>> Good afternoon. I’m Commander Ibad Khan, and I’mrepresenting the Clinician Outreach and Communication Activity, COCA, withthe Emergency Risk Communication Branch at the Centers for DiseaseControl and Prevention. I would like to welcome you to today’s COCACall: Molecular Approaches for Clinical and Public Health Applications toDetect Influenza and SARS-CoV-2 Viruses. All participants joining ustoday are in listen-only mode. Next slide please. Free continuing educationis offered for this webinar. Instructions on how to earn continuing educationwill be provided at the end of the call. In compliance with continuing educationrequirements, CDC, our planners, our presenters, and their spouses/partners wish todisclose they have no financial interests or other relationships with themanufacturers of commercial products, suppliers of commercial servicesor commercial supporters. Planners have reviewed contentto ensure there is no bias. The presentations will not include anydiscussion of the unlabeled use of a product or a product under investigational use. CDC did not accept commercial supportfor this continuing education activity.At the conclusion of today’s session, participants will be ableto accomplish the following: Explain the meaning and potential usecases of Ct values for SARS-CoV-2 testing; discuss the value of SARS-CoV-2 sequencing inpublic health compared to clinical practice; and describe clinical test orderingand utilization for seasonal influenza in the context of SARS-CoV-2 co-circulation. After these presentations,there will be a Q&A session. You may submit questions at anytime during today’s presentation. To ask a question using Zoom, click theQ&A button at the bottom of your screen, then type your questions in the Q&A box. Please note we receive many more questionsthan we can answer during our webinars. If you’re a patient, please refer yourquestions to your healthcare provider. If you’re a member of the media, pleasecontact CDC Media Relations at 404-639-3286 or send an email to media@CDC.gov.We have introduced self-knowledgechecks throughout this presentation. We hope you enjoy these opportunities toassess your understanding of today’s session. Please do not type your answersinto the Q&A box, as this may disrupt the Q&Aportion at the end of the session. I would now like to welcome ourpresenters for today’s COCA Call. We are pleased to have with us Dr.Manish Patel, who is the Team Lead for the Influenza Prevention and ControlTeam with CDC’s Influenza Division. Dr. John Barnes who is the Team Lead for theStrain Surveillance and Emerging Variants Team as part of CDC’s COVID-19 response. And Commander Alison Halpin who’s the TaskforceLead for the Laboratory and Testing Task Force as part of CDC’s COVID-19 response.It is now my pleasure toturn it over to Dr. Patel. Dr. Patel, please proceed. >> Thanks, Ibad. Quick mic check. >> Dr. Patel, if you canspeak a little bit louder. That was a little bit on the low end. >> Can you hear me okay? >> Yes, that’s much better. >> Much better. >> Thank you. >> Thanks very much. So I was going to speak today about the2021-2022 influenza season, which is now, and testing issues specificallyrelated to influenza in the context, SARS-CoV-2 co-circulation. And my goal was really to give youall very much a high-level overview of the CDC clinical guidance that’s availableon our websites on issues related to testing for influenza, taking into accountSARS-CoV-2 co-circulation with influenza. And I’ll basically walk you through theseavailable resources and the hyperlinks on these topics on our CDC website. And you should have those linksavailable in the presentation. The recommendations in general arecategorized by three patient settings.One is outpatients and emergency departmentpatients that are likely to be discharged. Second will be hospitalized patients,and third will be nursing home residents. Keep in mind the differenttests and the issues related to the tests themselves will not be covered, thoughthose links are available on the CDC websites. The website gives you all of the moredetails on those different diagnostic tests that are available and thevalidity of those tests. And then lastly, I’ll focus mostly oninfluenza and not SARS-CoV-2 itself today in the presentation, as thoseissues have been covered previously.Next slide. And so you see in this slide thatinfluenza activity really, as you well know, has a history of unpredictability. You know, last year or lastseason, really the past 18 months, we have had no influenza activity in theUnited States, and minimal activity globally in the southern hemisphereor the northern hemisphere. And this really has not happened beforesince we’ve had surveillance for influenza. The jury is still out onreasons why that hasn’t happened. That said, we do know influenza is going tocome back and already has started to reappear in many places in the United States,predominantly in young adults. And recently, CDC has released HANs,Health Alert Notifications, as well as an MMWR to outline the viruses that have beendetected recently in the United States. So I think that suffice it to say,it makes sense for us to be prepared and maintain vigilance for influenza. And so that really is the impetus forthis presentation, is to provide you some of the recommendations on testing for influenza,as well as show you the links available for the implications for increasing influenzaactivity in terms of testing and MPIs.So in terms of monitoring forinfluenza viruses in the United States, we use laboratory surveillance networks. And what that means is we do surveillancefor both influenza and SARS-CoV-2 in the US through various differentapproaches in two broad buckets. We use public health surveillance networksthat are established at the local level within a county, at the state level,and then also at the national level. And then we also have a network of clinicallabs where testing is conducted in outpatient or emergency department or hospitalsettings or nursing home settings.And these clinical test results are submittedto the states and subsequently nationally. And so we use this to monitor forboth influenza and SARS-CoV-2. And so I think using these data,we believe that preparing for — it will allow us to prepare forco-circulation of these two viruses. And I think it’s relevant because ithelps us mitigate the possible impact on healthcare strain this winter should theseviruses continue to co-circulate together. And with regard to influenza, as you all know, vaccination really is our besttool to reduce healthcare burden. We also have adjunctive treatments andprevention strategies with antivirals and nonpharmaceutical interventions. But at the root of that, wereally need a testing plan. Because testing itself can help usidentify these viruses specifically in the setting of co-circulation. So for that reason, guiding clinicians towardsthese testing algorithms is really the primary aim of the presentation today.Next slide. And so could co-infection of influenzaand SARS-CoV-2 occur in the same patient? And what are the implications of that? As I mentioned, we really have had minimalactivity of influenza in the context of SARS-CoV-2 for the past two years. And so we haven’t seen much co-circulationtogether yet, up until recently. And so we’ve had very few cases of co-infectionsof the two viruses in any given patient. However, you know, it is possible to see that, especially when you start seeing both virusesco-circulating together, we will have more cases. Currently because the data are limited,we’re not sure what the implications of co-infection would be orthe risk factors for patients that might get co-infections,or the potential severity. However, this is something we’regoing to continue to monitor through our surveillance networks.Suffice it to say, influenza antivirals canstill be used in a setting for infection. In terms of the differences between clinicalpresentation and some of the epidemiology and transmission of the two viruses, the two viruses are clinicallyquite different, as you well know. The incubation period forinfluenza is much shorter. It’s about one to three days from theonset of infection to clinical symptoms. For COVID, it can be much longer,anywhere from two up to 14 days. The viral shedding or the period of detectionof viral RNA is typically much shorter for influenza than for COVID-19or SARS-CoV-2 infection. And then of course, loss of taste or smell isquite common with COVID-19 and hasn’t been seen that commonly in the past with influenza. Lastly, the timing of onset ofthe severe disease that we see with COVID is much more delayedwith COVID than influenza. COVID typically presents in the second week,eight, nine days after initial infection, whereas influenza tends to present muchsooner, within the first few days of infection. Now, that said, at a patient level,it really is clinically challenging to differentiate the two viruses inpatients with acute respiratory symptoms.And so what that means is that we reallyneed to rely on more laboratory testing to distinguish those two viruses. Next slide. And we have several web pages. In this webpage right here, you see thehyperlink on the bottom of this slide. This basically provides you a summary of allof the adapted guidelines for influenza testing in the context of SARS-CoV-2 co-circulation. On the left box in the red, you see thegeneral proposed algorithms for testing. And basically, the testing strategiesvary by the three clinical settings — outpatients and ED, inpatientsor nursing home residents.And on the right, you have some more information on the various diagnostictests that are available. And there’s lots of them for influenza. I will not comment on those as I mentioned. It’s outside the scope of this presentation. However, the links are very nice andprovide you some more up-to-date information that are available for youto review at your leisure. I will walk you through all four ofthose hyperlinks you see on the left box. Next slide. And then this slide right here basicallygives you the punch line up front on testing. As I mentioned, the general summary ofthese algorithms is that the testing varies by clinical setting, whether the patientsare outpatients or ED patients likely to be discharged home, whetherthey’re hospitalized patients or whether they’re nursing home residents. In outpatients or ED patients,testing options could vary.There’s a lot more flexibility there. Part of this will depend on localtesting availability to those clinicians. So clinicians do have theoption to test for SARS-CoV-2 and then just use their clinical judgment fortesting of influenza, for diagnosing influenza and treating influenza shouldthe patient require it. But if testing is available for influenza, whichis more and more the situation in recent years, it will help with clinicaldifferentiation of the patient, whether it’s SARS-CoV-2 or influenza. And so if testing is available, you could test for influenza. In hospitalized patients and nursinghome residents, the recommendation is to test all suspected patientsfor influenza and for SARS-CoV-2. And the reason is really thereare treatment implications, and possibly other infection controlimplications for these two groups of patients.I think it goes without saying that viralculture and serology are not practically useful for clinical diagnosis of influenza. And you see the reasons outlined here forthose two modalities that were used in the past and are still currently used under researchsettings that are not clinically helpful. Next slide. In here, you can see a couple ofthese algorithms at a very high level.First, you see on the left the outpatientsand emergency department patients. Actually both of these refer to outpatientclinic or emergency department patients. On the left you see patientswho are hospitalized, and on the right you seepatients who are not hospitalized. Again, the general difference is that if thepatient is hospitalized, the recommendation is to test for both SARS-CoV-2 and influenza. And as I mentioned, the reason to test is thatpatients benefit from antiviral treatments and there’s implications for infection control.Next slide. And then the second web link you seeup on the bottom right of this slide, you click on that, you will come to this page. And this algorithm here basicallyhelps you drill down on the patients. I’m sorry, one second. It helps you drill down on the patients by hospitalization status,and an algorithm for testing. On the left box over there, you have thedifferent steps, including specimen collection, that process for SARS-CoV-2and influenza testing and then algorithm for treatmentswith antivirals. On the right slide–side, you havepatients if they’re not hospitalized, an algorithm for SARS-CoV-2 testing andthen influenza testing and treatment.Next slide. And then the basic summary of those–that webpagefor outpatients and ED patients who are likely to be discharged is that forinfluenza, these patients, again, clinicians have flexibility in testing. And testing is only recommendedif it changes clinical management. And this might be in various different forms, such as it might reduce further diagnostictesting, X-rays, antibiotic treatments, and it might also help guideantiviral treatment. If testing is available, it is a nice thing todo, and it does help guide clinical treatment. The assays that could be used herecould be single-plexes or multiplexes. If it is a single-plex assay,then you would probably need to collect two different specimens, onefor SARS-CoV-2 and one for influenza. If rapid influenza molecular assay isnot available in outpatient settings, it is okay to use a rapidantigen assay for influenza. However, keep in mind thesensitivity for those assays are lower. So rapid influenza molecular assays arethe preferred assays if they are available. Next slide.And then similar to the page for outpatientsand ED, this page with the hyperlink on the bottom takes you the testingguidance for hospitalized patients. Next slide. And here’s the general summary of that webpage. There are four specific detailsthe webpage covers. First, among these hospitalized patients,as I mentioned, the recommendation is to test all suspected patients forinfluenza to help guide antiviral treatment, help reduce antibiotic usage and alsohelp with infection control measures.Clinicians here in the hospital settingshould use multiplex or single-plex assays, but they should be molecular assays. Antigen assays, rapid antigen assays arenot as useful to hospitalized patients because the sensitivity is much lower,and largely they have fallen out of favor. For immunocompromised patients, multiplexassay, you know, with a broader panel of respiratory pathogensis typically recommended. Next slide. And then lastly, the fourth webpage –the hyperlink again is on the bottom — takes you to the testingconsiderations for nursing home residents. And each one of these web pages gives youmore details than I’m presenting here. But essentially, the guidance fornursing home residents is quite similar to inpatients, hospital patients. For influenza, same thing asfor hospitalized patients, the preferred assay is a rapid influenza nucleicacid detection assay or molecular assays. And then if they’re not available,rapid antigen assays are allowed, however keep in mind sensitivityis lower for those latter assays. Next slide. And here’s the general details presented — overview of the details presentedon those webpages. First and foremost for nursing home residents,health departments should be notified for both SARS-CoV-2 and influenzainfections in either residents or healthcare personnel workingwithin the nursing homes.And then with regard to testing, as I mentioned, the recommendations are exactly thesame as the hospitalized patients. And basically, if patientsare positive for influenza, they should be treated with antivirals. I will not go through all the details becausethey’re listed out there, and they’re the same as the ones I just coveredfor hospitalized patients. Next slide. So in summary, testing for both influenzaand SARS-CoV-2 is recommended in all patients who have acute respiratory illness inhospital or nursing home set settings, nursing home residents, or outpatients or EDpatients who are likely to be discharged home. As I mentioned, influenza testing canreally depend on the clinical judgment, and it affects clinical management. For example, it could be used toreduce further diagnostic testing or to guide antiviral treatment, or perhapseven reduce unnecessary antibiotic use. The rapid molecular assays, they’rebecoming more widely available, are preferred for influenza because of thelower sensitivity of the antigen assays. And then lastly, keep in mind,we are just seeing an uptick of influenza activity nationally.And this is really some of the first influenceactivity in the context of SARS-CoV-2, co-circulation, and so we’re not surewhat that’s going to look like in terms of healthcare burden or co-infections. And so we will continue to monitor this andreassess and provide updated guidance on testing or treatment, should thatarise as the season progresses. Flexibility does exist to modifyall of this locally as needed, depending on the activity and the burden. And the guidelines itself might also evolveas well as the slightly different data at the state level, dependingon what’s happening locally. Next slide. So that brings us to the knowledge check here. I’m going to read the questionand the answers real quick.What influenza assays are not recommendedfor diagnosis of influenza infection in hospitalized patients withacute respiratory illness? A, viral culture. B, antigen assays. C, serology. D, A and B only. And E, all of the above. I’ll give you a second. Next slide. And the correct answer hereis E, all of the above. Viral culture, as I mentioned, is not practicalor sensitive for detecting influenza viruses. Antigen assays, they have lowersensitivity compared to RT-PCR. And then serology assays require bothacute and convalescent sera four weeks after the initial blood draw, which is notpractical for diagnosing acute infection. Next slide. Here you see a series ofreferences that you could revert to. And then next slide. That brings me to the end of the presentation. Thank you for your attention,and please feel free to reach out to me, should there be any questions.And thank you for all yourefforts during the pandemic. Thanks. >> Thank you very much. Next slide, please. Now I’d like to turn it over to Dr. Barnes. Dr. Barnes, please proceed. >> Hi. Thank you for having me today. Today I’m going to talk about a numberthat has been widely used and talked about in the SARS Coronavirus outbreak andpandemic and some of the considerations that you have to think about when — about reallytalking about cycle threshold numbers and and where we may be inducingerror into our process.Next slide, please. So I put this slide in there to to really kind ofgo through where we are when we’re doing a test, where we may pick up variability andwhere we may actually have implicit bias. And there are certain areas inwhich we have — have potential for both. There’s a lot of steps — we think we’reordering like a test order for PCR or something is relativelysimple, but there’s a lot of steps involved in theactual testing procedure.And some of these things can actually drivebias in the sample sets that we are looking at, that we may utilize Ct values on. And then others may actuallyinduce quite a bit of variability that may not be apparentwhen this testing is is done. And really you can see that throughmany, many, many steps in the pathway. There are individuals that aredifferent in our testing parameters. So whether we’re testing symptomatic peopleor asymptomatic people, vaccinated people, or whatever, these may bias some of our results. Specimen quality — the qualityof specimen, the type of specimen that we take, specimen storage and transport. Reverse — technical things like reverse transcriptionefficiency, platform, and test that we’re using. Assay performance interpretation, all the way through to really do the RT-PCRdynamics in this cycle threshold. Next slide. So Ct values.Ct values are are are a value that we get — if you lookat the bottom panel of this of this graph that we see in the bottom, they’re a value we getthrough a setting of a threshold line, this red line that you see through thatpanel, that is essentially the — where we start to get divergence from the backgroundfluorescence of a particular PCR amplification. And this can absolutely berelated to genome copies.What we’re basically doing is amplifying a smallpiece of that genome, and we are amplifying it up in a very, very specific way thatcan be related to genome copies. And in fact, one of the things that my laboratory does is actuallymanufacture and develop diagnostic tests. And so when we go through a process like this,we actually look at that as, look at our ability to relate to genome copies as one of the reason — one of the factors that we use to tell how well that test is actually working. So if you see the top panel of this syntheticRNA that we have, that we’re utilizing to make this panel, we know wehave a certain amount of that RNA, and a certain amount of totalcopies per reaction.And our Ct values roughly move in a threefoldmanner, which means that we have three — roughly a jump in three Ct per logchange in nucleic acid concentration. And this is something that we want to maintain. The slope of this line should be good and true,even when we get down to a very low, low level. And this is actually indicative of a good test. I will say that this isn’t the –isn’t a requirement, though. And so this should always be kept in mind. But when we’re running it in these ways,we’re doing a lot of controls around this. We’re using the same instrument, the samerun conditions and assay, the same operator, quality, material, analysisand everything like that. And it makes it this this relationshipvery, very standard. And we uh — but what often happens is thereare assumptions made to the Ct data that this test maintains thislinear relationship in all cases.And then the the assay site that we’reusing — utilizing, meaning the pieces of DNA that we’re actually amplifying, there is nomutation in that that may change our ability to efficiently amplify that particular target. Next slide. So one of the things that uh many people donot know when they’re looking at Ct settings and how they may impact — Ct — thresholdsettings and how they may impact Ct value is that the threshold line that I was showingyou back on the on the red line in the previous graph and now in a green line here, canin some tests can actually be set by the person running the test, by the operator. And what you can see as in this curve,this amplification curve that shows as this PCR is being amplified from a signal offrom a detection, that depending on where you set that threshold line, you getvery, very different Ct values. Those Ct values, if you go back to that samerule of roughly three Ct equals a log change in nucleic acid concentration, it basicallygives you a range of 0.2 logs of difference.So if you were talking about 100, you goup to 1,000, to 10,000 copies, at the top, you could only detect at 10,000 copies, oryou could detect at 100 copies at the bottom. And so this this really shows thatthere’s variability just in the way that it can be set on a purelyarbitrary setting. This is not the case for alltests, but it is the case — these are are are considerations when you’reactually looking at utilizing these values. Next slide. And likewise, Ct values on the same amount ofstarting material can vary differently based on the test and based on the assay performance. So the — if we look at — my lab produced aa multiplex test called Flu SC2 Multiplex, and if we look at that target and then welook at a commercial assay that we have, and that has two different targets,you can see what I mean by this. If we utilize a standard amount of materialand drop again through a dilution series, you can see that you get very different valuesbetween the multiplex target that we have testing for the SARS-Coronavirus-2 andthe commercial targets for both N and RdRp.And what is also you can might be able to see inthis is that the distri — the difference between the jumps in those targets are quite different. Whereas we have a roughly three Ct jump between every on themultiplex target, 23 to 27, 23 and a half to 27 as we go on — we have over over six Ctjumps between the commercial end target. And then the RdRp target seemsto almost fall off a cliff. Meaning that what you havethere is nonlinearity in the way that the actual target is progressing througha defined number of copies per reaction. Meaning that it is very, very hard then tocorrelate the amount of Ct to the amount of genome copies actually detected. Next slide. So self-knowledge check. Which of the following factors can changeassay performance and induce variability in Ct values of a molecular test? A, specimen site of collection. B, specimen quality. C, enzyme used in assay. D, lab or technician preferencefor setting threshold line. Or E, all of the above. Next slide. The actual correct answeris E, all of the above. The reason is because all of thesefactors can have a very profound effect on the perceived sensitivityof a molecular assay, and can serve as sources ofvariability in Ct values.Next slide. So, viral mutations within a probe or primerregion can impact Ct value quite a bit. And as we have a situation likewe have with influenza or SARS, where the virus moves end-to-end very quicklyand mutates very quickly, these are not — we tend to try to put — good good assays tend totry to be put in biologically constrained areas. So they don’t actually move very many times,or we don’t pick up mutations very often. But, but they can occur. You can actually get mutations that occur inprimers and probes of these individual assays. And those can affect theefficiency of that assay into actually producing a Ct value or a result. It does not mean that those are less likelyto necessarily be positive or negative on an individual patient,but it can have that effect. And it could actually cause what is calleda delay in the Ct value actually coming up. And if you look at this, this is aparticular mutation that we found in uh between two different probes, both in thenucleocapsid region in the SARS-Coronavirus.So if we look at the nucleo — first probe for thenucleocapsid, N1, there is no mutation. And so, and the Ct values of these two targetsusually run really, really close together, basically right on top of each other. So they should be roughly equivalent. And that when you see the number of mutations thatwe have in the first three samples as being one, basically, we don’t get much discerniblechange between the N1 Ct and the N2 Ct. But when we look at a second mutation thatwould be introduced in the N2 target, induced by the red and the blue arrow, thenwe can actually see that we start to affect the sensitivity of the overall assay. That we are getting that as a lessefficient amplification and detection, and therefore a delay in that Ct. So you can see a battle log worth ofdifference, or three Ct change, again, or a log worth of difference between thenumber of potential genome copies detected by that assay with that mutation. This is just an example, and just a fairlyminor example, but others can happen and have much more detrimental effects.Next slide. So besides working and just looking atthe individual things that can happen with a Ct value and the actual abilityof that Ct value to detect genome copies, we also need to look at the use of Ct valuesto try to actually — try to actually look at infectiousness of a patient and/or transmissibility. Often, because Ct values can be correlatedto the number of genome copies detected in an individual, we try to make this jump inwhich we utilize the number of genome copies of the virus there to estimateviral load, and then therefore, assume infectiousness orassume transmissibility. And this can have a lot of problems. In this particular study, which isdone from Dutch healthcare workers, there were two populations in whichthey were kind of looking through. One was a very much unvaccinated population. And they were testing these peoplebetween January and April of 2020. And this is really when the — when we hadbasically Alpha going through, or the first kind of variant of the Coronavirus.So when we were — excuse me — wehave Wuhan and Alpha going through. So when we had — when the first of these things, we onlyhad this this D614G population, if you will. The vaccinated people reallywere looking at a wave on which we had the Delta Coronavirusgoing, basically a much more infectious — known much more infectious virus. And what they found was even thoughthey have a very, very close correlation between the two values — Ct values on the same on thesepopulations, that those from Delta ended up being uh having a much less replication-competentvirus. And this — so even though these populationswith the Ct value, as you see right here, we didn’t get actually goodviral particles from that. And those viruses were not as infectious, eventhough this virus was — were assumed to be similar through the Ct values of those two populations. Next slide. Likewise, this is a a study that we’ve done byBen Joe in the lab, in which, if we look at and compare RNA copies, which iswhat we detect with a Ct value on that nucleic acid amplification test, anddetermine with a standard curve and infectivity under conditions, we can see that we have the samenumber of RNA copies left at four degrees or room temperature or 37 degrees.Those are very, very similar at daythree, day seven and only start to diverge at the 37-degree mark at day 14 and 21. But infectious virus titer held at infectiousvirus, actual viral particles there — if we hold those at the same — to the same levels withseven, if you look at the blue arrow here, you can see at day three, you getvast divergence of those viruses held at room temperature and at 37degrees than you do the RNA copies. What this basically tells you isthat although you would have a very, very similar Ct at day — at four degreesand 37 degree at day seven, you would have 100,000 fewer infectiousviral particles at 37 degrees. So you cannot necessarily utilize — you cannotutilize Ct to — as a measure of infectiousness. A similar phenomenon was also identifiedby this preprint by Eyre et al., and the impact of SARS-CoV-2 vaccinationon Alpha and Delta transmission. They observed that viral loads determined by Ct were not representativeof viral loads at transmission. Next slide. So Ct’s can be used at estimating genome copies. A standard can be used to actually help youimprove the correlation between Ct and genome copies.NIBSC, which is the National Institute forBiological Standards and Control manufactures such a standard, and these can beused to help standardize assays between two different assays, and to each other. Standard curves for theseshould be run regularly. And these really should berun on a prospective basis. It’s not something that you can now run astandard curve and claim all of your good data in the past, that you know how manygenome copies you necessarily detected. That’s probably not the best practice. It does not eliminate all thecaveats associated with this, though. And these still cannot be linked toinfectiousness or transmiss — transmissibility without something like additional data. An example would be culture. Next slide. So how can Ct values be used? They can be used prospectivelyin a quantitative assay.And there are ways to do that. I use a molecular standard with standard curves,monitoring of reproducibility of how per plate, per instrument, per operator, et cetera. These really should be used in conjunctionwith sequencing so that you actually look at the viral — piece of target of amplificationthat you’re utilizing to make sure that you don’t have systematicchanges in the assay site.And they can also be used as with otherconfirmatory lab data like culture that helps your confidencein the use of Ct values. Or they can be used in groups,as an estimate of viral load. The same assay really shouldbe used for this to compare this, or you should use a comparison standard. And standardization improves of populationsimproves the correlation, sample type, symptom onset, asymptomatic, or symptomatic. And as you can see, I put an arrow hereand really kind of saying that the top end of this slide is really the most thebest use of these this data.And the bottom is really the kind of the not quite as good. But Ct values, again, should never beused as an estimate of infectiousness without additional supporting data. Next slide. So the takeaways, Ct values are nota definitive measure of infectiousness. Ct values can correlate with genome copy. The studies that are designedprospectively to minimize variability, and for instance can be strengthened byapplying a standard and a standard curve, especially at smaller sample sizes. Ct values can be used to comparedata from populations or groups to infer general assumptions on viral load. They can be used — Ct comparisons from the same test or standardizedfor references are preferable in this method. Language used here should be moresuggestive and not definitive. Typical — also, typical diagnostic and clinical reporting of Ct values are very difficultto administer and interpret. One number without a lot of background on how that number was actually derived isreally, really hard to understand.Substantial technical barriers in diagnosticlabs, in the major diagnostic labs, to actually getting thesenumbers out in any, in any real way. Assay kit result capture is positive generally for these labs, there’s generally positive, negative, inconclusive, or invalid. And actually getting Ct valuesis not necessarily easy. And then also these labs a lotof the time use multiple assays which can introduce significant variability, and the values can be generallygreatly overly interpreted. Next slide. Thank you for your attention.>> Thank you very much, Dr. Barnes. Next slide, please. Now, I would like to turnit over to Commander Halpin. Commander Halpin, please proceed. >> Thank you very much. Hello, everyone. Thank you for joining today. Next slide, please. So in the past few years, the pandemic hasreally only further demonstrated the value that sequencing and sequence data arecritical factors driving our ability to track, monitor, and analyze pathogens,including SARS-CoV-2. Based on the system that we’ve setup, you want to target something that is both representative and sensitive. And based on the system that we haveset up across the country, both CDC, investments across the nation, as wellas other academic and institutions who are working really hard to advanceand improve our sequencing capacity, we estimate that there’s a very highprobability — probably as much as 95% — that our national baseline surveillance systemwould be able to detect something circulating at very, very low levels in the population.Something as low as even .05 or .03 percent. Next slide, please. So why do we do genomic surveillancesequencing for public health purposes? Sequencing as a public healthsurveillance tool allows us to do population-level molecular epidemiology. And what does that mean? That means we can detect, track, andanalyze any pathogens circulating in the population at a very granular level. We can watch over time as theproportions of certain variants change. And beyond variants, each of which hasa particular constellation of mutations or genetic changes, we can zoom in onspecific mutations of interest as well. And finally, another strength of thegenomic surveillance system and approach is that it focuses on collecting and sequencingprimary specimens that are SARS-CoV-2 positive that can be selected for culture.And building a comprehensiverepository of cultured viruses serves as a really important resource forthe scientific community at large. And this — these individuals, these laboratories,they’re working really aggressively to characterize these specimens and these viralisolates as quickly as they can with regard to natural immunity, theimpact on natural immunity, vaccines, therapeutics and diagnostics. For example, shortly after Omicron wasreported to the World Health Organization in late November, CDC turnedon enhanced surveillance through its national SARS-CoV-2strain surveillance system. And the enhanced surveillance isreally meant to target strains of interest or variants of interest. In this case, we were targeting a mutationin the Omicron lineage as a screen, which allowed us to prioritizespecimens for sequencing to confirm that if a specimen was indeed Omicron or not. And if it was indeed Omicron, then movingforward towards subsequent isolation. And states rapidly provided usspecimens that fit this description, allowing CDC to start this process.And then once we’re able to start thisprocess, anything that’s isolated can be shared with partners who are working to phenotypicallycharacterize SARS-CoV-2 variants, and it can also be used for phenotypiccharacterization in-house at CDC as well. Next slide, please. I’m sure many of you have seenthe CDC COVID data tracker. And this is actually a relatively oldscreenshot, but I wanted to pick something that wasn’t all Delta all the time.And you can see on the left panel howDelta was really successful at edging out the other variants that werecirculating across the country at the time. You see from week to week the changes thatwere happening with Alpha in the teal, and Gamma in the olive green, shrinkingproportions in the sequence data week over week over week until it became virtuallyall Delta, that burnt orange color. And it’s been that way ever since. However, we are watching closely tosee how these proportions will change with the introductions of Omicron into theUnited States in the coming weeks and months. Next slide, please. Now, genomic sequencing in general isstill not what we would call rapid. Certain approaches, many approachescan require days to weeks to complete from specimen collection, to shipping, allthe way through sequencing and analysis. Therefore, the results arenot available fast enough to direct patient-level therapeutic choices. However, as I mentioned, we can usepublic health’s genomic surveillance to monitor specific changes or mutations inthe sequence data, including those mutations that are indicative of therapeutic resistancefor treatments or preventative purposes.This includes both the monoclonalantibodies and the small amount of molecular antivirals that are available. Our sequencing surveillance system can provideinformation at the regional and perhaps even at the state level to help guideappropriate distribution of therapeutics, based on the prevalence of specificmutations that are associated with resistance to therapeutics used in COVIDprevention and treatment. And we’ve included a few links to additionalinformation on therapeutics themselves and how to order and administer them, ifthat is something you’re interested in. Next slide, please. Okay, so just to make sure you’ve beenfollowing along, our self-knowledge test check is that genomic sequencing shouldbe ordered for persons diagnosed with SARS-CoV-2 infectionfor the following reasons: A, to determine which monoclonalantibody might be appropriate. B, to determine which small moleculeantiviral might be appropriate. C, to inform recommendationsfor the length of isolation.D, to assess the need for high-level care. E, A, B and D. Or F, none of the above. Next slide, please. And the answer, of course,is F, none of the above. Next slide please. And the reason this is F, as I mentioned,the time required between specimen collection and availability of sequence dataobviates the benefit of genomic sequencing for diagnostic purposes or clinicalmanagement at the patient level. We just aren’t there yet inmany cases in terms of speed. Furthermore, the results of genomic sequencingof SARS-CoV-2 are not typically CLIA-validated or authorized by FDA, meaningthey’re not meant to be used for — on human samples in terms of patient management. They’re not meant to diagnose, prevent,or treat disease or assess human health.If you’re interested in more informationabout that, there’s some information at the bottom of the slide footnote. CDC and other public healthlaboratories across the country and globally are performing genomicsequencing for the following purposes. Surveillance, as we’ve discussedat length in this presentation. Investigations, and this includes, forexample, outbreaks or superspreader events. And of course research purposes. Methods for near real-time characterizationof variants are under investigation, and hopefully as the science continues toadvance, we will see improvements in this area. Next slide please. Thank you very much for your time and attention. >> Thank you very much. Presenters, I would like to thank you for providing our audiencewith this timely information. We will now go into our Q&A session. Please remember that in order to ask aquestion using Zoom, click on the Q&A button at the bottom of your screen,then type your question.So our first question asks, are you aware ofeither the existence of or the development of any testing kits that test for bothSARS-CoV-2 and influenza simultaneously? >> Yeah. >> Do you want to take that? >> Sure, sure. Yes, there are several out there. There are actually a couple of rapid testseven that do SARS-Coronavirus-2 and influenza. And there are nucleic acidtests that are available for SARS-Coronavirus, flu, and RSV as well. Like I said in my presentation, we actuallycreated a B-influenza and SARS test. >> Thank you very much. Our next question asks, is there Ct valuedata available for the Omicron variant? And if not, do you have an anticipatedtimeframe having the data available and analyzed similar to the others? >> So that’s a really good question. And there were several in hereabout Ct values and use of those. And this is exactly what we’retrying to discourage a bit. The tests that we have in largepart, and there may be actually a — I haven’t checked in a little while, but theremay be actually a test that is approved for — that is actually approved for actually lookingat the number of genomes or quantitative method.But most of the tests that we actuallyhave out there are not quantitative. They are just for a positive or negative result. And doing that can come witha lot of different a lot of different problems. So I have not seen any data like that yet, butI wanted to make sure that we covered that. >> Thank you very much. Our next question asks, do you anticipatethat genomic sequencing will be used in acute clinical care in the near future,if the methods that you were discussing for near real-time characterization methodsare available and authorized in time? >> This is Alison. That’s a great question. I think there is great promisein the sequencing technology. I think it’s also important to remember thatone of the key components is that there needs to be a defined use for clinical care.You know, knowing the variant that apatient is harboring or infected with may or may not impact their, you know, infection prevention decisionsbeing made with regard to that. And some of the mutations mayimpact treatment in the future. But I think part of it is recognizing that it’sreally important that we are very confident in the performance of the testbefore it’s used for patient care. >> Thank you very much. Our next question is specificto a patient population. I know, Dr. Patel, you talkedabout outpatient clinics, emergency departments, hospitalsand nursing homes. The question asks, do you have recommendationssimilarly for incarcerated populations? Would you consider them similarto nursing homes or would you have different or variedrecommendations for incarcerated populations? >> That’s an excellent question.So recently, CDC issued a HAN, whichI’m sure we can add as a link if it’s not already accessible to participants. And in the past, there are 2018 CID guidelinesthat are posted in the reference list, which consider long-term care facilitiesand nursing homes as institutions. Prisons — there’s no specific guidance onprisons or other congregate settings. However, in the context of SARS-CoV-2,I think there’s a lot of flexibility for considering those institutions — those congregantsettings as institutions. So I think the HAN does layout thatflexibility for purposes of testing, purposes of treatment with antivirals andpossibly prophylaxis with the two antivirals that are currently available, oseltamivir and baloxavir. So that’s addressed in the HANreleased by CDC on December — November 14th. Thank you. >> Thank you, Dr. Patel. And for our audience who are interested inlooking at the HAN, you can direct your browsers to emergency.CDC.gov/HAN, and you’ll be ableto find the HAN in question in the archives. Okay, we have time for one last question. And our question states, in lightof co-circulation with SARS-CoV-2, does CDC have different or updatedantiviral recommendations for influenza? Or do those recommend — recommendationsstay unchanged? >> I’ll take that question also.It’s very similar to the previous question. And the HAN itself does address those. I think there is more flexibilitythat is necessary. And CDC recognizes that. There are no specific guidelinesor recommendations that are made specificallyto co-circulation SARS-CoV-2. So two things. One, in the setting of co-infections,antivirals for influenza can be used if there’s no contraindications orlimitations or restrictions for use. The use of antivirals baloxavir or oseltamivir could certainly help mitigate localized outbreaks with treatment and/or prophylaxis. And that can help reducehealthcare strain in the context of co-circulation of two viruses this winter. So there is a lot of flexibility, and the HANcovers those issues, but no specific guidelines or recommendations that are changingfor influenza and antiviral use. >> Thank you very much. This concludes today’s presentation. I want to take a moment to thank the presentersfor sharing their time and expertise with us. All continuing education for COCA Callsare issued online through the CDC training and continuing education onlinesystem at https://TCEOLS.cdc.gov.Those who participate in today’s live COCACall and wish to receive continuing education, please complete the onlineevaluation by January 10, 2022 with the course code WC2922-120921The access code is COCA 120921. Those who will participate inthe on-demand activity and wish to receive continuing education should completethe online evaluation between January 11, 2022 and January 11, 2024, anduse course code WD2922-120921. Again, the access code is COCA 120921. Continuing education certificates can beprinted immediately upon completing your online evaluation. A cumulative transcript of all CDC’s continuingeducation obtained through the CDC training and continuing education online systemwill be maintained for each user. Today’s COCA Call will be availableto view on demand a few hours after the live COCA Callat emergency.CDC.gov/COCA. Please note that a transcript and closedcaptioned video will be available on demand on COCA Calls’ webpage shortly after that. Continue to visit emergency.CDC.gov/COCA toget more details about upcoming COCA Calls as we intend to host more COCA Calls to keepyou informed of the latest guidance and updates on COVID-19. We invite you to subscribe toreceive announcements for future COCA Calls by visiting emergency.CDC.gov/COCA.You will also receive other COCA productsto help keep you informed about emerging and existing public health topics. Keep up with new research and scientificstudies about COVID-19 by signing up to receive CDC’s weeklyCOVID-19 Science Update email by visiting the webpage on this slide. We also invite you to stay connected withCOCA by liking and following us on Facebook at Facebook.com/CDCClinicianOutreachandCommunicationActivity. Again, thank you for joining us fortoday’s COCA Call, and have a great day..
Free Coupon for Discounts on Pharmacy Medications
