>> – good evening. I’m Commander Ibad Khan, and I’mrepresenting the Clinician Outreach and Communication Activity, COCA, withthe Emergency Risk Communication Branch at the Centre for DiseaseControl and Prevention. I would like to welcome you to today’s COCACall: Molecular Approachings for Clinical and Public Health Employment toDetect Influenza and SARS-CoV-2 Viruses. All players connecting ustoday are in listen-only mode. Next slide delight. Free continuing educationis offered for this webinar. Teachings on how to earn continuing educationwill be provided at the end of the announce. In compliance with continuing educationrequirements, CDC, our planners, our presenters, and their spouses/ spouses wish todisclose they have no financial interests or other relationships with themanufacturers of business produces, suppliers of business servicesor commercial-grade supporters. Planners have reviewed contentto ensure there is no bias. The presentations is not include anydiscussion of the unlabeled use of a product or a commodity under investigational squander. CDC did not accept commercial-grade supportfor this continuing education work. At the conclusion of today’s session, players will be ableto accomplish the following table: Explain the entail and possible usecases of Ct values for SARS-CoV-2 testing; discuss the value of SARS-CoV-2 sequencing inpublic health compared to clinical rehearse; and describe clinical evaluation orderingand utilization for seasonal influenza in the context of SARS-CoV-2 co-circulation.After these lectures, there will be a Q& A period. You may submit questions at anytime during today’s appearance. To ask a question using Zoom, click theQ& A button at the bottom of your screen, then type your questions in the Q& A chest. Please note we receive many more questionsthan we can answer during our webinars. If you’re individual patients, please refer yourquestions to your healthcare provider. If you’re a member of the media, pleasecontact CDC Media Relations at 404 -6 39 -3 286 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-1 9 response. And Commander Alison Halpin who’s the TaskforceLead for the Laboratory and Testing Task Force as part of CDC’s COVID-1 9 response. It is now my pleasure toturn it over to Dr. Patel. Dr. Patel, please followed. >> Thanks, Ibad. Quick mic check. >> Dr. Patel, if you canspeak a little bit louder. That was a little bit on the low-grade goal .>> 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 the2 021 -2 022 influenza season, which is now, and testing issues specificallyrelated to influenza in different contexts, 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 mostly tread you through theseavailable resources and the hyperlinks on these topics on our CDC website. And “youve had” those linksavailable in the presentation. The recommendations in general arecategorized by three patient regulates. One is outpatients and emergency departmentpatients that are likely to be discharged.Second will be hospitalized patients, and third will be nursing home citizens. Keep in subconsciou 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 experiments. And then lastly, I’ll focus largely 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 act 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 Country, and minimum 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 numerous 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 clears impression for us to be prepared and maintain vigilance for influenza. And so that really is the impetus forthis presentation, is required to provide you some of the recommendations on testing for influenza, as well as depict you the links available for the implications for increasing influenzaactivity in terms of testing and MPIs.So in areas of monitoring forinfluenza viruses in the United Government, we use laboratory surveillance structures. And what that symbolizes is we do surveillancefor both influenza and SARS-CoV-2 in the US through numerous differentapproaches in two expansive pails. We use public health surveillance networksthat are established at the local level within a county, at the state statu, and then also at the national level. And then we also have a network of clinicallabs where testing is conducted in outpatient or disaster department or hospitalsettings or nursing home settings. And these clinical measure results are submittedto the states and subsequently nationally.And so we use this to monitor forboth influenza and SARS-CoV-2. And so I meditate utilizing 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 likewise have adjunctive treatments andprevention approaches 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 fit of co-circulation. So for the above reasons, steering clinicians towardsthese testing algorithms is certainly 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 more, up until recently.And so we’ve had very few cases of co-infectionsof the two viruses in any passed patient. Nonetheless, you are familiar with, it is possible to see that, extremely when you start seeing both virusesco-circulating together, we will have more events. Currently because the data are limited, we’re not sure what the implications of co-infection would be orthe risk factors for cases that is likely to come co-infections, or the potential severity. However, this is something we’regoing to continue to monitor through our surveillance systems. Suffice it to say, influenza antivirals canstill be applicable to a fit for infection. In calls of the differences between clinicalpresentation and some of the epidemiology and transfer of the two viruses, the two viruses are clinicallyquite different, as you well know.The incubation interval 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 shed or the period of detectionof viral RNA is typically much shorter for influenza than for COVID-1 9or SARS-CoV-2 illnes. And then of course, loss of taste or smell isquite common with COVID-1 9 and hasn’t been seen that frequently in the past with influenza. Lastly, the timing of onset ofthe severe malady that we discover with COVID is much more delayedwith COVID than influenza.COVID often introduces in the second week, eight, nine eras after initial illnes, 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 represents is that we reallyneed to rely on more laboratory testing to distinguish those two viruses. Next slide. And “were having” various web pages. In this webpage right here, you examine thehyperlink on the bottom of this slide. This basically are provided by a summing-up of allof the accommodated the guiding principles for influenza testing in the context of SARS-CoV-2 co-circulation. On the left box in the red, you verify thegeneral proposed algorithms for testing. And basically, the testing strategiesvary by the three clinical defines — outpatients and ED, inpatientsor nursing home residents.And on the right, “youve had” some more information on the various diagnostictests that have existed. 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 amble you through all four ofthose hyperlinks you learn on the left box. Next slide. And then this slither 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 train, whether the patientsare outpatients or ED cases likely to be exhausted dwelling, whetherthey’re hospitalized patients or whether they’re rest home residents.In outpatients or ED patients, testing alternatives could vary. There’s a lot more flexibility there. Place of this will depend on localtesting availability to those clinicians. So clinicians do have theoption to test for SARS-CoV-2 and then really use their clinical opinion fortesting of influenza, for diagnosing influenza and analyse influenza shouldthe patient requires it. But if testing is available for influenza, whichis more and more the situation in recent years, it will help with clinicaldifferentiation of individual patients, whether it’s SARS-CoV-2 or influenza.And so if testing is available, you could test for influenza. In hospitalized patients and nursinghome tenants, the recommendation is to test all suspected patientsfor influenza and for SARS-CoV-2. And the reason is really thereare treatment inferences, and perhaps other illnes controlimplications for these two groups of patients. I think it goes without saying that viralculture and serology are not practically helpful for clinical diagnosis of influenza. And you envision the above reasons outlined here forthose two modalities that were used in the past and are still currently used under researchsettings that are not clinically supportive. Next slide. In here, you can see a couple ofthese algorithms at a highest level. First, you participate on the left the outpatientsand emergency department patients. Actually both of these refer to outpatientclinic or emergency agency cases. On the left you examine 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 medications and there’s implications for infection mastery. 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, two seconds. 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 collect, that process for SARS-CoV-2and influenza testing and then algorithm for treatmentswith antivirals. On the claim slide–side, you havepatients if they’re not hospitalized, an algorithm for SARS-CoV-2 testing andthen influenza testing and care. Next slide. And then the basic summary of those–that webpagefor outpatients and ED patients who are likely to be removed is that forinfluenza, these patients, again, clinicians have flexibility in testing.And testing is only recommendedif it reforms clinical management. And this might be in various different forms, such as it might abbreviate 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 specimen, onefor SARS-CoV-2 and one for influenza. If rapid influenza molecular assay isnot available in outpatient puts, 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 accessible. Next slide. And then similar to the page for outpatientsand ED, this sheet with the hyperlink on the bottom makes you the testingguidance for hospitalized patients.Next slide. And here’s the general summary of that webpage. There is only four specific detailsthe webpage cover-ups. First, among these hospitalized patients, as I mentioned, the recommendation is to test all believed cases forinfluenza to help guide antiviral therapy, help reduce antibiotic practice 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 mainly they have fallen out of favor. For immunocompromised patients, multiplexassay, you are familiar with, with a broader committee 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 rest home occupants. And each one of these web pages gives youmore details than I’m presenting here. But virtually, the guidance fornursing home residents is quite similar to inpatients, hospital cases. 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 permitted, nonetheless keep in mind sensitivityis lower for those latter assays. Next slide. And here’s the general items acquainted — overview of the details presentedon those webpages. First and foremost for nursing home occupants, health departments should be notified for both SARS-CoV-2 and influenzainfections in either occupants or healthcare personnel workingwithin the nursing homes. And then with regard to testing, as I mentioned, the recommendations are precisely thesame as the hospitalized patients. And mostly, if patientsare positive for influenza, they should be treated with antivirals.I will not go through all the details becausethey’re registered out there, and they’re the same as the ones I time coveredfor hospitalized cases. 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 specifies, nursing home citizens, or outpatients or EDpatients who are likely to be accomplished home. As I mentioned, influenza testing canreally depend on the clinical judgment, and it feigns clinical control. For example, it could be used toreduce further diagnostic testing or to guide antiviral therapy, or perhapseven shorten useless 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 work 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 encumbrance or co-infections. And so we will continue to monitor this andreassess and provision revised steering 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 somewhat different data at the commonwealth degree, dependingon what’s happening locally.Next slide. So that produces 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 simply. And E, all of the above. I’ll give you a second. Next slide. And the remedy react hereis E, all of the above. Viral culture, as I mentioned, is not practicalor sensitive for discover 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 suck, which is notpractical for diagnosing acute illnes. Next slide. Now you accompany a series ofreferences that you could restored to. And then next slide. That draws me to the end of the presentation. Thank you for your attention, and please feel free are to achieve me, should there be any questions. And expressed appreciation for 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, delight followed. >> Hi. Thank you for having me today. Today I’m going to talk about a numberthat has been widely used and has spoken about in the SARS Coronavirus outbreak andpandemic and some of its further consideration that you have to think about when — about reallytalking about cycle threshold numerals and and where we may be inducingerror into our process. Next slide, satisfy. So I framed this slither 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 possibilities 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 test specifies 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 actually 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 beings, injected beings, 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, stage, and research that we’re abusing. Assay performance interpretation, the whole 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 diagram that we see in the bottom, they’re a cost we getthrough a decided 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 perfectly berelated to genome imitates. What we’re basically doing is amplifying a smallpiece of that genome, and we are amplifying it up in a terribly, very specific way thatcan be related to genome forgeries. And in fact, one of the points 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 mimics as one of the reason — one of the factors that we use to tell how well that test is actually succeeding. So if you watch the top body of this syntheticRNA that “were having”, that we’re apply 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 approximately 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 ascent of this order should be good and genuine, even when we get down to a very low, low level. And this is actually indicative of a good research. I will say that this isn’t the –isn’t a requirement, though. And so this should ever be kept in mind. But when we’re running it in these ways, we’re doing a great deal of ensures around this. We’re using the same instrument, the samerun situations and assay, the same operator, quality, material, analysisand everything like that. And it forms it this this relationshipvery, exceedingly standard. And we uh — but what often happens is thereare assumptions made to the Ct data that this test maintains thislinear liaison in all cases. And then the the assay place that we’reusing — utilizing, implying the fragments of DNA that we’re actually amplifying, there is nomutation in that that may change our ability to efficiently enlarge that special target.Next slide. So one of the things that uh numerous parties donot know when they’re looking at Ct settles 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 pink thread in the previous graph and now in a dark-green argument now, canin some experiments are truly be set by the person running the test, by the operator. And what you can see as in this curve, this amplification curve that depicts as this PCR is being amplified from a signal offrom a detection, that depending on where you determined 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 enters of difference.So if you were talking about 100, you goup to 1,000, to 10, 000 transcripts, at the top, you could only detect at 10,000 imitates, oryou could detect at 100 copies at the bottom. And so this this really shows thatthere’s variability exactly in the way that it can be set on a purelyarbitrary adjust. This is not the case for alltests, but it is the case — these are are are circumstances when you’reactually looking at utilizing these values. Next slide. And likewise, Ct values on the same amount ofstarting fabric can go differently based on the test and based on the assay execution. So the — if we look at — my lab rendered aa multiplex measure announced Flu SC2 Multiplex, and if we look at that target and then welook at a business 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 fell again through a dilution line, you can see that you get widely differing 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 prances 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 business death 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 characterized number of copies per action. Meaning that it is very, very hard then tocorrelate the amount of Ct to the amount of genome transcripts 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 assessment? A, specimen site of accumulation. B, specimen quality. C, enzyme used in assay. D, laboratory or technician preferencefor setting threshold line. Or E, all of the above. Next slide. The actual chasten answeris E, all of the above. The rationalization is because all of thesefactors can have a very profound effect on the realized sensitivityof a molecular assay, and can serve as sources ofvariability in Ct values. Next slide. So, viral mutants within a probe or primerregion are affecting 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 leant — good good assays tend totry to be put in biologically confined neighborhoods. So they don’t actually move very many times, or we don’t pick up mutations very often. But, but they can occur. You are truly get mutants 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 reaction. 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 field 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 operated certainly, really close together, basically right on top of each other. So there is a requirement to approximately equivalent. And that when you realise the number of mutants thatwe have in the first three tests as represent 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, generated 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 elaboration and sensing, and therefore a delay in that Ct. So you can see a battle log worth ofdifference, or three Ct change, again, or a enter worth of difference between thenumber of potential genome replicas identified by that assay with that mutation. This is just an example, and simply a fairlyminor lesson, but others can happen and have much more detrimental effects.Next slide. So besides use and just looking atthe individual things that can happen with a Ct value and the actual abilityof that Ct value to spy genome transcripts, we also need to look at the use of Ct valuesto try to actually — try to actually look at infectiousness of individual patients and/ or transmissibility. Often, because Ct values can be correlatedto the number of genome prints 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, premise infectiousness orassume transmissibility. And this can have a lot of troubles. In this particular study, which isdone from Dutch healthcare workers, there were two populations in whichthey were kind of seem through. One was a very much unvaccinated person. And they were testing these peoplebetween January and April of 2020. And “its certainly true it is” when the — when we hadbasically Alpha going through, or the first kind of variant of the Coronavirus. So “when hes” — excuse me — wehave Wuhan and Alpha going through. So when we had — when the first of these things, we onlyhad this this D6 14 G population, if you are able to. The vaccinated people reallywere looking at a movement on which “weve had” the Delta Coronavirusgoing, basically a so much better infectious — known much more infectious virus. And what they found was even thoughthey have a terribly, very close correlation between the two appraises — Ct values on the same on thesepopulations, that those from Delta aimed up being uh having a much less replication-competentvirus. And this — so even though these populationswith the Ct value, as you watch 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 liken RNA replicas, which iswhat we detect with a Ct value on that nucleic acid amplification exam, anddetermine with a standard curve and infectivity under conditions, we can see that we have the samenumber of RNA replicas left at four degrees or area temperature or 37 magnitudes. Those are very, very similar at daythree, period seven and simply start to diverge at the 37 -degree mark at daylight 14 and 21. But virulent virus titer held at infectiousvirus, actual viral molecules there — if we impound those at the same — to the same status withseven, if you look at the blue arrow now, “youre seeing” at daylight three, you getvast dissimilarity of those viruses held at room temperature and at 37 degrees than you do the RNA copies.What this basically tells you isthat although you would have a particularly, very similar Ct at epoch — at four degreesand 37 degree at day seven, you would have 100,000 fewer infectiousviral molecules at 37 positions. So you cannot certainly 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 quantities determined by Ct were not representativeof viral ladens at transmitting. Next slide. So Ct’s can be used at estimating genome reproduces. A standard can be used to actually help youimprove the correlation between Ct and genome follows. NIBSC, which is the National Institute forBiological Standards and Control makings such service standards, and these can beused to help standardize assays between two different assays, and to one another. Standard arches for theseshould be run regularly. And these actually 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 simulates you undoubtedly identified. 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 pattern 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 slab, per instrument, per hustler, et cetera. These actually 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 place. 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 its evaluation 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 linkage, test form, manifestation onslaught, asymptomatic, or symptomatic. And as “youre seeing”, I framed an arrow hereand certainly kind of saying that the top end of this slip is really the most thebest use of these this data. And the bottom is really the various kinds of the not quite as good. But Ct values, again, should never beused as an estimate of infectiousness without added reinforcing data. Next slide. So the takeaways, Ct values are nota exhaustive measure of infectiousness.Ct values can correlate with genome emulate. 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 people or groups to extrapolate general beliefs on viral consignment. They can be used — Ct comparings from the same test or standardizedfor remarks are preferable in this method. Language abused here should be moresuggestive and not exhaustive. Normal — likewise, usual diagnostic and clinical reporting of Ct values are very difficultto administer and interpret. One digit without a lot of background on how that crowd was actually derived isreally, really hard to understand. Substantial technical hindrances in diagnosticlabs, in the major diagnostic laboratories, to actually getting thesenumbers out in any, in any real behavior. Assay kit result capture is positive generally for these laboratories, there’s generally positive, negative, inconclusive, or invalid. And actually get Ct valuesis not necessarily easy. And then likewise these laboratories a lotof the time use multiple assays which can introduce substantial variability, and the values can be generallygreatly extremely understood. Next slide.Thank you for your attention. >> Thank you very much, Dr. Barnes. Next slide, delight. Now, I would like to turnit over to Commander Halpin. Commander Halpin, delight followed. >> Thank you very much. Hello, everyone. Thank you for participating today. Next slide, satisfy. So in the past few years, the pandemic hasreally exclusively further substantiated the price that sequencing and string data arecritical factors driving our ability to track, observer, and analyze pathogens, including SARS-CoV-2. Located 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, speculations across the nation, as wellas other academic and organizations who are working really hard to advanceand improve our sequencing capability, we estimate that there’s a very highprobability — probably as much as 95% — that our national baseline surveillance systemwould be able to detect something spread at exceedingly, very low levels in the population.Something as low-toned as even. 05 or. 03 percentage. Next slide, delight. So why do we do genomic surveillancesequencing for public health determinations? Sequencing as a public healthsurveillance tool allows us to do population-level molecular epidemiology. And what does that planned? That means we can detect, road, andanalyze any pathogens flowing in the population at a extremely granular stage. We can watch over time as theproportions of certain variances vary. And beyond variances, each of which hasa particular constellation of mutants or genetic modifications, we can zoom in onspecific mutants of interest as well.And lastly, 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 structure a comprehensiverepository of cultured viruses performs as a really important resource forthe scientific community at large. And this — these beings, these laboratories, they’re working really aggressively to mark these specimens and these viralisolates as quickly as they can with regard to natural immunity, theimpact on natural exemption, vaccines, therapeutics and diagnostics.For example, shortly after Omicron wasreported to the World Health Organization in late November, CDC turnedon ameliorated surveillance through its national SARS-CoV-2strain surveillance system. And the enhanced surveillance isreally meant to target sprains in the best interests or discrepancies 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 countries rapidly catered usspecimens that fit this description, granting CDC to start this process.And then once we’re able to start thisprocess, anything that’s isolated can be shared with spouses 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 slink out the other variances 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 cycle data week over week over week until it became virtuallyall Delta, that burnt orange color.And it’s been that route ever since. Nonetheless, we are watching closely tosee how these proportions will change with the introductions of Omicron into theUnited Commonwealth in the next few weeks and months. Next slide, please. Now, genomic sequencing in general isstill not what we would call rapid. Certain approaches, numerous approachescan require eras to weeks to complete from specimen collecting, to shipping, allthe method through sequencing and analysis.Therefore, the results arenot available fast enough to direct patient-level therapeutic options. However, as I mentioned, we can usepublic health’s genomic surveillance to monitor specific varies or mutants inthe cycle data, including those mutations that are indicative of therapeutic resistancefor managements or preventative intents. This includes both the monoclonalantibodies and the small amount of molecular antivirals that have existed. Our sequencing surveillance system can provideinformation at the regional and perhaps even at the government degree 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 prescribe and administer them, ifthat is something you’re interested in. Next slide, please. Okay, so merely to make sure you’ve beenfollowing along, our self-knowledge test check is that genomic sequencing shouldbe ordered for people diagnosed with SARS-CoV-2 infectionfor the following reasons: A, to determine which monoclonalantibody might be appropriate.B, to determine which big 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, satisfy. And the answer, of course, is F , nothing of the above. Next slide satisfy. And the reason this is F, as I mentioned, the amount of time required between specimen accumulation and availability of cycle dataobviates the best interests of the genomic sequencing for diagnostic intents or clinicalmanagement at the patient level. We precisely aren’t there more inmany cases in terms of speed. Furthermore, the results of genomic sequencingof SARS-CoV-2 are not generally CLI-Avalidated or authorized by FDA, meaningthey’re not meant to be used for — on human tests in terms of patient management. They’re not meant to diagnose, thwart, or treat illnes or assess human health. If you’re interested in more informationabout that, there’s some information at the bottom of the move note. CDC and other public healthlaboratories across the country and globally are playing genomicsequencing for the following purposes. Surveillance, as we’ve discussedat length in this presentation.Investigations, and this includes, forexample, outbreaks or superspreader contests. 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 delight. Thank you very much for your time and attention. >> Thank you very much. Presenters, I would like to thank you for catering 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 nature your question. So our first issue requests, are you aware ofeither the existence of or the development of any testing kits that measure 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 appearance, we actuallycreated a B-influenza and SARS test. >> Thank you very much. Our next question questions, 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 is indeed various in hereabout Ct values and use of those. And this is exactly what we’retrying to discourage a bit. The evaluations that we have in largepart, and there may be actually a — I haven’t checked in a bit 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 enveloped that. >> Thank you very much. Our next question questions, 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 engineering. I think it’s also important to remember thatone of the key components is that there needs to be a defined use for clinical caution. You know, knowing the variant that apatient is harboring or newly infected may or may not impact their, you know, illnes prevention decisionsbeing made with regard to that.And some of the mutants mayimpact management in the future. But I recall 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, disaster bureaux, hospitalsand nursing homes. The question queries, do “youve had” recommendationssimilarly for incarcerated people? Would you be taken into account similarto nursing homes or would you have different or variedrecommendations for incarcerated populations? >> That’s an excellent question. So recently, CDC published a HAN, whichI’m sure we can add as a join 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. Confinements — there’s no specific guidance onprisons or other congregate prepares. Nonetheless, in the context of SARS-CoV-2, I think there’s a lot of flexible for considering those institutions — those congregantsettings as institutions. So I suppose the HAN does layout thatflexibility for purposes of testing, purposes of treatment with antivirals andpossibly prophylaxis with the two antivirals which is presently, oseltamivir and baloxavir. So that’s addressed in the HANreleased by CDC on December — November 14 th. Thank you. >> Thank you, Dr.Patel. And for our gathering 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 go that question too. 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 locate of co-infections, antivirals for influenza can be used if there’s no contraindications orlimitations or regulations for use. The help of antivirals baloxavir or oseltamivir could certainly help mitigate localise outbreaks with care and/ or prophylaxis.And that can help reducehealthcare strain in the context of co-circulation of two viruses this winter. So “theres a lot” of flexible, and the HANcovers those issues, but no specific guidelines or recommendations that are changingfor influenza and antiviral call. >> Thank you very much. This concludes today’s give. I want to take a moment to thank the presentersfor sharing their hour and expertise with us. 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