Pulmonologist Brian Block, MD, provides an analysis that clarifies risk factors, in terms of both patient and hospital status. He also discusses how to manage coming flu-related challenges and offers evidence on masking efficacy for both disease spread and severity.
me I'm gonna try to address, in particular the upcoming flu season and how that might have an impact on what's already been a difficult pandemic. So the way we're going to spend the talk today because I'd like to kind of break it down into a few sections, and then we'll pause after each section to look at the chat and see if there's any questions in the Q and A that need to be addressed. I'm going to start by updating you all on the epidemiology of the pandemic. Then we'll talk about ways of deciding and risk. Stratify ing Thio Identify people who are most likely to become very sick from Kobe. 19. Well, in transition to talking about strategies to mitigate the risks of flu and Copa 19 occurring together this coming season in the winter. And then we'll dive in on some interesting theories that air coming out about masks and how they might doom or than just preventing cove in 19 infection. So what's the state of the pandemic here? Mid September and I was looking at an article today. It was actually reflecting on the fact that we're now six months from the start of the lock down in San Francisco with the Bay Area all following suit that same week. So at this point, you can see the curve here that some people will say we've had two waves, Although I know Tony Fauci likes to say that we never left the first wave. We had a pandemic that, at the national level in the United States, took off in March to April, largely affecting the Northeast, with some down trending in case numbers through the springtime, especially in the areas that were initially so hard hit. And then a second surge this summer that affected California more greatly, as well as states across the Sun Belt speaking at the end of July and calming down. Now, we've had almost 200,000 deaths. This is data as of today in The New York Times Tracker, and we're still averaging 752,000 deaths every day. The cases are happening in different places now than they were at the outset. So this is another figure from The New York Times, where red denotes areas that have been mawr impacted by Cove in 19 in the last couple of weeks, you can see that. Whereas the Northeast and the Sun Belt states in California were affected earlier on, we're now seeing more cases in the Plains and the Midwest, places that had not seen such case burden before. Here in California are pattern largely mirrors what happened elsewhere this summer, with the most infections occurring in July and August, and then a downtrend that's been rather steady since middle of August. You can see a little dip here that was actually due to a data reporting error. So that's really should have looked flat around the beginning of August, when we peaked at nearly 10,000 diagnosed cases a day. California's been doing between 80 and 110,000 tests per day for Cova 19. So we were having up Thio. Eight or 10% of these test returned positive in the late summer, with 8% seeming to be a threshold above which the pandemic is considered to be really widespread. We look at reported deaths by day, and here in California we've been having a stubbornly high death number that persists above 100. Even as cases have been down trending since mid August, some of This is because death typically lagged behind the incidents of new cases by several weeks at the more local level. Still here in the San Francisco Bay area. Um, what have we seen? We've been seeing that case numbers and death numbers. Uh, this is from the San Francisco Chronicle are followed the same pattern as elsewhere and are following that same downward trajectory as this has happened. Hospital utilization in the Bay Area. Looking at I C. U beds here in teal era. I'm sorry, General Medical beds here in teal and I see you beds in this kind of mustard yellow. We had an initial surge of infections in April that then dissipated. And actually, at this time at UCSF, we managed to close one of our covert specific ice use at San Francisco General Onley to reopen it in June, when we had a much larger surge of infections with up to 600 people at a time, admitted to the general medical wards across the Bay Area and peaking at about 200 patients in the intensive care units. That number's been down trending and because the length of stay and I see you tends to average about three weeks among survivors who are discharged. This I see you line is going down at a slower rate than the General Medical Ward line. The most, uh, granular data we have or I can share with you is for UCSF, where I pulled this set of information from our data dashboard that we have across the hospital. So as a medical center, this is including UCSF. All the campuses in San Francisco and also in the East Bay done almost 52,000 tests since the start of the pandemic. We're getting turned around quite quickly. A median time to test result is six hours. There triaging test turnaround time so that in patients and emergency room patients were tested most quickly, the percent returning positive. This is looking at dark and lighter orange, representing symptomatic and asymptomatic people getting tested as the case numbers were increasing in the Bay Area and across the state in June, July and August, we were getting a return on symptomatic tests, sometimes in the teens, in terms of percentages returning positive. That number, most recently has come down to less than 5% of symptomatic patients testing positive for asymptomatic patients. We had a few days during the higher number cases over the caseload over the summer, where we're having about 2% of people returned positive. This is now back below 1%. So this is to say, if you met a random person on the street, we had no symptoms. You might suggest that their probability of having SARS cov to carriage would be about 0.8% today. Okay, In terms of hospitalizations at UCSF, this is data for the last several months looking at I C u patients in red and yellow who were ventilated or not ventilated versus the rest of the patients in the Medical Center in Orange and our surge. We've had a lot of patients coming in July and August, peaking at about 40 patients again. This is across all of the different UCSF health medical centers. And then those numbers have been decreasing, particularly of late to date, there have been 419 patients with Cova 19 admitted to U. C. S F. About two thirds of those have been non. I see you level care about a third of them. Every part I see you level care 377 of these patients have been discharged, 16 have died and 26 remain hospitalized. Have transferred out of UCSF to another hospital. So these are actually very encouraging numbers. Um, and I think we're trying to understand why there's been such disparities and reported outcomes across different medical centers and across different times during the pandemic. Now that's a question that I'm very interested in a research perspective, and I'll share some preliminary thoughts about that with you a little bit later during the talk. So this is just a slide that I took from one of the epidemiologists at UCSF who presented it a grand rounds last week, looking at major cities across the United States and chronicling the number of cases that have been identified, the number of deaths at a popular per 100,000 population and the fatality rate deaths per case identified. You'll notice that San Francisco has a very low death per case identified rate compared to other places, although this is still higher than the death per case of influenza, we are also testing mawr, so some of this is because the denominator is larger because we're identifying more cases by testing more, but this is still very encouraging. If you look on the population level of major cities, the desk, her 1000 cases per 1000 individuals in San Francisco also as well. So who is it during Kobe 19. That is getting most sick? I know that some of this was presented at a prior conference, but I wanna push a little bit further into thinking about risk factors for severe illness. So this is the first article I remember reading about Kobe. 19 outcomes in the United States. This was the report from the University of Washington up in Seattle about the experience they had there in February. And this figure is showing what happened to 20 some odd folks who are admitted to the I. C. U. And you can see all these lines in red ending in patient death. So, at the time of publication, with about a quarter of people still not having an outcome in this group, half of them had died suggesting a mortality rate of at least 50% amongst people admitted to the ICU. Yeah, Now we know that not everyone who has cova 19 gets so sick and reports based on outcomes of infection in Italy, suggested that about half of people have mild disease. About a quarter have few or no symptoms, and then about a quarter end up in the hospital or more like 30%. And of those, most are not requiring. I see level care. They would fit in the severe category on this graph, and 5% would fit in the critical category here, requiring I see level support. So who is it that ends up in the sickest portion of this pie chart? Well, a study from Colombia that looked at over 1000 people admitted consecutively to the hospital, of whom 200 were admitted to the I. C. U did some multi variable regression to identify factors that were independently associated with death among people with Cove in 19 admitted to the hospital. What they saw is that older age, chronic heart disease and chronic lung disease and specifically COPD and interstitial lung diseases all conferred an increased risk of death. Yeah, Other reports that didn't uniformly provide kind of a hazard ratio have identified diabetes, obesity, male sex and chronic kidney disease as patient level risk factors for immortality amongst people with Cove in 19. There's one risk factor that hasn't seemed to be a significant. And I know I have many patients who have asked me about this. Patients with asthma often on glucocorticoids inhaled steroid therapy, sometimes on systemic steroids. Other times on monoclonal antibody therapy wondering if they are at increased risk for severe outcomes due to covert 19. And it turns out that several studies now suggest that the answer is no covert patients of this study, looking at several 1000 people admitted to the hospital with co vid found that they were no more likely toe have asthma compared to population level controls. And then, if you adjusted for other things that are known to be risk factors for a severe outcome such as age, sex body mass Index, after adjusting for those asthma, was not associated with being intubated among people who had covert 19. And this paper, which has just come out last week, was kind of postulating why this might be the case. And, as you may have heard, the receptor for the stars Kobe to viruses one called Ace to. There's been a lot of interesting research about differences in expression levels of ACE to among Children versus adults on also whether certain medications, like ACE inhibitors early in the epidemic, were thought to be problematic because they might lead to changes in a sea expression, although data hasn't supported that being problematic. Well, it turns out that the ACE two receptor is up regulated in patients with COPD, and it's down regulated in asthma. So one theory for why asthma is different than other chronic lung diseases in terms of risk for severe outcomes due to Kobe. 19. Maybe this differential expression of face two receptors. So what? The thing that I'm alluded to earlier is that different cities have seen different outcomes among patients admitted to the hospital with Kobe 19. And it's also been the case that during different periods of the pandemic, the mortality rate has seemed to differ. So a question that I was very interested in and started some research on last fall spring was to ask whether surges of patients with Cove in 19 lead toa excess mortality mawr deaths than otherwise would have happened. So I asked this question of whether the burden of Cove in 19 admissions at an individual hospital was associate ID with Cove in 19 mortality. And I thought about this in terms of back to this pandemic curve looking in the month of April because this is a time where part of the country was very affected. The New York City Tri State area was overwhelmed by patient surge, as we all can remember from the media coverage and then pictures like this of a hospital in Queens, with tents and lines of people outside waiting to get treatment. But at the same time that this was going on in New York City, we were seeing nothing like this in San Francisco. Seattle and early sight of infections had cooled off, and much of the rest of the country was not seeing many infections either. So April then seemed like an ideal time to look at the question of how mortality varied with the burden of Copan 19 admissions because they were very concentrated in some locations on Lee. So what I did is I worked with a group that has hospital level data for hundreds of hospitals across the country, and we created a variable called Cove in 19 burden, which we defined as the number of admissions to Ah hospital in April 2020 with Cove in 19 divided by that hospital's bed count, as determined by CMS, the Center for Medicare and Medicaid Sciences. The idea being that 10 admissions to a 50 bed hospital might be one level of burden. But that's very different than admitting 10 patients with Cova, 19 to a 500 bed hospital. So here we could normalize by bed count. What did we see? So this is some data that we have under review for publication at this time. Looking at it's called a Caterpillar plot, with 117 hospitals each having a line here with a estimated mortality rate after adjustment for patient level risk factors and 95% confidence intervals. This horizontal line here shows that across all hospitals 117 hospitals with nearly 15,000 patients with Kobe 19 the mortality rate was 21% point to one. But you can see that at the low end thes hospitals air allayed in order a rate in order by mortality. Some places were having 15% mortality, whereas others were having upto half of patients die, so adding in this color here where we have orange lines representing those hospitals that had the greatest burden. That is the most cove in 19 admissions compared to their hospital sides and blue being all other hospitals, you could see the most of the orange hospitals are off to the right. We're suggesting that the high burden hospitals were those that had the highest mortality rates. And if we kind of rearrange the data where we break hospitals 117 hospitals into Quintiles. So about 20 hospitals, 25 hospitals per grouping here, Quintiles 123 and four. So those hospitals that had fewer patients with Kobe 19 each of them in order the average mortality across thes hospitals was very similar to the overall mortality average for all hospitals. Whereas if we looked at those hospitals with the greatest burden of covert 19 some of these places had twice as many admissions with covert 19 as they had beds in their hospital. The average mortality was upwards of 30% suggesting that mortality was tied to the hospital that people were admitted in and the burden of cove in 19. So we're not the first ones to suggest that hospital level actors also matter beyond patient level factors. There was a study that came out this summer in JAMA internal medicine showing that among people with critical illness due to Koba 19 they were more likely to survive if they're admitted to a hospital that had over 100 I C U beds, compared to a hospital that had fewer than 50 I C U beds. And then in a different study published in the Journal of General Internal Medicine, survival was worse whenever the percentage of occupied beds in the hospital increased. Going to turn to talking about flu and co vet, which presents kind of a new set of challenges here six months into the pandemic. So why is this a problem? Some of these things are obvious, but the C. D. C. Thought it was important enough to create ah, whole section of their Web page on flu and Copa 19. So influenza leads to 300 to 800,000 hospitalizations a year. And as any of you spent time in the hospital, no, the hospitals can get very full in December, January February, and it could be harder to find beds, certainly among people with respiratory failure. So this could just lead the hospitals being full. And if they're already full of patients with flu, it's going to make problems of capacity surge for Kobe 19 patients even more difficult, much of the material that is used to test patients for influenza and Cova 19 is the same, and we've all read about swabs and different types of meat. Transport, media says, could put a strain on testing materials. Finally, of course, some people could get infected with both viruses at the same time. Now the viruses can cause very similar presentation, so you actually need a test to differentiate between the two. But what is it going to mean? If we start seeing a large number of people with co infection, we don't have the experience to really confidently say so. This is why there's a major push to get people to take the flu vaccine this fall. With this flu vaccine just rolling out this week, that U. C S f as I expect it might be in your own health care settings. So flu reduces flu vaccine reduces the chance of getting sick enough that you require a doctor's visit for flew by about half. I think one thing that's really interesting when you think about how well the vaccine works, there is the biologic question. How well does the vaccine lead Tau antibody creation? Then there's the how well did the scientists developing the vaccine Guess about which flu strains would be most prevalent the next year? Because even if the vaccine is great at generating immune responses, that doesn't help. If a new strain of virus comes along that wasn't in the vaccine. So this is one way to look at the efficacy. Another is to say that among those who do get sick and do require hospitalization. Fortunately, the vaccine still reduces the risk of critical illness or death. So in kids, there's some data that the risk of I C. U. Admission is about one quarter amongst people who are vaccinated versus not vaccinated. Among adults who are hospitalized with influenza, the risk of I C. U um, admission or death is cut at about half 40 to 60%. Reduction among adults over 65 who represent the brunt of mortality for patients with influenza is about a 40% reduction and hospitalization. Another way to look at this is what is the risk of getting flew in a given year among adults, and it's about 2% and that number is reduced to just less than 1%. With vaccination, that's a 1.4% absolute risk decrease, which in epidemiologic terms corresponds to a number need needed to vaccine, like a number needed to treat if you've come across the terminology before off 70. So if you vaccinate 70 people for influenza, you'll prevent one case. So the problem is that even though vaccines can have a good efficacy, not only do they have to be designed against the correct strains of flu in circulation that season, but people have to get the vaccine. As you can see here, over the last 10 flu seasons, kids get vaccinated more often than adults, and as a population we only get about half of people vaccinated every year. And during this time period that this figure represents. The recommendation was that everyone over six months should be getting vaccinated. Now, vaccinating half of people certainly helps data from the 2018 19 season. This lead to 4.4 million fewer cases of flu, 58,000 fewer hospitalizations and prevented an estimated 3500 deaths. So every bit of vaccination helps. And last year there were about 175 million doses of vaccine delivered. And given the goal this year, they're producing upwards of 200 million. So what are some barriers to vaccination? And I was trying to think about things that would be most practical as we enter the fall, because it's easy to say that flu vaccination is important, but it's a different thing to say. Well, what can we do about it? So obviously, people who don't have access to a clinician to a primary care provider aren't gonna have as much access to a vaccine. Of course, you can get it at a commercial like a minute clinic or pharmacy, but they might not have access to that. The cost. Some people will have been vaccinated the past of it might be fearful or concerned about side effects. Sometimes the person seeing the patient doesn't bring up vaccination. We all have a million things that we have to dio during an inpatient or outpatient visit, and this is one thing that could get lost in the shuffle. And then, of course, I've been doing a lot of clinic over Zoom recently, which is a major barrier because I'll be seeing a patient who's at their home, and there's no way to get them the vaccine without them coming into a visit. So of course, they can come into a visit. But some people are reticent to do that because they're fearful of coming into the hospital. So one way to address the barriers is to think about this issue of fear where people are worried about adverse reactions. And here I would emphasize that adverse reactions are quite rare. When we look at two different types of vaccine, one being the inactivated vaccine, we see that the most common reaction with that vaccine is a local reaction due to the injection. This would be something like bursitis where we see only eight cases per million people vaccinated. Another is Guillain Barre syndrome. The neurologic consequence. This happens in 1 to 2 people per million vaccinated, and actually, influenza itself can cause GI Hombre syndrome at much higher rates than the vaccine, the live attenuated vaccine. This is the one that you could take. Nasal. Leah's a messed for young adults who are healthy without immuno compromised this version of the vaccine in 2.5 million administrations, as reported to a surveillance network for vaccines Onley eight asthma exacerbations were reported seven cases of anaphylaxis in one case of Bells policies. So these air very low rates of serious adverse reactions. So what could we dio other than presenting patients with this information about the low risk of severe adverse reactions? Well, this is a publication from the Academy of Family Physicians from a group of about 60 clinicians in Philadelphia. The implemented a strategy to Augmon rates of flu vaccination amongst their patients. They were successful and increasing that rate from 66 toe 82%. So they suggest that it's really important to find a champion in the practice, someone who is going to be well versed in the methodology and the data about vaccination and remind others to do it. Another way is to make this a less effortful tasks for patient people seeing patients rather than having to enter in order for influenza, which we could easily forget to dio, what about using standing orders? It could be released by anyone from the nurse to the medical assistant on up. Otherwise, you could do things to optimize documentation. This could be triggers so that the clinician, seeing the patient as a prompt toe, offer vaccination or other ways to make it so it's less burdensome to document about the flu. It's also important to write down whether patients already been vaccinated elsewhere so that we capture that as someone who's been appropriately treated and vaccinated. Reminders air important. So you can't just talk about influence of vaccine at the beginning of the season, you have to have regular reminders about the importance, the data, the methodology and then level um, clinician. Level feedback on how people are doing is also important to give them a sense of whether they're on track and how they're doing it offering vaccination. So these are just based on one practices approach to improving vaccination rates. The Cochran data, that base that does systematic reviews, published a paper in 2018 looking at the evidence behind strategies for increasing vaccination rates for influenza, and this data comes from adults over age 60. So this was saying that there's two things that you need to dio you need to increase demand for a vaccine, so increase the number of patients that are asking for it. Clinicians that air offering it then you need to increase access to the vaccine in different strategies will accomplish each of those tasks. So for increasing demand, important things would include reminder calls to patients. Pamphlets tell them about it, and this can come from anyone on the team to provide education. Ways to improve access Would be things like doing home visits are finding group visits of patients that you can target all in mass to get vaccinated at the same time. Offering free vaccination also increases access. Then you could think about incentivizing the treating clinician and their studies of paying physicians extra incentives if people get vaccinated or doing or withhold other reminders around the clinic and different ways of examining charts. To see vaccination read thes air all things that you could do. Thio Improve Clinician, offering of testing on last issue here, which is masks, which will also bring us back to a question earlier on. So first question is dim, asks prevent spread of coronavirus. So this is a study from nature medicine. Last spring looking at. People who were and were not wearing were and were not wearing surgical face masks and how often you could identify coronaviruses. This is actually not stars Kobe to, but other coronaviruses, influenza or rhinovirus, and amongst these people with PCR confirmed infection. If you weren't wearing a mask for all of these viruses, you find about one quarter one quarter one third of people you could recover virus and drop. The particles adding a face mask seem to reduce the number from whom you could recover virus, particularly in coronavirus and influenza less so and flew. Now the numbers are small here, so the statistical significance is hard. But we actually have a real world experiment of this coming from the Southern Hemisphere and looking at the flu pandemic this year. So this is really interesting. This is from The Economist last week, although a lot of people share this in different publications. This is looking at how bad flu waas in each of the last several seasons, compared to in 2020 and you could see that in the Southern Hemisphere, which of course, has their flu pandemic. During our summer, the flu was taking off just like it has every year in March and then cove it came along. Everyone started wearing masks and they basically wiped out flu in Argentina, in Australia. Similarly, in Chile and New Zealand, we did not see nearly the number of influenza cases is before. So this is kind of really world evidence that masks these air mostly cloth masks or surgical mask not in 95 our protective against the spread of droplets spread of viral infections. It also goes back to the last section on mitigating the risk of Kobe 19 and flew to say that mask could not only protect people from Kobe 19 but it very well could limit the spread of influenza this coming season. So you know, an N 95 reduces the number of particles coming out by 95% that hence the name, whereas a surgical mask is reducing more like two thirds, so it's less effective. But any amount of reduction is going to mean that whatever virus you shed, whatever virus you are exhaling and droplets or coughing out less of it is going to reach another person, particularly if they're wearing a mask. But even if they're not So this led to an interesting theory from, uh, team at UCSF. This is an article just a perspective in last week's New England Journal, and they also presented this information last week at the UCSF grand rounds. Just a quick plug. I would say that those air available every Thursday on YouTube they're about 75 minutes each time. They've been fantastic, and I've learned a lot about them through the pandemic, so I'd encourage you to check them out if you're interested. But the question is, well, if masks still might let people get sick, but their meaning, they transmit and receive much less virus. Perhaps this could be something that, while we're waiting for a vaccine as a new form of very elation, so very elation is the strategy that preceded vaccination for variola smallpox, where they would take the blisters of smallpox or some puss and use that to infect another individuals. They would take it from an infected individual as a way to intentionally give it to another person, but with the goal being that by inoculating them this way, they would get less severe illness subsequently, be immune. And so this kind of anticipated the development of vaccination. So the question is, Does face masking for Cova? 19 offer the opportunity to accomplish something similar to vary elation, where we know that the dose of virus that a person inhales is related to how sick they get. This has been known for decades, and we have some anecdotal evidence from health care workers in high burden settings like China at the start of this pandemic or Italy who got very sick at high rates. So there is some experimental evidence to support this. This is data from hamsters who were given in red hamsters. This is a severity score. Looking at a C T scan severity of pneumonia day after injection. And we had mice here, representative in red who were given a high dose of SARS. Kobe, too. Mice and blue who were given a lower dose and black given a control. So obviously none of these control my Scott sick CT severity score was low. But you could see that there is a dose response here where the mawr virus that hamsters were given, the sicker they got. And in another study they actually showed that trying to replicate the effect of masking would attenuate the illness that developed. This is some lab evidence to suggest that Max Mask can reduce severity of illness. There's also epidemiologic illness and these slides I borrowed from Dr Gandhi, who had presented this paper in the New England Journal and also at our grand rounds last week. So this is data from the US looking at 2018 2019 2020 and you can see there's a seasonality here to the percentage of deaths due to pneumonia, flu or Kobe 19 where every winter we have an increase in respiratory related deaths. And then in 2020 we had this massive increase due to the first jolt of influence of Kobe, 19 in the Northeast. Then case numbers came down. Death came down. And then over the summer, as I showed you before at the outside of this talk, we had even Mawr infections. But we didn't see such a high increase in mortality. Now there are some caveats here. It could be that people getting sick are younger now or not as many comparability com or abilities. We obviously have different treatments available for the vaccine. Eso. We'll need to have more information to know if this is mediated by mask wearing. But the theory is that these folks who got infected in April May we're likely not wearing masks and exposed to more virus. Whereas people infected this summer might have been exposed to less. This is actually borne out in other countries as well. This is data from Spain where you can see cases in blue and deaths and red. And as cases went up at the start of the pandemic in Spain a couple of weeks later, death similarly started. Go up and come down along with cases Now. More recently, cases have again gone up, but deaths have not. So the question is, Do masks lead Teoh a way of buying time while we're waiting for vaccination by not only reducing the spread of disease but by by reducing the mortality of Copan 19 because people get a lower viral inoculation than they would have if they were not masked or the other person was not masked. So that was the last thing I wanted Thio address. So I'll quickly review are learning objectives and then see if there's any more questions as we wrap up. So the objections were to describe risk factors for a severe covert 19. We talked about patient level risk factors, hospital level risk factors and then in this last part, other risk factor would be the time that you were infected with it, seeming like the mortality might be going down over time as the pandemic evolves. We talked about strategies for reducing the spread of cova 19. This included vaccination and masking. We talked about strategies for increasing the percentage of people, the number of patients to get vaccinated. Then we talked about masking not on Lee as something that reduces the probability of getting sick. But it might reduce the degree of illness and people who get sick something like the old version of smallpox prevention, which involved vary elation. So I'm really glad you've had the opportunity to talk to you about Kobe 19 today. I hope you enjoyed this and got something out of it.