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Computational Epidemiology

- From Disease Transmission Modeling to Vaccination Decision Making

Über Computational Epidemiology

1 Paradigms in Epidemiology1.1 Methodological Paradigms 1.2 Recent Developments 1.3 Infectious Diseases and Vaccination 1.4 Objectives and Tasks 1.4.1 Modeling Infectious Disease Dynamics 1.4.2 Modeling Vaccine Allocation Strategies 1.4.3 Modeling Vaccination Decision-Making 1.4.4 Modeling Subjective Perception 1.5 Summary 2 Computational Modeling in a Nutshell 2.1 Modeling Infectious Disease Dynamics 2.1.1 Infectious Disease Models 2.1.2 Age-Specific Disease Transmissions2.2 Modeling Contact Relationships 2.2.1 Empirical Methods 2.2.2 Computational Methods 2.3 Case Study 2.3.1 2009 Hong Kong H1N1 Influenza Epidemic 2.3.2 Age-Specific Contact Matrices 2.3.3 Validation2.4 Further Remarks 2.5 Summary 3 Strategizing Vaccine Allocation 3.1 Vaccination 3.1.1 Herd Immunity 3.1.2 Vaccine Allocation Strategy 3.2 Vaccination Priorities 3.3 Age-Specific Intervention Priorities 3.3.1 Modeling Prioritized Interventions 3.3.2 Effects of Vaccination 3.3.3 Effects of Contact Reduction 3.3.4 Integrated Measures 3.4 Case Study 3.4.1 2009 Hong Kong HSI Vaccination Programme 3.4.2 Effects of Prioritized Interventions 3.5 Further Remarks 3.6 Summary 4 Explaining Individuals'' Vaccination Decisions 4.1 Costs and Benefits for Decision-Making 4.2 Game-Theoretic Modeling of Vaccination Decision-Making 4.3 Case Study 4.3.1 2009 Hong Kong HSI Vaccination Programme 4.3.2 Vaccination Coverage 4.4 Further Remarks 4.5 Summary 5 Characterizing Socially Influenced Vaccination Decisions 5.1 Social Influences on Vaccination Decision-Making 5.2 Case Study 5.2.1 Vaccination Coverage 5.3 Further Remarks 5.4 Summary 6 Understanding the Effect of Social Media 6.1 Modeling Subjective Perception 6.2 Subjective Perception in Vaccination Decision-Making 6.2.1 Dempster-Shafer Theory (DST) 6.2.2 Spread of Social Awareness 6.3 Case Study 6.3.1 Vaccination Decision-Making in an Online Social Community 6.3.2 Interplay of Two Dynamics 6.4 Further Remarks 6.5 Summary 7 Welcome to the Era of Systems Epidemiology 7.1 Systems Thinking in Epidemiology 7.2 Systems Modeling in Principle 7.3 Systems Modeling in Practice 7.4 Toward Systems Epidemiology 8 Further Readings References

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783030521073
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 113
  • Veröffentlicht:
  • 19. September 2020
  • Ausgabe:
  • 12020
  • Abmessungen:
  • 155x235x0 mm.
  • Gewicht:
  • 454 g.
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Beschreibung von Computational Epidemiology

1 Paradigms in Epidemiology1.1 Methodological Paradigms
1.2 Recent Developments
1.3 Infectious Diseases and Vaccination
1.4 Objectives and Tasks
1.4.1 Modeling Infectious Disease Dynamics
1.4.2 Modeling Vaccine Allocation Strategies
1.4.3 Modeling Vaccination Decision-Making
1.4.4 Modeling Subjective Perception
1.5 Summary
2 Computational Modeling in a Nutshell
2.1 Modeling Infectious Disease Dynamics
2.1.1 Infectious Disease Models
2.1.2 Age-Specific Disease Transmissions2.2 Modeling Contact Relationships
2.2.1 Empirical Methods
2.2.2 Computational Methods
2.3 Case Study
2.3.1 2009 Hong Kong H1N1 Influenza Epidemic
2.3.2 Age-Specific Contact Matrices
2.3.3 Validation2.4 Further Remarks
2.5 Summary
3 Strategizing Vaccine Allocation
3.1 Vaccination
3.1.1 Herd Immunity
3.1.2 Vaccine Allocation Strategy
3.2 Vaccination Priorities
3.3 Age-Specific Intervention Priorities
3.3.1 Modeling Prioritized Interventions

3.3.2 Effects of Vaccination
3.3.3 Effects of Contact Reduction
3.3.4 Integrated Measures
3.4 Case Study
3.4.1 2009 Hong Kong HSI Vaccination Programme
3.4.2 Effects of Prioritized Interventions
3.5 Further Remarks
3.6 Summary
4 Explaining Individuals'' Vaccination Decisions
4.1 Costs and Benefits for Decision-Making
4.2 Game-Theoretic Modeling of Vaccination Decision-Making
4.3 Case Study
4.3.1 2009 Hong Kong HSI Vaccination Programme
4.3.2 Vaccination Coverage
4.4 Further Remarks
4.5 Summary
5 Characterizing Socially Influenced Vaccination Decisions
5.1 Social Influences on Vaccination Decision-Making
5.2 Case Study
5.2.1 Vaccination Coverage
5.3 Further Remarks
5.4 Summary
6 Understanding the Effect of Social Media
6.1 Modeling Subjective Perception
6.2 Subjective Perception in Vaccination Decision-Making
6.2.1 Dempster-Shafer Theory (DST)
6.2.2 Spread of Social Awareness
6.3 Case Study
6.3.1 Vaccination Decision-Making in an Online Social
Community
6.3.2 Interplay of Two Dynamics
6.4 Further Remarks
6.5 Summary
7 Welcome to the Era of Systems Epidemiology 7.1 Systems Thinking in Epidemiology
7.2 Systems Modeling in Principle
7.3 Systems Modeling in Practice
7.4 Toward Systems Epidemiology
8 Further Readings
References

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