Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Oct:172:108602.
doi: 10.1016/j.cie.2022.108602. Epub 2022 Aug 27.

Blockchain solution benefits for controlling pandemics: Bottom-up decentralization, automation with real-time update, and immutability with privacy preservation

Xiaoming Li  1 , Huigang Liang  2
Affiliations

Blockchain solution benefits for controlling pandemics: Bottom-up decentralization, automation with real-time update, and immutability with privacy preservation

Xiaoming Li et al. Comput Ind Eng. 2022 Oct.

Abstract

The current COVID-19 pandemic has created turmoil around the world. To fight this ongoing global crisis and future ones, all stakeholders must collaborate and share timely and truthful information. This paper proposes a blockchain solution based on its inherent technological advantages. We posit that benefits can be derived from three unique blockchain features: bottom-up decentralization, automation with real-time update, and immutability with privacy preservation. A decentralized common platform provides easy access and increases participation in disease surveillance, which reduces the estimation errors of the compartmental model parameters. Automation with real-time update facilitates prompt detection and diagnosis, accurate contact tracing, and targeted mitigation and containment, achieving faster recovery and slower transmission. Being immutable while preserving privacy, the blockchain solution enhances respondents' willingness to truthfully report their contact history, avoiding false and erroneous data that will cause wrong estimates on pandemic transmission and recovery. Thus, the blockchain solution mitigates three types of risks: sample variance, delay, and bias. Through simulation, we quantify the value of the blockchain solution in these three aspects. Accordingly, we provide specific action plans based on our research findings: before building blockchain solutions for controlling COVID-19, governments and organizations can calculate the blockchain benefits and decide whether or not they should invest in such blockchain solutions by conducting a cost-benefit analysis.

Keywords: Blockchain; COVID-19 pandemic; Epidemic outbreaks; Risk management.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Difference between centralized applications and DApps.
Fig. 2
Fig. 2
A blockchain solution for pandemics.
Fig. 3
Fig. 3
Davidson County’s daily cases in 2020 and our estimated instantaneous reproduction number.
Fig. 4
Fig. 4
The evolution of susceptible, infected, and recovered fractions over time.
Fig. 5
Fig. 5
The 100-round evolutions of susceptible, infected, and recovered fractions in four scenarios.
Fig. 6
Fig. 6
The response surface of the total and maximum infected fraction at different levels of blockchain benefits.
Fig. 6
Fig. 6
The response surface of the total and maximum infected fraction at different levels of blockchain benefits.
Fig. 7
Fig. 7
Evolutions of susceptible, infected, and recovered fractions over time for 50% reporting.
Fig. 7
Fig. 7
Evolutions of susceptible, infected, and recovered fractions over time for 50% reporting.
Fig. 8
Fig. 8
The ending recovered fractions (i.e., the total infected) and their relative deviations in three scenarios.
Fig. 9
Fig. 9
The ending recovered (total infected) fractions at different levels of underreporting and transmission rates.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Abutaleb, Y., & Sun, L. H. (2021). How CDC data problems put the U.S. behind on the delta variant. Washington Post accessed August 23, 2021, available at https://www.washingtonpost.com/health/2021/08/18/cdc-data-delay-delta-va....
    1. Ahmadi, M., Taghavirashidizadeh, A., Javaheri, D., Masoumian, A., Ghoushchi, S. J., & Pourasad, Y. (2021b). DQRE-SCnet: A novel hybrid approach for selecting users in federated learning with deep-Q-reinforcement learning based on spectral clustering. Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2021.08.019.
    1. Ahmadi M., Sharifi A., Khalili S. Presentation of a developed sub-epidemic model for estimation of the COVID-19 pandemic and assessment of travel-related risks in Iran. Environmental Science and Pollution Research. 2021;28:14521–14529. - PMC - PubMed
    1. Araz O.M., Choi T.-M., Olson D.L., Salman F.S. Role of analytics for operational risk management in the era of big data. Decision Sciences. 2020;51(6):1320–1346.
    1. Banco, E. (2021). Inside America’s Covid-reporting breakdown. Politico, accessed August 23, 2021, available at https://www.politico.com/news/2021/08/15/inside-americas-covid-data-gap-....

LinkOut - more resources