Blockchain and Artificial Intelligence Technology for Novel Coronavirus Disease 2019 Self-Testing
1
Department of Public Health, University of Limpopo, Polokwane, Limpopo Province 0727, South Africa
2
Genesis Technology and Management Group, (GenesisTMG, LLC), Bethesda, MD 20817, USA
*
Author to whom correspondence should be addressed.
Diagnostics 2020, 10(4), 198; https://doi.org/10.3390/diagnostics10040198
Received: 26 March 2020
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Revised: 30 March 2020
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Accepted: 31 March 2020
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Published: 1 April 2020
(This article belongs to the Special Issue Implementation and Scale Up of Point of Care (POC) Diagnostics in Resource-Limited Settings)
The novel coronavirus disease 2019 (COVID-19) is rapidly spreading with a rising death toll and transmission rate reported in high income countries rather than in low income countries. The overburdened healthcare systems and poor disease surveillance systems in resource-limited settings may struggle to cope with this COVID-19 outbreak and this calls for a tailored strategic response for these settings. Here, we recommend a low cost blockchain and artificial intelligence-coupled self-testing and tracking systems for COVID-19 and other emerging infectious diseases. Prompt deployment and appropriate implementation of the proposed system have the potential to curb the transmissions of COVID-19 and the related mortalities, particularly in settings with poor access to laboratory infrastructure.
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MDPI and ACS Style
Mashamba-Thompson, T.P.; Crayton, E.D. Blockchain and Artificial Intelligence Technology for Novel Coronavirus Disease 2019 Self-Testing. Diagnostics 2020, 10, 198. https://doi.org/10.3390/diagnostics10040198
AMA Style
Mashamba-Thompson TP, Crayton ED. Blockchain and Artificial Intelligence Technology for Novel Coronavirus Disease 2019 Self-Testing. Diagnostics. 2020; 10(4):198. https://doi.org/10.3390/diagnostics10040198
Chicago/Turabian StyleMashamba-Thompson, Tivani P., and Ellen D. Crayton. 2020. "Blockchain and Artificial Intelligence Technology for Novel Coronavirus Disease 2019 Self-Testing" Diagnostics 10, no. 4: 198. https://doi.org/10.3390/diagnostics10040198
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