Quantitative reverse transcription polymerase chain reaction results as a non-biased powerful epidemiological indicator

Description

Quantitative reverse transcription polymerase chain reaction results as a non-biased powerful epidemiological indicator of the pandemic curve in Belgium Background: Infection with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) induces the coronavirus infectious disease 19 (COVID-19). The pandemic form of the COVID-19 is related to its basic reproductive number, which is strongly influenced by mitigation measures (mainly effective physical distancing, quarantine and contact tracing). One of the measure consists in test (by quantitative reverse transcription polymerase chain reaction, qrtPCR) and quarantine infected human to disrupt the chain of transmission of the SARS-CoV-2. Method and principal expected results: To investigate if results of qrtPCR should be useful as epidemiological indicator of the pandemic curve in Belgium, we wish to investigate massive qrtPCR results respecting anonymity (more than 110,000 tests were performed at the University of Liège on elderly home occupants in first instance and on persons from sorting centers). Statistical analyses could permit to validate the use of both prevalence results and distribution of cycle threshold (Ct value) in PCR as an epidemiological indicator of the spatio-temporal trend of the pandemic picture in Belgium. Expected conclusion and significance: Based on the proposal study, we expect that the trend analysis of PCR results at local/regional/national level should be very useful to monitor the COVID-19 pandemic based on evidence. This indicator should be easy to use by the way of the laboratory information management system (LIMS). The same methodology should be used in all countries affected and possibility aggregated in order to have a more robust global picture of the pandemic at continent/world level and to follow the efficacy of the mitigation measures against the COVID-19 by space-time unit.

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  • hdbp0241
  • 5a92241d-ec18-5ec1-98c0-7683a9c8a0d7

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  • HEAL

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