In Search of an Alternative to "Strict Lockdown"; Data-driven Policies in the Face of COVID-19 Pandemic

Document Type : Promotional article

Authors

1 GPTT

2 University of Tehran

3 Sharif Policy Research Institute (SPRI), Sharif University of Technology, Tehran, Iran

Abstract

The world noticed an emerging virus in the Chinese city of Wuhan, in early January. At first, no one was concerned – officials said it was not infectious – so on Chinese New Year, it was considered a local problem that was published coincidentally. Today, after about 300 days of lockout, which is limited to the coronavirus outbreak's epicenter, it has spread all over the world, with every aspect of life, including the ruin of companies. Some countries faced the crisis preferring the use of big data governance over just maximum physical isolation. Notably, some Southeast Asian countries, such as Taiwan, South Korea, Japan, and Singapore, have adopted a set of smart strategies based on data science and disruptive techs to enhance the crisis management process. Past work indicates a major difference in terms of results and overall efficacy between the smart data-driven approach and the strict lockdown policy. This point of view attempts to address these gaps by making distinctions based on knowledge obtained from two approaches. Therefore, it holds a critical position on the extent of progress for each nation, which is the embeddedness of such an integrated strategy in both socio-cultural and political contexts. The paper investigates Iranian experiences of data-driven responses to COVID-19, namely Mask application and the Ministry of Health and Medical Education's online self-assessment, regarding their contribution to the crisis management process. Thus, it seems that integrating success around the problem mentioned above, threatening human existence, requires a cohesive governance strategy that allows people of the digital age to be mobilized for a public interest, social security, and public health.

Keywords

References

Boulos, M. N. K., Resch, B., Crowley, D. N., Breslin, J. G., Sohn, G., Burtner, R., Pike, W. A., Jezierski, E., & Chuang, K.-Y. S (2011). Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples. International journal of health geographics, 10 (1), 67.
Crowley, J., & J. Chan (2011). Disaster relief 2.0: the future of information sharing in humanitarian emergencies, Harvard Humanitarian Initiative and UN Foundation-Vodafone Foundation-UNOCHA.
Dong, E., Du, H., & Gardner, L (2020).  An interactive web-based dashboard to track COVID-19 in real time. Thelancet, 20 (5), 533-534. DOI:https://doi.org/10.1016/S1473-3099(20)30120-1.
 
Gardner, L (2020). Mapping COVID-19. Johns Hopkins University:
 https://systems.jhu.edu/research/public-health/ncov/.
 
Greene, T (2020). Alibaba’s new AI system can detect coronavirus in seconds with 96% accuracy. Thenextweb: https://thenextweb.com/neural/2020/03/02/alibabas-new-ai-system-can-detect-coronavirus-in-seconds-with-96-accuracy/.
Kingsley-Hughes, A (2020). Join the battle against COVID-19 coronavirus using your computer. Zdnet: https://www.zdnet.com/article/how-you-can-use-your-computer-to-help-fight-covid-19-coronavirus/
Palen, L., Vieweg, S., Sutton, J., Liu, S. B., & Hughes, A. L (2007). Crisis informatics: Studying crisis in a networked world. Proceedings of the Third International Conference on E-Social Science.
Qadir, J., Ali, A., Rasool, R., Zwitter, A., Sathiaseelan, A., & Crowcroft, J (2016). Crisis Analytics: Big Data Driven Crisis Response. Journal of International Humanitarian Action, 1. 10.1186/s41018-016-0013-9.
 
Rajkumar, S (2020). Novel Corona Virus 2019 Dataset. Kaggle:
 https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset.
 
Rapoport, A (1968). General system Theory. International Encyclopedia of social science, 15, 453.
Ray, T (2020). Google DeepMind’s effort on COVID-19 coronavirus rests on the shoulders of giants. Zdnet: https://www.zdnet.com/article/google-deepminds-effort-on-covid-19-coronavirus-rests-on-the-shoulders-of-giants/
Salathe, M., Bengtsson, L., Bodnar, T. J., Brewer, D. D., Brownstein, J. S., Buckee, C., Campbell, C. Cattuto, E. M., Khandelwal, S., & Mabry P. L (2012). Digital epidemiology. PLoS Comput Biol, 8(7), e1002616, 2012.
Scott, M (2020). Social media giants are fighting coronavirus fake news. It’s still spreading like wildfire. Politico: https://www.politico.com/news/2020/03/12/social-media-giants-are-fighting-coronavirus-fake-news-its-still-spreading-like-wildfire-127038.
Zhua, L., Anagondahallib, D., & Zhangc, A (2017). Social media and culture in crisis communication: McDonald’s and KFC crises management in China. Public Relations Review, 43, 487–492.
--- (2020). 2019-wuhan-coronavirus-data. Github: https://github.com/globalcitizen/2019-wuhan-coronavirus-data.
--- (2020). Americans Give Higher Ratings to South Korea and Germany Than U.S. for Dealing With Coronavirus. Pewresearch: https://www.pewresearch.org/global/2020/05/21/americans-give-higher-ratings-to-south-korea-and-germany-than-u-s-for-dealing-with-coronavirus/.
--- (2020). COVID-19 pandemic in Iran. Wikipedia:  https://en.wikipedia.org/wiki/COVID-19_pandemic_in_Iran.
--- (2020). Dutch data scientists can predict Corona infections per country. Innovationorigins: https://innovationorigins.com/dutch-data-scientists-can-predict-corona-infections-per-country/.
 
--- (2020). Facebook says no to fake news, joins hands with WHO to combat misinformation about coronavirus. Economictimes:
https://economictimes.indiatimes.com/magazines/panache/facebook-says-no-to-fake-news-joins-hands-with-who-to-combat-misinformation-about-coronavirus/articleshow/74477266.cms
--- (2020). Fighting Coronavirus COVID-19 with Data Science & Crowdsourcing: 3 Projects You Should Know About. Exxactcorp: https://blog.exxactcorp.com/fighting-coronavirus-covid-19-with-data-science-crowdsourcing-3-projects-you-should-know-about/.
--- (2020). Infervision in the Frontlines Against the Coronavirus. .itnonline: https://www.itnonline.com/content/infervision-frontlines-against-coronavirus.
--- (2020). Open-Source-COVID-19. Github: https://github.com/WeileiZeng/Open-Source-COVID-19.
 --- (2020). 'The new normal': China's excessive coronavirus public monitoring could be here to stay. The guardian:  https://www.theguardian.com/world/2020/mar/09/the-new-normal-chinas-excessive-coronavirus-public-monitoring-could-be-here-to-stay
--- (2020). The A flood of coronavirus apps are tracking us. Now it’s time to keep track of them. MIT Technology Review:  https://www.technologyreview.com/2020/05/07/1000961/launching-mittr-covid-tracing-tracker/
 
https://ana.press/fa/news/11/473666
 
https://www.tasnimnews.com/fa/news/1398/12/09/2212530
 
پاینده، ع (1399). معجزه فناوری در تایوان. روزنامه دنیای اقتصاد در تاریخ 07/02/1399.
حسینی، ح (1394). مقدمه­ای بر روش تحقیق در علوم انسانی. ماهنامه کار و جامعه، 187، 55-69.
سوری، ع (1394). اصول، مبانی و رویکردهای مدیریت بحران (با تأکید بر بحران­های اجتماعی). فصلنامه مدیریت بحران، 24. 98 – 139.
مک­کارتی، ش (1381). نقش اطلاعات در مدیریت بحران. تهران: انتشارات فرهنگ گفتمان.
نجاتی، ن (1399). طراحی داشبوردهای شهری- کشوری. روزنامه دنیای اقتصاد در تاریخ 07/02/1399.

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History

  • Receive Date: 19 May 2020
  • Revise Date: 11 August 2020
  • Accept Date: 24 August 2020

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