Version 1
: Received: 18 May 2020 / Approved: 20 May 2020 / Online: 20 May 2020 (04:10:24 CEST)
How to cite:
Bergant, M.; de Marco, A. Diagnostics and Monitoring of COVID-19 Infection – Current Understanding. Preprints2020, 2020050316. https://doi.org/10.20944/preprints202005.0316.v1
Bergant, M.; de Marco, A. Diagnostics and Monitoring of COVID-19 Infection – Current Understanding. Preprints 2020, 2020050316. https://doi.org/10.20944/preprints202005.0316.v1
Bergant, M.; de Marco, A. Diagnostics and Monitoring of COVID-19 Infection – Current Understanding. Preprints2020, 2020050316. https://doi.org/10.20944/preprints202005.0316.v1
APA Style
Bergant, M., & de Marco, A. (2020). Diagnostics and Monitoring of COVID-19 Infection – Current Understanding. Preprints. https://doi.org/10.20944/preprints202005.0316.v1
Chicago/Turabian Style
Bergant, M. and Ario de Marco. 2020 "Diagnostics and Monitoring of COVID-19 Infection – Current Understanding" Preprints. https://doi.org/10.20944/preprints202005.0316.v1
Abstract
The progression of the recent COVID-19 pandemic surprised political authorities as well as scientists. The possibility to design powerful strategies for health care and preserving economic and social activities strongly relies on the capacity to monitor correctly the virus spreading and the immune response in the symptomatic and asymptomatic population. The available data relative to the first pandemic months indicate that the test reliability was progressively improved but also that the extremely variable methodologies used in the diagnostic studies generated data that are often not comparable. This condition prevents a simple metadata analysis for the identification of reliable diagnostics guidelines. Nevertheless, there are converging evidences that combinations of complementary approaches may enable more precise identification of virus infection. Furthermore, it appears that the similarities between SARS-CoV2 and the related types SARS-CoV1 and MERS that caused outbreaks in the last 20 years can be exploited to infer some information for which no direct evidence is still available
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
