Last month [Duke] announced it would be performing weekly surveillance testing for its students, faculty and staff. The most recent round tallied 14,141 tests, returning eight positives . . .
[UNC] opted against mandatory testing for students before their re-entry, stating that widespread testing went against CDC recommendations and that it could “create a false sense of security” . . . Since the pandemic began, 1,138 students and 72 employees have tested positive. The university has performed a total of 4,612 tests.
These charts lay out the key metrics for understanding the reach and severity of COVID-19 in a given area: number of new daily cases, tests per 100,000 people (testing rate), and percentage of tests that are positive (positivity rate).
As testing capacity increases, considering confirmed new cases, testing rates, and percent positivity together gives us a fuller picture of COVID-19 in a particular state or region. Under these conditions and stable testing practices, trends in daily cases can be cautiously interpreted as trends in transmission of the virus. Leaders can then make informed decisions about lifting social distancing and other transmission control measures.
Most epidemiological models applied to COVID-19 do not consider heterogeneity in infectiousness and impact of superspreaders, despite the broad viral loading distributions amongst COVID-19 positive people (1-1 000 000 per mL). Also, mass group testing is not used [due] to existing shortage of tests. I propose new strategy for early detection of superspreaders with reasonable number of RT-PCR tests, which can dramatically mitigate development COVID-19 pandemic and even turn it endemic.
I used stochastic social-epidemiological SEIAR model, where S-suspected, E-exposed, I-infectious, A-admitted (confirmed COVID-19 positive, who are admitted to hospital or completely isolated), R-recovered. The model was applied to real COVID-19 dynamics in London, Moscow and New York City.
Viral loading data measured by RT-PCR were fitted by broad log-normal distribution, which governed high importance of superspreaders. The proposed full scale model of a metropolis shows that top 10% spreaders (100+ higher viral loading than median infector) transmit 45% of new cases. Rapid isolation of superspreaders leads to 4-8 fold mitigation of pandemic depending on applied quarantine strength and amount of currently infected people. High viral loading allows efficient group matrix pool testing of population focused on detection of the superspreaders requiring remarkably small amount of tests.
The model and new testing strategy may prevent thousand or millions COVID-19 deaths requiring just about 5000 daily RT-PCR test for big 12 million city such as Moscow. Though applied to COVID-19 pandemic the results are universal and can be used for other infectious heterogenous epidemics.
We have developed a highly sensitive RT-LAMP assay compatible with current reagents, that utilizes a colorimetric readout in as little as 30 minutes. In addition to this, we have developed an inexpensive pipeline to further increase sensitivity without requiring highly specialized equipment. A rapid inactivation protocol capable of inactivating virions, as well as endogenous nucleases, was also developed to increase sensitivity and sample stability.
This protocol, combined with our RT-LAMP assay, has a sensitivity of at least 50 viral RNA copies per microliter in a sample. To further increase the sensitivity, a purification protocol compatible with this inactivation method was developed. The inactivation and purification protocol, combined with our RT-LAMP assay, brings the sensitivity to at least 1 viral RNA copy per microliter in a sample.
We hope that this inactivation and purification pipeline, which costs approximately $0.07 per sample and which uses readily available reagents, will increase the availability of SARS-CoV-2 testing, as well as expand the settings in which this testing can be performed.
The urgent need for massively scaled clinical or surveillance testing for SARS-CoV-2 has necessitated a reconsideration of the methods by which respiratory samples are collected, transported, processed and tested.
Conventional testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab, storage of the swab during transport in universal transport medium (UTM), extraction of RNA, and quantitative reverse transcription PCR (RT-qPCR). As testing has scaled across the world, supply chain challenges have emerged across this entire workflow.
Here we sought to evaluate how eliminating the UTM storage and RNA extraction steps would impact the results of molecular testing. Using paired mid-turbinate swabs self-collected by 11 individuals with previously established SARS-CoV-2 positivity, we performed a comparison of conventional (swab → UTM → RNA extraction → RT-qPCR) vs. simplified (direct elution from dry swab → RT-qPCR) protocols.
Our results suggest that dry swabs eluted directly into a simple buffered solution (TE) can support molecular detection of SARS-CoV-2 via endpoint RT-qPCR without substantially compromising sensitivity. Although further confirmation with a larger sample size and variation of other parameters is necessary, these results are encouraging for the possibility of a simplified workflow that could support massively scaled testing for COVID-19 control.
Rapid and accurate SARS-CoV-2 diagnostic testing is essential for controlling the ongoing COVID-19 pandemic. The current gold standard for COVID-19 diagnosis is real-time RT-PCR detection of SARS-CoV-2 from nasopharyngeal swabs. Low sensitivity, exposure risks to healthcare workers, and global shortages of swabs and personal protective equipment, however, necessitate the validation of new diagnostic approaches.
Saliva is a promising candidate for SARS-CoV-2 diagnostics because (1) collection is minimally invasive and can reliably be self-administered and (2) saliva has exhibited comparable sensitivity to nasopharyngeal swabs in detection of other respiratory pathogens, including endemic human coronaviruses, in previous studies.
To validate the use of saliva for SARS-CoV-2 detection, we tested nasopharyngeal and saliva samples from confirmed COVID-19 patients and self-collected samples from healthcare workers on COVID-19 wards. When we compared SARS-CoV-2 detection from patient-matched nasopharyngeal and saliva samples, we found that saliva yielded greater detection sensitivity and consistency throughout the course of infection. Furthermore, we report less variability in self-sample collection of saliva. Taken together, our findings demonstrate that saliva is a viable and more sensitive alternative to nasopharyngeal swabs and could enable at-home self-administered sample collection for accurate large-scale SARS-CoV-2 testing.
IgG antibodies may indicate exposure to SARS-CoV-2 (COVID-19). It usually takes at least 10 days after symptom onset for IgG to reach detectable levels. An IgG positive result may suggest an immune response to a primary infection with SARS-CoV-2, but the relationship between IgG positivity and immunity to SARS-CoV-2 has not yet been firmly established.
Antibody tests have not been shown to definitively diagnose or exclude SARS-CoV-2 infection. Positive results could also be due to past or present infection with non-SARS-CoV-2 coronavirus strains, such as coronavirus HKU1, NL63, OC43, or 229E. Diagnosis of COVID-19 is made by detection of SARS-CoV-2 RNA by molecular testing methods, consistent with a patient’s clinical findings.
0.4 mL (Note: This volume does not allow for repeat testing.)
Gel-barrier tube or serum from red-top tube or serum transfer tube
ROOM TEMP: 3 days
REFRIGERATED: 7 days
FROZEN: 7 days
FREEZE / THAW CYCLES: stable x3
No special preparation required
Causes for rejection
Gross hemolysis; visible microbial contamination; specimen type other than serum
Qualitative detection of IgG antibodies to SARS-CoV-2, the virus that causes COVID-19, to help identify individuals who have been exposed to the virus. Serologic results should not be used as the sole basis to diagnose or exclude recent SARS-CoV-2 infection. This test is recommended in individuals at least 10 days post symptom onset or following exposure to individuals with confirmed COVID-19.
This test has not been reviewed by the FDA.
Negative results do not rule out SARS-CoV-2 infection, particularly in those who have been in contact with the virus. Follow-up testing with a molecular diagnostic should be considered to rule out infection in these individuals.
Results from antibody testing should not be used as the sole basis to diagnose or exclude SARS-CoV-2 infection or to inform infection status.
Positive results may be due to past or present infection with non-SARS-CoV-2 coronavirus strains, such as coronavirus HKU1, NL63, OC43, or 229E.
This test was developed and its performance characteristics determined by LabCorp. It has not been cleared or approved by the Food and Drug Administration.