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Big Data Technology Applications and the Right to Health in China during the COVID-19 Pandemic

Author

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  • Taixia Shen

    (Law School & Intellectual Property School, Jinan University, Guangzhou 510632, China)

  • Chao Wang

    (Faculty of Law, University of Macau, Taipa, Macao 999078, China)

Abstract

Individuals have the right to health according to the Constitution and other laws in China. Significant barriers have prevented the full realisation of the right to health in the COVID-19 era. Big data technology, which is a vital tool for COVID-19 containment, has been a central topic of discussion, as it has been used to protect the right to health through public health surveillance, contact tracing, real-time epidemic outbreak monitoring, trend forecasting, online consultations, and the allocation of medical and health resources in China. Big data technology has enabled precise and efficient epidemic prevention and control and has improved the efficiency and accuracy of the diagnosis and treatment of this new form of coronavirus pneumonia due to Chinese institutional factors. Although big data technology has successfully supported the containment of the virus and protected the right to health in the COVID-19 era, it also risks infringing on individual privacy rights. Chinese policymakers should understand the positive and negative impacts of big data technology and should prioritise the Personal Information Protection Law and other laws that are meant to protect and strengthen the right to privacy.

Suggested Citation

  • Taixia Shen & Chao Wang, 2021. "Big Data Technology Applications and the Right to Health in China during the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(14), pages 1-15, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7325-:d:590821
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    References listed on IDEAS

    as
    1. Lei Qin & Qiang Sun & Yidan Wang & Ke-Fei Wu & Mingchih Chen & Ben-Chang Shia & Szu-Yuan Wu, 2020. "Prediction of Number of Cases of 2019 Novel Coronavirus (COVID-19) Using Social Media Search Index," IJERPH, MDPI, vol. 17(7), pages 1-14, March.
    2. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
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    Cited by:

    1. Weiwei Duan & Tianbao Qin, 2022. "The Impact of China’s Legal System on Public Health and Quality of Life during the COVID-19 Pandemic: An Empirical Study," IJERPH, MDPI, vol. 19(20), pages 1-16, October.

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