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Roadmap to the Bioanalytical Testing of COVID-19: From Sample Collection to Disease Surveillance
Author(s) -
Amin Hosseini,
Richa Pandey,
Enas Osman,
Amanda Victorious,
Feng Li,
Tohid F. Didar,
Leyla Soleymani
Publication year - 2020
Publication title -
acs sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.055
H-Index - 57
ISSN - 2379-3694
DOI - 10.1021/acssensors.0c01377
Subject(s) - pandemic , point of care testing , covid-19 , disease , emerging technologies , medicine , contact tracing , health care , infectious disease (medical specialty) , outbreak , disease surveillance , intensive care medicine , risk analysis (engineering) , computer science , virology , pathology , economic growth , artificial intelligence , economics
The disease caused by SARS-CoV-2, coronavirus disease 2019 (COVID-19), has led to a global pandemic with tremendous mortality, morbidity, and economic loss. The current lack of effective vaccines and treatments places tremendous value on widespread screening, early detection, and contact tracing of COVID-19 for controlling its spread and minimizing the resultant health and societal impact. Bioanalytical diagnostic technologies have played a critical role in the mitigation of the COVID-19 pandemic and will continue to be foundational in the prevention of the subsequent waves of this pandemic along with future infectious disease outbreaks. In this Review, we aim at presenting a roadmap to the bioanalytical testing of COVID-19, with a focus on the performance metrics as well as the limitations of various techniques. The state-of-the-art technologies, mostly limited to centralized laboratories, set the clinical metrics against which the emerging technologies are measured. Technologies for point-of-care and do-it-yourself testing are rapidly emerging, which open the route for testing in the community, at home, and at points-of-entry to widely screen and monitor individuals for enabling normal life despite of an infectious disease pandemic. The combination of different classes of diagnostic technologies (centralized and point-of-care and relying on multiple biomarkers) are needed for effective diagnosis, treatment selection, prognosis, patient monitoring, and epidemiological surveillance in the event of major pandemics such as COVID-19.

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