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Online User Information Sharing and Government Pandemic Prevention and Control Strategies-Based on Evolutionary Game
Yao Xiao1,2, Wanting Xu1,2, Shouzhen Zeng3
1Center for Innovation and Development Studies, Beijing Normal University, Zhuhai, China.
Frontiers in Public Health
|December 6, 2021
Summary
Online users
Area of Science:
- Public Health
- Information Science
- Behavioral Economics
Background:
- Online user information is crucial for COVID-19 management but poses privacy risks.
- User data sharing and government control decisions are interdependent, impacting public health outcomes.
- Balancing information sharing for pandemic control with personal data privacy is a key challenge.
Purpose of the Study:
- To analyze the interplay between online users' information sharing and government decision-making in COVID-19 control.
- To identify the root causes of inefficiencies in pandemic prevention and control strategies.
- To propose solutions for reconciling privacy concerns with the need for effective public health measures.
Main Methods:
- Utilized evolutionary game models to simulate behavioral patterns.
- Examined the decision-making processes of both online users and government entities.
- Analyzed the dynamics of information disclosure and privacy risks.
Main Results:
- Identified the conflict between individual privacy risks and collective benefits of information sharing.
- Determined that the divergence between individual and collective rationality hinders COVID-19 control efficiency.
- Highlighted the need for strategies that address the inherent contradictions in data sharing for public health.
Conclusions:
- Reconciliation of privacy protection and public health efficiency is achievable.
- Guidance and incentives can effectively modulate internet users' behavior regarding information sharing.
- Addressing behavioral expectations is key to optimizing pandemic response strategies.
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