Research Updates on COVID-19: Vaccine Advancements, Chloroquine, Testing Updates & More

Weekly COVID-19 Research Update
May 20, 2020

During the COVID-19 pandemic, it is vital to make objective and informed decisions that affect your family and loved ones. As part of Princeton Longevity Center’s strategic partnership with PinnacleCare, we are excited to bring you their Pandemic Response Research updates as a complimentary resource through the remainder of this crisis. These updates will bring you factual, objective, scientific information to help make safe decisions for you, your family and your community. Updates, while scientifically based, are easy to understand and will include both resources and references for a more clinical insight.

Treatments & Trials

Favorable Results Reported in Preliminary Vaccine Trial

Moderna, the manufacturer of one of the potential vaccines for COVID-19, announced that they observed an immune response after two injections of the vaccine in eight people in the clinical trial to test the safety and efficacy of the vaccine (Grady, 2020). The vaccine was also found to have a good safety profile in the healthy volunteers enrolled in the first phase of the trial. The blood from the eight participants has been tested, and the antibodies produced in response to the vaccine prevented the replication of the virus in cell culture experiments, suggesting they are active, neutralizing antibodies. The level of antibodies that were produced in response to the vaccine were found to be similar to levels observed in people who had recovered from COVID-19. The FDA has approved the next phase of the trial with 600 volunteers, and spokespeople from Moderna said it is expected to begin soon. They have also stated that the third phase, involving thousands of healthy participants, is expected to begin in July if the second phase goes as planned. The vaccine being tested in this trial is an RNA vaccine, which is the same type of vaccine described in more detail in last week’s update. To date, no vaccines using this technique have been approved for use against any disease.

Clinical Trials of Potential COVID-19 Treatments

As of May 4, there were more than 1,000 trials addressing aspects of COVID-19 (Bauchner and Fontanarosa, 2020). Many of the early trials may not lead to unequivocal evidence of efficacy of the treatments, however. Early in the outbreak, a sense of urgency led to trials without a control group (a group of participants who do not receive the treatment). When there is no control group, it is difficult to determine the magnitude of any effect that is observed. This may be especially important with COVID-19 because there is limited understanding of individual characteristics that lead to manifestation of severe symptoms, a large variety in the regions of the body affected by the infection, and a group of people spontaneously and quickly recover from severe illness without a disease-based treatment. This last characteristic of COVID-19 could give the impression that a potential treatment is working if there is no control group for comparison. Small trials, which most currently are, do not have enough participants to allow for an assessment of the effect of a treatment on a subgroup of participants. For example, a treatment may be effective for treating the inflammatory response associated with COVID-19, but if too few people in the trial experienced this symptom, it may not be apparent. Limited numbers of participants also leads to difficulty in determining the effect on mortality from the treatment. In a clinical trial, it is easier to determine the statistical significance of outcomes such as the time to resolution of symptoms, improvements in laboratory and radiographic testing, or reduction in the use of mechanical ventilation. A larger number of participants is needed to determine if the treatment is able to prevent people from dying, and it may take longer to measure this outcome compared to, for example, the time for a participant to be removed from ventilation.

An example of these complications was apparent with the recently released studies of remdesivir (Herper, 2020). One of the trials organized by the NIH included a control group and a group that received remdesivir for 15 days. At the end of the 15 days, participants were assessed using a scale from zero to eight, where zero corresponded to death and eight was defined as not hospitalized and no restrictions on activities. Results from studies in China suggested that remdesivir may require longer than 15 days to elicit an effect on COVID-19. To avoid a negative result even with a potentially effective treatment, the endpoint of the trial was changed to how long it took for participants to recover. When the results were analyzed, the researchers found that participants using remdesivir had a 31% faster time to recovery with the drug. However, there was no statistically significant difference in the mortality rate between the two groups (8% for those receiving the drug and 11.6% for those who did not). Based on the data, the study was found to be successful, showing a small, but beneficial effect in participants taking remdesivir. At the time of the first analysis, some of the participants enrolled in the trial were still being treated, and the outcome of their treatment would be included in the final results. Because the preliminary results were positive, the organizers decided that participants still being treated who were in the control group should be offered the use of remdesivir if they chose.

However, this would mean their data could not be used in the final analysis. Because of the small size of the study, it was expected that the additional information from these participants would better define the mortality rate and lead to more definitive answers on whether the drug reduces the chance of dying from COVID-19. There has been a large debate how the trial should have been completed. With a normal drug trial, the results would not have world-wide consequences, but based on the positive outcome of remdesivir, it will be used as the baseline drug for comparisons of future clinical trials, and the evidence for its use is not as strong as most would prefer. Janet Wittes, a statistician and the president of Statistics Collaborative, commented to STAT News that “we don’t know if it’s strong enough for it to be the standard of care. I don’t think we know who should be treated [with remdesivir].” Steven Joffe, an ethics expert at the University of Pennsylvania, remarked that he feels the NIH researchers responded correctly to the results of the trial by giving remdesivir to those in the control group, but he also felt that the trial should not have been changed to measure the time to recovery rather than more “clinically important endpoints” such as mortality. A trial from China released around the same time reported no beneficial effect of remdesivir, and the Chinese trial was ended early because of an inability to enroll a sufficient number of participants. Another large study by Gilead, the company that manufactures the drug, does not include a control group, making determination of a change in mortality impossible.

Further complicating the search for a COVID-19 treatment is a concern about the magnitude of the effect from treatments deemed “successful” in a clinical trial. In a normal trial, a beneficial response in 5% to 10% of patients is considered a useful treatment, but at this level of efficacy, most patients with COVID-19 would not benefit (Bauchner and Fontanarosa, 2020). In order to make a difference in the outcome of the COVID-19 pandemic, a treatment will need to lead to a cure rather than simply reduce the duration of intubation or length of a hospital stay.

Another factor involved is determining the correct time to use a drug. At the start of the epidemic, potential antiviral drugs against COVID-19 were mainly used in severely ill people. However, there is evidence from other viruses that it is necessary to start antiviral medications before the start of severe symptoms. For example, the influenza drug oseltamivir needs to be started within 48 hours of the onset of symptoms to provide a measureable benefit over placebo (Lipsitch et al., 2020). SARS-CoV-2 infections have a high level of viral production early in the disease, suggesting that early treatment is required to get a meaningful reduction in the replication of the virus. It has been observed that there is a window of about five days between symptom onset and the need for hospitalization with COVID-19. Researchers are investigating if treatment with antivirals during this window could prevent the progression to severe symptoms. Use of antivirals after this window may not be expected to have a large effect, because at this point the symptoms observed have mainly been attributed to an overly robust immune response rather than high levels of viral replication.

Combination Treatments with Lopinavir, Ritonavir, and Ribavirin with or without Interferon Beta-1b

A combination of the antiviral medications lopinavir, ritonavir, and ribavirin successfully treated people with SARS in 2003 and led to a reduction in mortality and the need for intensive  respiratory support (Hung et al., 2020). Additional studies indicate interferon beta-1b further reduced the viral replication of SARS and improved lung health in an animal model. Clinical trials of lopinavir with ritonavir showed little effect on COVID-19, but SARS-CoV-2 has been found to have the highest level of viral replication right before or at the time that symptoms appear, which suggests that treatments that reduce viral production are expected to be the most effective when used at the time symptoms begin.

The current clinical trial used an expanded combination of antiviral medications and included 127 participants with COVID-19 in Hong Kong. This corresponds to 80% of the confirmed cases in Hong Kong during the time period. For treatment, 86 were randomly assigned to the combination group, and the rest were assigned to the control group. Patients in the combination group received treatment for 14 days with a combination of lopinavir, ritonavir, and ribavirin with interferon beta-1b on alternate days. The control group received 14 days of treatment with lopinavir and ritonavir. The median time from the start of symptoms to the start of treatment was five days (with a range between four and seven) for the combination group and four days (with a range between three and eight) for the control group. The measured outcome in the trial was the time until participants were negative for SARS-CoV-2 using PCR-based testing. The time until virus was no longer detectable was seven days in the combination group and twelve days in the control group. The group taking the combination therapy also had a resolution of symptoms within four days of the start of treatment, which was a statistically significant difference from the control group (eight days). The combination group also had shorter hospital stays. No patients died in either group, so a determination of a change in mortality rate was not possible. The main side effects of the treatment were diarrhea, fever, and nausea, which resolved without treatment mostly within three days of the start of therapy. There is a possibility that use of interferon beta-1b later in the course of the infection could contribute to the excess inflammatory response observed in some people with COVID-19, and therefore the authors do not suggest using the treatment more than seven days after the initiation of symptoms.

Suppression of Inflammation in Individuals with Severe Symptoms

Another study, conducted in Italy, investigated the outcome of treatment with an anti- inflammatory medication, anakinra, in people who had COVID-19 with moderate-to-severe ARDS and hyper-inflammation (Cavalli et al., 2020). Anakinra blocks the activity of cytokines and is normally used to treat auto-inflammatory diseases. This study compared the outcomes of three groups of participants: 16 patients with COVID-19, ARDS, and hyper-inflammation who were treated with non-invasive ventilation (CPAP) outside of the ICU; seven patients with COVID-19, ARDS, and hyper-inflammation who were treated with CPAP outside of the ICU while receiving anakinra at the level used for treatment of auto-inflammatory diseases (low-dose administered subcutaneously); and 29 patients with COVID-19 and ARDS who were treated with CPAP and standard treatment outside of the ICU as well as high-dose, intravenous anakinra. The participants were evaluated for changes in clinical outcome for 21 days, or until discharge from hospital, ICU admission, or death.

The group receiving low-dose anakinra had no change in the level of inflammation and no reduction in symptoms after seven days of treatment when compared to measurements taken at the beginning of the trial. Participants in the high-dose group were treated for a median of nine days with a range between seven and eleven days. Compared with standard treatment (no anakinra), the use of high-dose anakinra was associated with a higher survival rate at 21 days. Those receiving the high dose of anakinra had a survival rate of 90% compared to a survival rate of 56% in the standard treatment group. There was a quick reduction in the level of inflammatory proteins in those who received a high dose of anakinra and slower improvements in oxygen levels over 14 days in comparison to the levels measured at the start of the trial. In the group receiving standard treatment, there was a persistent increase in inflammatory proteins and little improvement in oxygen levels. The high-dose treatment was discontinued in seven participants due to bacterial infection or increased levels of liver enzymes, which indicates potential liver damage. These same adverse events were also observed in the standard care group, however, and at similar levels. There were three participants that did not improve with the use of high-dose anakinra, and it was later determined that they had developed thromboembolism.


The results from several new studies investigating the use of chloroquine or hydroxychloroquine have been released, and there remains no evidence of a benefit to people with COVID-19. A study published in the New England Journal of Medicine described the outcomes in participants who were either treated with hydroxychloroquine or not at a large medical center in New York City (Geleris et al., 2020). During the timeframe of the study, 1376 people were treated, and 58.9% received hydroxychloroquine. As a group, 25.1% required intubation or died. There was no statistically significant difference in the number of people who required intubation or who died based on the use of hydroxychloroquine.

A larger study that included 88.8% of the individuals with COVID-19 treated in 25 hospitals in the New York metropolitan region also found no evidence of a reduction in mortality from the use of hydroxychloroquine, with or without azithromycin (Rosenberg et al., 2020). The study, published in JAMA, compared the outcome of people treated with hydroxychloroquine and azithromycin, hydroxychloroquine alone, azithromycin alone, or neither drug. The probability of death for patients receiving hydroxychloroquine with azithromycin was 25.7%, hydroxychloroquine alone was 19.9%, azithromycin alone was 10.0%, and with neither drug was 12.7%, which was found to not be statistically significant. However, cardiac arrest was more likely in patients receiving hydroxychloroquine and azithromycin than in those receiving none of the drugs.

COVID-19 in Children

A study out of China indicates that children are as likely as adults to become infected with SARS-CoV-2 (Bi et al., 2020). In the study, the researchers describe the contact tracing of 391 COVID-19 cases and 1286 close contacts. They found that people who had contact with a sick person in their household and those people who had traveled with an infected person were at a higher risk for being infected. Evaluation of household cases showed that the infection rate in children under ten years of age was 7.4% which was similar to the overall infection rate of the general population (6.6%). Based on the information they collected, the authors concluded that “children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission.”

While serious symptoms remain less frequent than in adults, more information has become available on the effect of COVID-19 on children. A report in JAMA describes symptoms in children admitted for COVID-19 at 46 pediatric intensive care units in North America between March 14 and April 3 (Shekerdemian et al., 2020). There were 48 children admitted to the hospitals participating in the study, and their ages ranged from 4.2 years to 16.6 years. Within the group, 83% had substantial pre-existing conditions. After being hospitalized, 38% of the children required mechanical ventilation, 23% had failure of two or more organ systems, and extracorporeal membrane oxygenation was required for one child. At the end of the study, two children had died (corresponding to 2% of the group), 31% were still hospitalized, and three still required mechanical ventilation. The authors conclude that severe illness does occur in children from COVID-19, but at a lower frequency than in adults. At the time of this study, pediatric multisystem inflammatory syndrome had not yet been identified.

The number of cases of the recently identified multisystem inflammatory syndrome in children (also called MIS-C) in the United States and in other countries around the world continues to increase, but at this time, physicians think the condition will remain infrequent (Belluck, 2020). The initial cases were identified in New York, where as of May 13, around 100 children with the syndrome had been identified and three had died. Additional cases have now been reported in Louisiana, Mississippi, and California.

The CDC released a Health Advisory Notice on May 14, which recommends that providers caring for patients younger than 21 years of age meeting MIS-C criteria should report suspected cases to their local, state, or territorial health department (CDC, 2020).

Recommended treatment protocols for the condition have not been released by the CDC, but the American Academy of Pediatrics (AAP) released an update that suggests intravenous immunoglobulin (antibodies) and supportive care for the symptoms of shock (AAP, 2020). Sean

  1. O’Leary, a member of the AAP Committee on Infectious Diseases, stated that supportive care in an intensive care setting is currently the most important factor for treatment. He said, “Pediatric intensive care doctors know how to take care of sick children very well, and they know how to manage the things that are happening with these kids like low blood pressure and in some cases difficulty breathing, (and) in some cases kidney failure. They’re used to managing those types of conditions even though this is a new phenomenon.” The advice to parents from the AAP is to watch for a persistent fever and contact their pediatrician if their child appears ill.

Modeling of the Outbreak

The CDC and researchers from the University of Massachusetts Amherst released a composite model of the numerous available models that have been released to predict the course of the COVID-19 outbreak (Aizenman and McMinn, 2020). Based on the analysis, the group predicts that the death toll from the virus will increase from 82,000 on May 12 to 110,000 by June 6, an increase of 28,000 deaths which corresponds to 34% of the number of people who have died thus far in the entire outbreak dying in an approximately four week time span. All of the twelve models predict a dramatic increase in the number of deaths between now and the first weeks of June. The number of deaths is not expected to be uniform across the country, and states currently dealing with increased numbers of deaths are expected to continue this trend, and a large increase is not expected to emerge in areas where the number of deaths is still small (CDC, 2020). Graphs with the national forecast and state forecasts can be found at

Excess Deaths in the United Kingdom due to COVID-19

Researchers in the United Kingdom have estimated the number of excess COVID-19-related deaths compared to the usual mortality in certain groups (Banerjee et al., 2020). The calculations were performed at differing infection rates based on interventions for reducing transmission, including full suppression (0.001%), partial suppression (1%), mitigation (10%), and no intervention (80%). The medical records of 3,862,012 people in the United Kingdom were included in the study, and it was determined that 20% of the study population are in the high-risk category for COVID-19. Specifically, 13.7% were older than 70, and 6.3% were younger than 70 with at least one underlying medical condition. The one-year mortality rate of this group under normal circumstances is expected to be 4.46%. They also determined the expected number of deaths in the high-risk populations in several different countries before the COVID-19 outbreak. In the United Kingdom, the population is 66.4 million, and there are 5.77 million people who are over 70 and 2.66 million who have at least one health condition that puts them at high-risk of COVID-19. Based on this information, the typical number of deaths in these two groups in a year would be expected to be 376,001. In a full suppression scenario in the UK population, between two and seven excess deaths were expected due to COIVID-19 with full suppression. With mitigation, between 18,374 and 73,498 excess deaths were expected, and if no interventions were put in place, the researchers determined that the number of excess deaths would be between 146,996 and 587,982 for those in the high-risk category for COVID-19. For comparison, the United States has a population of 329.1 million with 28.6 million over the age of 70 and 13.2 million with at least one health condition that puts them at high-risk of COVID-19. The typical number of deaths in a year for this population in the United States is 1,862,459.

Required Hospital Capacity in the United States based on Information from China

A report in JAMA used information on the peak number of hospitalized patients in two cities in China to predict the capacity required in United States (Li et al., 2020). In Wuhan, strict measures were implemented within six weeks of confirmed community transmission to reduce the spread of COVID-19. In the time between the start of community transmission and the initiation of containment procedures, the virus had spread considerably. Between January 10 and February 29, the median number of COVID-19 patients in the ICU each day was 429, ranging between 25 and 1143 people, with a median of 1521 patients in the hospital with serious illness each day, which ranged between 111 and 7202 people.

However, in the city of Guangzhou, which has a comparable population to Wuhan, containment measures were implemented one week after the confirmation of community transmission, and the number of people in the hospital was much lower. Between January 24 and February 29, there were a median of nine COVID-19 patients each day in the ICU with a range between seven and twelve, and a median of 17 people in the hospital with serious illness each day, ranging between 15 and 26 people. During the peak of the epidemic, 15 patients were in critical condition, and 38 were classified as having serious illness.

Based on demographic data from the United States, the authors estimated the number of hospitalized people if a similar situation were to occur here. The critically ill patients at the peak of a Wuhan-like outbreak in the United States ranged from 2.2 to 3.2 patients per 10,000 adults when the age of the populations was matched and from 2.8 to 4.4 patients per 10,000 adults when the rate of hypertension prevalence was taken into account. In a 2012 report, it was estimated that there were 2.0 to 3.2 ICU beds per 10,000 adults in the United States (Prin and Wunsch, 2012). If all these beds were available, it would be sufficient for the number of COVID- 19 patients. However, a typical metropolitan intensive care unit only has 5% of their beds empty at a time, which suggests that the United States hospital system could not handle an outbreak like the one that occurred in Wuhan (Hick and Biddinger, 2020).

Infection Prevalence in France and Spain

The Johns Hopkins Bloomberg School for Public Health reported in their daily situation briefing that France and Spain recently released information on the extent of their outbreaks based on serological testing (Johns Hopkins Center for Health Security, 2020). Serological testing can result in a high number of false positive results, depending on the accuracy of the test used, and a number of tests recently developed have been shown to be unreliable. However, the information from serological testing can be useful when carefully interpreted. The study in France, published in the journal Science, estimated that 4.4% of the population had previously been infected (Salje et al., 2020). The Spanish study was available from the country’s Ministry of Health and reported similar results to the French study, with 5% of the population previously infected (Ministerio de Sanidad, 2020). The infection rate was also calculated using data from diagnostic testing with PCR-based tests, which is reported as the number of confirmed cases.

Based on this calculation only 0.2% of the population in France and 0.5% of the population in Spain have had COVID-19. The researchers from Johns Hopkins pointed out two important points from these studies: there could potentially be between 10 and 20 undetected infections for every known case and at least 95% of the populations in both countries have not been infected and would still be susceptible.

Testing Updates

There has been a recent increase in the number of new cases of COVID-19 in Wuhan, China, and the government there has announced that they plan to test all of the city’s residents to stop a secondary wave of infection (Schnirring, 2020). This massive plan to test the 11 million people who live in the city was initially given a timeframe of ten days, but an epidemiology team involved in the process said the time frame remains undecided as details are worked out (Fan, 2020). It has been reported that testing supplies may be ample for this level of testing, but the average daily capacity to run the tests using the 53 testing facilities in Wuhan was around 46,000 with an estimated maximum capacity of 63,000.

In the United States, the daily number of new cases for the country has begun to level off, but it is not decreasing, and the number of new cases each day remains high (Joseph, 2020). This suggests that there are still active reservoirs of the virus, which are keeping the number of infections high even with a large number of the country staying home. New cases in previous hot spots such as New York City, Massachusetts, and San Francisco have been falling, but this reduction is being offset by a rising number of new cases in other areas of the country including Texas and Kansas.

There were several novel types of testing that received an FDA, Emergency Use Approval (EUA) for the diagnosis of COVID-19. There are also reports that as the numbers of tests available increases, the number of people coming to get tested has not increased.

Testing Capacity Increased

The Washington Post released results from a survey of governors’ offices and health departments that shows that at least a dozen states have increased their testing capacity to the point where they have more tests than people coming to be tested (Thompson et al., 2020).

However, the number of people being tested is still below the level recommended by public health officials. Officials speculate that people are not getting tested even when they have been exposed to the virus or have symptoms because of a lingering sense of scarcity, a lack of access in rural or underserved communities, concerns about cost, and skepticism about testing operations. The criteria for getting tested has become less stringent in some places, and the CDC changed its recommendations to include testing for people without symptoms who are referred by local health departments or clinicians. In Georgia, the governor suggested that all residents schedule an appointment to get tested even if they have not had symptoms and are simply curious, which is a reversal of previous recommendations. The director of the Harvard Global Health Initiative, Ashish Jha, stated that the goal is to have communities throughout the United States get to a point where everyone who has mild symptoms is tested. This effort is still limited in certain areas by periodic shortages of personal protective equipment and other necessary supplies, such as nasal swabs and the chemicals needed to process the tests. In the District of Columbia, there is enough laboratory capacity to process at least 3,700 tests per day, but the department of health was only able to purchase enough chemicals to process 1,500 tests per day. However, the Washington Post reports that only about 1,000 District of Columbia residents are seeking testing per day, which is below even the diminished capacity of the network of labs. A lack of a coordinated effort is also slowing the rate of testing. Different areas have adopted different strategies that range from allowing everyone to get tested to focusing on certain hot spots of infection. A report from JAMA suggests that even with perfect testing setups the effort will be wasted if there is not also a plan for those who test positive that includes contact tracing and guidance on how to isolate themselves to prevent further transmission (Kaplan and Forman, 2020).

FDA Releases Warning about Accuracy of Abbott Labs Test

The recently touted testing apparatus developed by Abbott Laboratories called Abbott ID NOW that allows for results with a few minutes at the point-of-care rather than in a laboratory setting was the subject of an alert released by the FDA. (FDA, 2020). In the letter from May 14, the FDA states that there have been reports that the test may return false negative results more often than reported in validation testing. Officials from the FDA also stressed that positive tests from the Abbott ID NOW are considered to be valid because the test has not been shown to produce excess false-positive results. Because the device is able to quickly identify positive cases, testing with the device is being allowed to continue. However, negative results should be confirmed with another type of PCR-based testing. Both Abbott and the FDA are collecting information about the reported high rate of false negatives. The FDA released the alert before the investigation has been concluded in order to allow medical professionals to adjust their practices if necessary.

Diagnostic Testing through Detection of Antigens

 An antigen is a foreign substance in the body that produces an immune response. In the case of COVID-19, antigens would be pieces of the virus or whole viruses present during an active infection. Tests can be developed to detect antigens in bodily fluids, such as blood or respiratory fluids. Antigen tests are able to be quickly performed (within a few minutes) with less equipment than PCR-based tests. Antigen tests are most accurate when a positive test is returned, and positive tests are indicative of the presence of SARS-CoV-2. Negative antigen-based tests are less accurate, and negative test results may need to be confirmed with a more time-consuming PCR-based test. The FDA announced on May 9, that they had given an EUA to the first antigen test for COVID-19 produced by Quidel Corporation (FDA, 2020). The test is called Sofia 2 SARS Antigen FIA, and it detects the nucleocapsid (or the outer protein shell) from SARS-CoV- 2 in nasal or throat swabs (FDA, 2020). The test can be used in laboratories certified under the CLIA recommendation that meet the requirements to perform high or moderate complexity tests and at the point of care with the appropriate authorization. Based on the letter of EUA, the test is appropriate for people with an active infection. Positive results indicate the presence of SARS- CoV-2 nucleocapsid protein, but clinical correlation with patient history and other diagnostic information should be used to determine infection status. Negative results should be treated as presumptive and confirmed with a molecular assay (PCR-based test), if necessary for patient management.

CRISPR-Based COVID-19 Tests

A new type of test for the diagnosis of COVID-19 was recently announced which utilizes the CRISPR genome-editing tool (Begley, 2020). In general, CRISPR tests are very sensitive and are able to detect as few as 100 virus particles in a nasal-swab or saliva sample. One test, produced by Sherlock Biosciences, was granted Emergency Use Approval by the FDA on May 7 and can be used in laboratories that are certified through the CLIA process to perform high complexity tests (Guglielmi, 2020 and FDA, 2020). The test, called Sherlock CRISPR SARS- CoV-2 Kit, produces results within about an hour, requires minimal handling of the samples, and does not need the many specialty chemicals that have been in short supply recently for PCR- based tests. Samples for testing can be collected by nasal swabs, nasopharyngeal swabs, oropharyngeal swabs, nasopharyngeal wash/aspirate, nasal aspirate, and bronchoalveolar lavage specimens.

The test was originally developed by researchers at the McGovern Institute at MIT and the Broad Institute, and Sherlock Biosciences reports that they are working with an experienced manufacturer and to produce tens of thousands of tests per week (Satyanarayana, 2020). The company expects to mainly supply the test to hospitals where they will be able to add to the validation data with real-world results.

The researchers at MIT and Sherlock Biosciences are also working on another CRISPR test called the INSPECTR platform, which is an instrument-free, handheld test that is similar to an at-home pregnancy test (Begley, 2020 and Sherlock, 2020). The scientists named the test STOPCovid, and they are continuing to validate the accuracy of the test by running hundreds of samples that are known to be positive or negative. The currently available validation testing of STOPCovid shows a specificity of 100% (no false-positives) and 97% sensitivity (gave a false- negative result for 3% of samples). For comparison, the PCR-based test is reported to have around a 30% rate of false negatives. As the number of validation tests increases, the overall sensitivity rate for STOPCovid may change, which is why numerous tests are required.

Other labs have reported development of CRISPR-based COVID-19 tests. One of the tests from the University of California and Mammoth Biosciences takes about 40 minutes to receive a result, but early reports suggested that the tests were not as accurate as PCR-based tests and produced false negatives slightly more often than the PCR test (Begley, 2020). Mammoth Biosciences is reportedly in the midst of applying for Emergency Use Approval from the FDA (Satyanarayana, 2020). A third company, Caspr Biotech, has also released information on a CRISPR-based test in a pre-print on BioRxiv.

Testing using Saliva Samples

To this point, samples for testing were collected using nasopharyngeal swabbing techniques where a long swab was used to collect viral particles from deeper in the respiratory system. On May 7, the FDA issued an EUA for the Rutgers Clinical Genomics Laboratory TaqPath SARS- CoV-2 Assay from Rutgers University that allows PCR-based testing on self-collected saliva samples using the Spectrum Solutions LLC SDNA-1000 Saliva Collection Device (FDA, 2020). Validation of this method was necessary because some tests are not sensitive enough to detect the presence of virus in saliva. There is a higher amount of virus found in lower in the respiratory system, making it more likely that virus particles will be detected. Approval indicates that the test used by the Rutgers lab can detect the smaller number of particles in saliva.

Test to Detect Neutralizing Antibodies

Vyriad and Regeneron announced a new serological test that can determine if antibodies produced against SARS-CoV-2 after an infection are protective from subsequent infection (Vyriad, 2020). Antibodies that can prevent future infections, or immunity, are referred to as neutralizing. It is possible to produce antibodies during an infection that will not prevent future infections, and in order to determine if antibodies are neutralizing, tests are typically performed using live virus in a biocontainment laboratory. However, Vyriad and Regeneron have announced a new test that can identify people who produce neutralizing antibodies that does not require the use of live virus, which would allow it to be more widely used in normal laboratory conditions. In their announcement on May 12, they report that the test is expected to be available through major CLIA-certified testing labs by the end of May.

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