Khoi
      Pages 183-193

    3. Sentiment Analysis for COVID Vaccinations Using Twitter: Text Clustering of Positive and Negative Sentiments

      • Dwijendra Nath Dwivedi, Shailendra Pathak
      Pages 195-203

    4. Participation and Active Contribution of Private Universities in the Prevention of the Covid-19 Pandemic Transmission

      • Mahyudin Ritonga, Ahmad Lahmi, Sandra Ayu, Yufi Latmini Lasari, Sri Wahyuni, Desminar et al.
      Pages 205-215

    5. Effects on Mental Health by the Coronavirus Disease 2019 (COVID-19) Pandemic Outbreak

      • Sanjay Kumar Rout, Duryodhan Sahu
      Pages 217-245

    6. Multimodal Analysis of Cognitive and Social Psychology Effects of COVID-19 Victims

      • V. Kakulapati, S. Mahender Reddy, Sriman Naini
      Pages 247-270

    7. Public Transport Passenger’s Density Estimation Tool for Supporting Policy Responses for COVID-19

      • Nilton A. Henao-Calle, Mateo Arroyave-Quintero, Semaria Ruiz-Alvarez, Danny A. J. Gómez-Ramírez
      Pages 271-284
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Keywords

About this book

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises’ productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem.

 The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.


Editors and Affiliations

  • Department of Operations Research and Decision Support, Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Said Ali Hassan

  • Department of Operations Research, Faculty of Graduate studies for Statistical Research, Cairo University, Giza, Egypt

    Ali Wagdy Mohamed

  • Department of Statistics and Operations Research, King Saud University, Riyadh, Saudi Arabia

    Khalid Abdulaziz Alnowibet

About the editors

Said Ali Hassan is a full professor at the Department of Operations Research and Decision Support, Faculty of Computers and Artificial Intelligence, Cairo University (Egypt). He has published plenty of research papers in respected journals and at conferences and serves as a reviewer for many international journals. His research interests lie broadly in Operations Research, Optimization, Decision sciences, Forecasting, Management science, Strategic management, and modelling-solving of real-life applications.

Ali Wagdy Mohamed is an associate professor at the Department Operations Research, Cairo University (Egypt), and an associate professor of statistics at the Wireless Intelligent Networks Center (WINC), Nile University (Egypt). His research focuses on mathematical and statistical modeling, stochastic and deterministic optimization, swarm intelligence, and evolutionary computation.

Khalid Abdulaziz Alnowibet is an associate professor at the Department of Operations Research, King Saud University (Saudi Arabia). He has published several papers in multiple research areas related to operations research, including stochastic modeling, queueing theory and applications, stochastic processes theory and applications, and modeling communication networks.

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