Article ; Online: A Global Digital Citizen Science Policy to Tackle Pandemics Like COVID-19.
Journal of medical Internet research
2020 Volume 22, Issue 5, Page(s) e19357
Abstract: The coronavirus disease (COVID-19) pandemic is an extremely complex existential threat that requires cohesive societal effort to address health system inefficiencies. When our society has faced existential crises in the past, we have banded together by ... ...
| Abstract | The coronavirus disease (COVID-19) pandemic is an extremely complex existential threat that requires cohesive societal effort to address health system inefficiencies. When our society has faced existential crises in the past, we have banded together by using the technology at hand to overcome them. The COVID-19 pandemic is one such threat that requires not only a cohesive effort, but also enormous trust to follow public health guidelines, maintain social distance, and share necessities. However, are democratic societies with civil liberties capable of doing this? Mobile technology has immense potential for addressing pandemics like COVID-19, as it gives us access to big data in terms of volume, velocity, veracity, and variety. These data are particularly relevant to understand and mitigate the spread of pandemics such as COVID-19. In order for such intensive and potentially intrusive data collection measures to succeed, we need a cohesive societal effort with full buy-in from citizens and their representatives. This article outlines an evidence-based global digital citizen science policy that provides the theoretical and methodological foundation for ethically sourcing big data from citizens to tackle pandemics such as COVID-19. |
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| MeSH term(s) | Betacoronavirus ; COVID-19 ; Citizen Science ; Coronavirus Infections ; Humans ; Pandemics ; Pneumonia, Viral ; Public Health ; SARS-CoV-2 |
| Keywords | covid19 |
| Language | English |
| Publishing date | 2020-05-26 |
| Publishing country | Canada |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2028830-X |
| ISSN | 1438-8871 ; 1438-8871 |
| ISSN (online) | 1438-8871 |
| ISSN | 1438-8871 |
| DOI | 10.2196/19357 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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