How Data Can Manage Global Health Pandemics: Analyzing and Understanding Covid-19

Description

In contrast to the 1918 Spanish flu pandemic which occurred in a non-digital age, the timing of the COVID-19 pandemic intersects with the digital age which is characterized by the collection and availability of large amounts of data and sophisticated technologies. Data and technology are being used to combat this digital age pandemic in ways that were not possible in the pre-digital age. Given the adverse impacts of pandemics in general and the COVID-19 pandemic in particular,  it is imperative that people understand the meaning and origin of pandemics, related terms (for example, epidemic, super spreader, and patient zero), trajectory of a new disease, butterfly effect of contagious diseases, factors governing the pandemic potential of a disease, pandemic preparedness and strategies to combat a pandemic at different levels (individual, community, organizational, national, and global), role of data,  data sharing, data strategy, data governance, analytics, and data visualization in managing pandemics, pandemic myths, critical success factors in managing pandemics, and lessons learnt. This book discusses these elements with special reference to COVID-19. The book does not assume any prior or specialist knowledge in pandemics, strategies, data, data governance, analytics or data visualization. This book is technology agnostic and contains a large number of illustrations and examples from COVID-19, making it easy for the readers to understand and relate to the concepts discussed in this book. Target Audience: ·  On a broad level the target audience is the scientific community, policy makers and professionals across the domains of health, management, risk, strategy and data. The book is specifically beneficial for university students, academicians, professors, researchers, and industry professionals. Even the general public will find this book useful and interesting. ·  Courses where health, pandemics, strategies, and data analytics are a part of the course curriculum. Some courses include Bachelor's and Master Degree in Information Technology, Computer Science, Data Analytics, Epidemiology, Biomedical Informatics, and Management. Cover Title Copyright Dedication Contents List of Figures List of Tables Foreword Preface Acknowledgments About the Author 1 Pandemic—An Introduction Introduction What Is a Pandemic? Pandemic—Definitions Characteristics of Pandemics Large Geographic Spread Person-to-Person Spread High Transmission Rates and Explosiveness Novelty Minimal Population Immunity Infectiousness Severity Origin of Pandemic Notable Pandemics in History Pandemics, COVID-19, Technology, Data, and Analytics in the 21st Century Concluding Thoughts References 2 Data—Management, Strategy, Quality, Governance, and Analytics Delving into the Definition of Data Varieties of Data Structured Data Unstructured Data Semi-Structured Data Big Data versus Traditional Data Volume Velocity Variety Organization of Data Data Management Data Strategy Data Quality Data Quality Dimensions Data Quality Management Data Governance Data Analytics Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Concluding Thoughts References 3 Trajectory and Stages of a New Disease Introduction New Disease Trajectory—From Darkness to Light Contagious Disease and Butterfly Effect Contact Tracing and Disease Transmission Epidemic, Pandemic, Outbreak, and Endemic Index Case, Primary Case, Secondary Case, Patient Zero, and Super Spreaders Index Case Primary Case Secondary Case Patient Zero Super Spreaders Epidemiological Parameters Stages of a Disease and Pandemic Status Disease Stages as Defined by Centers for Disease Control and Prevention Disease Stages as Defined by WHO Stages of Spread of a Pandemic as Defined by Yigitcanlar et al. (2020), Bharat (2020) Flattening the Curve Concluding Thoughts References 4 COVID-19—A Pandemic in the Digital Age Introduction COVID-19 Pandemic Predictions Coronaviruses What Is COVID-19? Who Was Patient Zero in COVID-19? COVID-19—From a Localized Outbreak into a Global Pandemic COVID-19 Features Spread and Impact of COVID-19—What Does the Data Say Concluding Thoughts References 5 Data and Pandemic in the Digital World Data, Technology, Digital World, and Pandemic Types of Data from a Pandemic Analytics Perspective Role of Data in Pandemic Big Data Sources and Pandemic Management Use of External Data and Data Sharing in a Pandemic Data Challenges in a Pandemic—COVID-19 as an Example Data Collection Misinformation Data Quality Data Definition and Metadata Data Security, Data Protection, and Data Privacy Concluding Thoughts References 6 Data Analytics and Pandemic Pandemics and Data Analytics Data Analytics Use Cases in the Pandemic Predicting Virus Spread Medical Imaging New Drug Development Modeling Infection Severity Combating Misleading Information Vaccine Development, Management, and Distribution Pandemics, Analytics, and Retail Pandemics, Analytics, and Finance COVID-19—Examples of Data Analytics Application in Different Industry Sectors Data Visualization and Its Role in a Pandemic Concluding Thoughts References 7 Disease and Pandemic Potential Pathogens and Pandemic Potential Factors Determining Pandemic Potential Concluding Thoughts References 8 Pandemic and Critical Success Factors An Introduction to Pandemic Myths and Critical Success Factors Pandemic Myths Myth 1. Pandemics Are Public Health Problem Only Myth 2. Pandemics Are Extremely Rare and Have Short-Term Impacts Myth 3. Doctors Are Aware of All the Infectious Diseases Myth 4. Infrastructure, Resources, and Capacity Are There to Detect and Effectively Respond to Pandemics Myth 5. Disease Emergence Is Unavoidable, and No One Can Do Anything About It Critical Success Factors to Manage a Pandemic Government and Leadership Capacity to Trace, Test, and Treat Education and Training Pandemic Preparedness and Strategies Communication Technology and Data Collaboration, Coordination, and Global Solidarity Concluding Thoughts References 9 Pandemic Preparedness and Strategies Preparing for a Pandemic Pandemic and Strategies Data Strategy and the Pandemic Concluding Thoughts References 10 Pandemic—Lessons Learned and Future Ahead Introduction Lessons from Past Pandemics—With Special Reference to 1918 Spanish Flu COVID-19 Pandemic—Specific Lessons 1. Save Nature 2. Government and Leadership Lessons 3. Transparency, Effective Governance, and Timely Release of Relevant Information 4. Non-Pharmaceutical Interventions and Pharmaceutical Precautions 5. Robust Health Surveillance System 6. Testing Responsiveness and Resilience of Health Systems and Action Plan to Balloon Healthcare Infrastructure 7. Funding Research and Development (R&D) 8. Opportunities to Use Novel Approaches and Technologies 9. Leverage Data 10. Communication and Collaboration Concluding Thoughts References Appendix A: Abbreviations and Acronyms Appendix B: Glossary of Terms References Index