At the end of 2018, we remember and respect Influenza, 100 years after the great pandemic

The Mother of All Pandemics
In the 1918-1919 calendar year, the world experienced the worst influenza pandemic in modern times. Coming on the heels of WWI, the H1N1 pandemic occurred in three waves – in the spring of 1918, fall 1918 and spring 1919. Estimates suggest that the pandemic infected a third of the world’s population, with 50 million people dying worldwide, including 675,000 Americans. Mortality was high at extremes of ages, but what sets this particular pandemic apart was the significant mortality (over half of all deaths) in young, healthy 20-40yr olds. Why such devastating morbidity and mortality? Perhaps a combination of war-ravaged, crowded conditions, malnourishment, inadequate healthcare resources (many doctors/nurses were deployed at war), and poor hygiene. In the early 20th century, there were no influenza vaccines to prevent flu or lessen its symptoms; no antivirals to help reduce transmission; no antibiotics to treat post-influenza bacterial pneumonia. The Smithsonian National Museum estimated that the total death toll of the 1918 pandemic outnumbered military deaths in both World War I and II. You can watch a video created by the CDC about the 1918 pandemic here. This avian-origin H1N1 pandemic has been called “The Mother of All Pandemics”, setting the stage for all of the subsequent epidemic and pandemic strains of influenza we have experienced.

After 1918: Influenza still deadly, though not as devastating
In 1957-1958 an H2N2 avian influenza virus caused a pandemic resulting in 1.1 million deaths worldwide including 116,000 Americans. 10 years later, another avian-based virus H3N2 triggered a similar sized pandemic with 1 million deaths worldwide and 100,000 Americans. The H3N2 still circulates as a seasonal flu virus and is included in seasonal vaccines. The next major pandemic was triggered by a novel influenza A virus called H1N1pdm09 in 2009, originating in the United States. By this time, seasonal influenza vaccines had included H1N1 but this variant was completely different from the seasonal flu vaccine, resulting in an estimated over half million deaths worldwide and up to 18,000 Americans.

Today: There is still work to be done
Since 2009's pandemic, seasonal influenza is still prevalent, with an estimate of over 291,000-645,000 deaths from seasonal influenza worldwide. The highest mortality rates are in poorer, developing countries, with individuals at extremes of age being most vulnerable to death from seasonal influenza. We still do not have a universal influenza vaccine, though research is moving in that direction. The 2017-2018 influenza season brought a serious influenza epidemic, with 48.8 million illnesses, 959,000 hospitalizations and 79,400 deaths estimated in the United States alone. This week, the Infectious Diseases Society of America (IDSA) released updated guidelines for diagnosis, and management of seasonal influenza. In the guidelines, they recommend testing for influenza in upper respiratory specimens of high risk patients, when testing can reduce unnecessary additional testing/inappropriate antibiotics, or when testing can influence chemoprophylaxis for high-risk household contacts. Annual seasonal flu vaccination reduces the risk of influenza by 40-60% and is still recommended as the best way to mitigate the impact of seasonal influenza, but antiviral prophylaxis may be necessary in outbreaks or for certain at-risk populations. Other ways to prevent spread include hand hygiene, limiting contact with people who have influenza-like illness, and if you have such an illness yourself, STAY HOME. 

More than 166.6Million influenza vaccines have been distributed in the US as of December 20, 2018.The influenza vaccine may not always be a 100% match to all circulating strains, as we saw with last year's flu season.  This year’s vaccine contains an influenza A H1N1pdm09-like strain, an influenza A H3N2-like strain, and influenza B strains from the Victoria and Yamagata lineages. Updated this year, the Advisory Committee on Immunization Practices (ACIP) also recommends the live-attenuated influenza vaccine (FluMist); however, the American Academy of Pediatrics suggests this only be used if the alternative would be no flu shot at all. The CDC can explain the types of vaccines available and who should get them. 

Final thoughts about the flu 

Regardless of which vaccine is more appropriate, our ancestors would probably encourage us to just get ANY vaccine if it would help avoid recreating the influenza pandemic of 1918. There's still time - it's not too late so if you haven't gotten your flu shot, consider getting it today!

Eye Protection and Seasonal Influenza

At the last HICPAC meeting, Drs. Bryan Christensen and Ryan Fagan led an excellent discussion of the following question: should eye protection be included in droplet precautions for seasonal influenza and other respiratory viruses? 

Eye protection is one aspect of Standard Precautions, of course, to be used whenever there is a risk for splashes or sprays of blood and body fluids (BBF), or during aerosol-generating procedures. However, there is no recommendation for routine use of eye protection as part of Droplet Precautions—it’s an “unresolved issue”. 

Nonetheless, whenever CDC has had to issue interim guidance for new respiratory viral threats (SARS, MERS, novel influenza A viruses, etc.), they’ve included the routine use of eye protection. But seasonal influenza kills far more people annually than any of the novel threats, and there’s little reason to believe that seasonal flu strains can’t use the eye as a portal of entry (in addition to rarely causing direct ocular disease). The same applies to various of the other respiratory viruses (adeno, RSV, rhinovirus, hMPV, etc.). 

As is so often the case, we don’t have much published data to help answer this question: some work done in the 80’s suggested that eye protection was important for RSV transmission prevention, and Dr. Werner Bischoff demonstrated in an experimental system (air chamber into which live attenuated influenza vaccine virus was aerosolized) that the eyes could serve a portal of entry for influenza. So definitely wear goggles if Werner invites you to enter an airtight test chamber.

Anyway, thanks to Bryan and Ryan for their review (I will link to it when the transcript is out), and to HICPAC members for the lively discussion that followed…so what do you think? Does your center use eye protection routinely for droplet precautions for seasonal flu?

Fear the "freely evolving turbulent puff cloud"!

It’s well worth your time to check out a great video recently published in NEJM by Dr. Lydia Bourouiba (from the MIT Fluid Dynamics of Disease Transmission Laboratory). Simply entitled “A Sneeze”, the images and videos graphically demonstrate the biological plausibility of the findings Eli describes in his recent post on presenteeism.

In her description, Dr. Bourouiba writes:

"[The video]…shows a turbulent cloud that consists of hot and moist exhaled air, mucosalivary filaments and drops, and residues from droplet evaporation (nuclei). The ejection lasts up to 150 msec and then transitions into a freely evolving turbulent puff cloud. The largest droplets rapidly settle within 1 to 2 m away from the person. The smaller and evaporating droplets are trapped in the turbulent puff cloud, remain suspended, and, over the course of seconds to a few minutes, can travel the dimensions of a room and land up to 6 to 8 m away.”

Thanks to John Boyce for pointing this out on the SHEA Open Forum (join SHEA to sign up!).

Paid Sick Leave: Avoiding Contagious Presenteeism and Preventing Influenza

The US of A is the ONLY industrialized country without nationwide access to paid sick leave. Reread that sentence several times to let it sink in, it's OK, I'll wait for you. Opponents of paid sick leave say that mandatory sick leave increases the cost of labor and hurts job creation. In addition, they suggest  that paid leaving increases shirking behavior and "noncontagious absenteeism". However, there are potential economic benefits for paid leave, particularly in regards to encouraging workers to not work when they've acquired an infectious disease - "contagious presenteeism."

Before wider adoption of mandatory paid sick leave in the US, it is likely that the health and economic value of such mandates will need to be estimated. To that end, economists Stefan Pichler and Nicolas Ziebarth have just published an unreviewed working paper in the National Bureau of Economic Research, that sought to estimate the impact of paid sick leave on labor supply and avoiding presenteeism as manifest through reduced influenza cases. They were able to take advantage of the staggered implementation of several city (San Francisco, Washington DC, Seattle, Philly, Portland and New York City) and state (CT, CA, MA, OR) sick leave mandates in order to determine the reduction in population-level influenza-like illness (ILI) cases using Google Flu data (2003-2015). Other cities, and states not covered by the mandates served as controls. 

When they examined the impact of the mandates using city-level data and difference-in-differences models, they found that gaining access to paid sick leave resulted in a 5.5% reduction in ILI per 100,000 doctors visits. When analyzed using state-level data, they found a 2.5% reduction in ILI after adoption of mandatory sick pay. Importantly, the authors state that "infections rates may further decrease in the medium to long-run when employees have accrued larger amounts of paid sick days." The paper then takes a deep dive into the underlying behavioral mechanisms of these programs (contagious presenteeism and noncontagious absenteeism) and the positive and negative aspects of mandatory sick leave using US and German data, which makes for interesting reading if you have time. 

The findings of this paper suggest an important population-level benefit for mandatory sick leave policies, which suggests the US should consider passing a bill to make such a policy nationwide. In fact, President Obama said this during his 2015 State of the Union Address: “Send me a bill that gives every worker in America the opportunity to earn seven days of paid sick leave. It’s the right thing to do. It’s the right thing to do.” I'm thinking more mandatory sick leave and less influenza would make America a wee bit greater.

Image Source: nyc.gov

My week with SIRS

I’ve been down for several days this week with influenza A, which is not shocking since this year’s vaccine (yes, I did receive it) has a whopping 51% effectiveness against the predominant circulating strain. You’ll have to find our prior posts on the horrible influenza vaccine on your own, myalgias prevent me from adding more links. 

Early into illness, I had a vivid dream in which I was being admitted to a hospital. A doctor who looked exactly like the Phillie Phanatic told me I met criteria for SIRS/sepsis, and started administering vancomycin and piperacillin-tazobactam by direct injection into my kidneys. 

But the only thing more boring than stories about people's self-limited viral infections are stories about their dreams, so I’ll stop now and retire quickly to my sofa (this, of course, is a really bad sepsis pun about the new qSOFA score). For while I did meet SIRS criteria, I never met qSOFA criteria (RR >= 22/min, altered mentation, or SBP <= 100 mm Hg), demonstrating with an N of 1 that qSOFA is more specific for identifying those likely to suffer "poor outcomes typical of sepsis".

Eli already linked to the Third International Consensus Definitions for sepsis, which are well worth a read. There is also an excellent piece in Slate about sepsis, by Dr. Jeremy Faust (an Emergency Medicine resident at Mt. Sinai in NYC), that accessibly covers the new definitions and the unintended adverse consequences of the CMS sepsis measure, including those that impact antibiotic stewardship. Finally, ECCMID is underway and I’ve already read tweets about a terrific session on sepsis there today—I’m assuming the content will be available at this link once the session is uploaded.

Clarification: I'm in favor of mandating influenza vaccination of healthcare workers (for now)

There's been some misunderstanding of the motivation behind my recent posts offering suggestions for improving the implementation of compulsory influenza vaccination policies and acknowledging the limitations of the existing data supporting vaccine mandates. Most of the snark was on twitter where folks challenged my commitment to infection prevention and my interpretation of the data. If I can dish it, I better be able to take it. With that being said, however, I still feel a need to clarify my support for mandatory influenza vaccination policies in both acute care and long-term care settings. But...

1) I will only support such policies for 4-5 years. If those that push these policies can't come up with better clinical trial data during that time, I'm going to call BS. There is simply no excuse for stretching the existing data to drive change now and not validating your claims. Recommend the mandate, but then do the proper studies.

2) CDC and others must fund studies evaluating the benefits of mandatory vaccine policies in acute care settings. There is never going to be a better time than now, when hospitals are implementing mandatory vaccination programs, to fund the necessary cluster-randomized and quasi-experimental studies. Wouldn't it be great if we could find 50 or more hospitals planning to implement an influenza vaccine mandate and then fund a mixed-methods, stepped-wedge cluster randomized trial as those hospitals implemented the policy over the next 3-4 years? I think it can happen and SHEA, IDSA, PIDS and APIC need to demand such a study.

3) As Sara Cosgrove and I wrote in the 2007 SHEA Business-Case Guideline: "Most hospital epidemiologists or infection control specialists want to increase the resources available for infection control activities, but it is important to avoid overestimating benefits or underestimating staff and time costs. Overestimation in an initial analysis may improve the situation in the short term, but it will hinder efforts and necessary trust in the long term after actual resource audits are performed." There's simply no excuse for hand waiving and over promising the benefits of healthcare worker influenza vaccination. It erodes trust and prevents the necessary validation studies from being funded. Please take the long view and don't be afraid to challenge dogma.

Happy holidays!

Potential Risks and Benefits of Gain-of-Function Research - December 15-16

About 3 months ago we posted a letter from Marc Lipsitch highlighting the risks of "gain-of-function" research. He described this research as "experiments that create potential pandemic pathogens from virulent precursors that are not readily transmissible." The concerns about this particular kind of research are particularly acute when applied to pathogens with pandemic potential like MERS, SARS and influenza. In two weeks (December 15-16) there will be a 1.5 day meeting in Washington DC at the National Academy of Sciences on this topic. The meeting is open to the public with each session including 30 minutes for audience discussion. In addition, public input is sought electronically before the meeting via the meeting meeting web page. A very important topic - hope some of you can attend.

The agenda and registration information are here: http://dels.nas.edu/Upcoming-Event/Risks-Benefits-Gain/AUTO-9-61-70-Q

Traveling With Ebola Is Not Traveling With Influenza

With everyone away at IDWeek, I've had time to think about Ebola and things like airport screening programs. I'm not supportive of outright travel bans. As many have eloquently said, bans will do more economic harm than good and hinder efforts in West Africa. However, I'm worried that we might be equating Ebola with Influenza. Many of the discussions concerning travel restrictions and Ebola spread have centered around models and estimates derived from respiratory viruses epidemics like the 2009 H1N1 influenza pandemic. Yes, influenza and Ebola are both viruses, but that's like equating a sparrow and an Allosaurus because they're both dinosaurs.

The first and perhaps most important difference between the current Ebola outbreak and the the 2009 H1N1 pandemic is that Ebola it is very slow moving. For example, the first case of Ebola is thought to have occurred 307 days ago on December 6th in a two-year old boy. Since that time there have been an estimated 8,032 cases (granted these could be underestimates). If you compare a similar 307-day period for 2009 H1N1, April 12, 2009 to February 12, 2010 CDC estimated that between 42 million and 86 million cases occurred in the US with a mid-level estimate of 59 million people infected. Think about that - 7300 times more cases of H1N1 using the mid-level estimate during the same 307 days.

Another difference between influenza and Ebola is the incubation period (time from exposure to symptoms). Generally, the incubation period for influenza is 1-4 days (2-day average). For Ebola symptoms appear 2 to 21 days after exposure with an average of 8 to 10 days.

A final difference between Ebola and 2009 H1N1, which seems to be overlooked in discussions of airport screenings and other control measures, is infectivity during the incubation period. Put another way, can you transmit the virus without knowing you are sick? With Ebola, humans are not infectious until they develop symptoms. In comparison, with 2009 H1N1 it's reported "that pre-symptomatic influenza transmission occurred via both contact and respiratory droplet exposure before the earliest clinical sign, fever, developed" in a ferret model. This finding has been confirmed in humans. Interestingly, SARS is not infectious prior to symptom development (see CDC and Zeng et al), which may explain why we were ultimately able to contain SARS (unlike influenza).

To summarize, Ebola is slower moving, has a much longer incubation period (especially compared to the duration of a transcontinental flight), and is not contagious before symptoms develop. What does this mean? It means that if Ebola was as infectious as influenza, millions would have already died - apocalypse. It also means that since Ebola is not transmissible during its long incubation period, it may be possible to quickly isolate patients when symptoms develop. Thus, airport screening on exit or entry could limit transmission and perhaps through early diagnosis allow Ebola infected patients to receive life saving treatment more quickly.

A more concrete example: Imagine a person infected yesterday with influenza but still asymptomatic during their two day-incubation period. This person would screen negative overseas and in the US. However, it's highly likely that they are already infectious or will become infectious during their flight. Thus, many other passengers in the airport and plane would take influenza home with them as a vacation souvenir. Screening doesn't work for influenza. This would not be the case with Ebola because they will detect their symptoms as they become infectious and only spread it though blood exposure - something unlikely so early in the infection even on a long transcontinental flight. And think about how many times another person has bled on you even when they were bleeding (i.e. the Ebola condition) versus how many times someone has coughed or sneezed on you when they were coughing and sneezing (the influenza condition). **cough**

Airport screening for Ebola symptoms may still be ineffective, but I would like to see a few more mathematical models analyzing the epidemiology of Ebola and the impact of specific screening programs. In the meantime, let's focus our attention and resources on the horrible plight in West Africa.

image source: xkcd

Influenza "Gain of Function" Research - Worried? Read on

Marc Lipsitch (Harvard School of Public Health) and many others are highly concerned about influenza "gain of function" research.  Recently, Marc sent around an email that I've posted below as some of you might want to support this effort. Those who would like to learn more about this issue, I suggest you read his recent NYT op-ed, which he mentions below, and also listen to yesterday's NPR Morning Edition discussion on the subject.

Dear Colleagues: 

I want to reach as many colleagues as possible about a very important issue, the growing experimental program underway at institutions around the world to create novel strains of influenza that are transmissible in ferrets, the leading animal model for human flu infection.  These so-called "gain of function" experiments create potential pandemic pathogens from virulent precursors that are not readily transmissible; as such they are a uniquely risky approach to studying influenza. A group of scientists and other concerned experts is calling for a curtailment of such experiments until a serious, quantitative, disinterested risk assessment has been performed to ask whether these experiments offer unique benefits, unattainable by safer means, that justify their unique risks. We have called for an Asilomar-like meeting to start such a process, which would include all points of view under a neutral sponsorship.

These experiments create pathogens which have the potential to spread widely if accidental infection occurs and could, in the worst case, lead to an uncontrolled pandemic. Recent events in federal labs in the US show that even in the leading laboratories, human error leads to the risk of human exposure. This is not an unusual occurrence; in the period 2004-10 there were two loss or release events PER WEEK in biocontainment labs in the US involving Select Agents. While the probability of such incidents in any given lab in a year can be estimated from available data, experiments that deliberately enhance transmissibility of influenza viruses present orders of magnitude greater risk than anthrax or wild-type, poorly contagious avian flu strains, because of the risk of transmission.

I am writing you to invite you to join the Cambridge Working Group, www.cambridgeworkinggroup.org, by supporting our statement that these experiments should be curtailed until there is a serious, quantitative, risk-benefit analysis of what benefits are uniquely obtainable by this exceptionally risky class of experiments, and whether these unique benefits justify the risks involved. Note that we are not calling for a halt to work on dangerous pathogens in general; our call focuses on the creation of novel, transmissible dangerous pathogens, one of many techniques available for studying such organisms but a uniquely dangerous one.

The website has a link for you to add your support to that of a growing number of scientists and others, as well as several pages of links to relevant articles, press coverage and the like. For those interested, I wrote a recent New York Times op-ed on the topic. Much more detailed and technical information is available on the website.

Thank you for considering this request.

-Marc

Sometimes, what we suffer from is bigger than we think

There was a time when the makers of Tamiflu (oseltamivir) ran ads with the tagline "sometimes, what we suffer from is bigger than we think" urging folks to see their doctor for viral URIs and get treatment for the influenza.  Now, however, I think the tagline is perfect for describing the predicament clinicians, public health officials and governments are in when trying to decide what to do with neuraminidase inhibitors (oseltamivir and zanamivir) for influenza prevention and treatment. You see, what they all suffered from when trying to decide what to recommend was a missing data problem, specifically unpublished clinical trial data held back by the pharmaceutical companies (Roche and GlaxoSmithKline). This "missing data" problem was bigger, much bigger, than initially appreciated.

Today, the Cochrane Review updated the "Neuraminidase inhibitors for preventing and treating influenza in healthy adultsand children" based on full internal reports of 46 clinical trails. The key findings are that neuraminidase inhibitors reduced the duration of symptoms by 1/2-day in adults, with data uncertain in children and that there was no evidence of a reduction in hospitalisations or serious influenza complications including pneumonia in adults or children. Side-effects, such as nausea, vomiting, psychiatric events etc, were significantly more common in the oseltamivir treated groups. In prophylaxis trials, both agents reduced the risk of symptomatic influenza in individuals and in households.

Some quotes from key individuals involved with the release of this report:

Dr. David Tovey, Editor-in-Chief, Cochrane: “Initially thought to reduce hospitalisations and serious complications from influenza, the review highlights that Tamiflu is not proven to do this, and it also seems to lead to harmful effects that were not fully reported in the original publications."

Dr. Tom Jefferson and co-authors of the review: “We urge people not to trust in published trials alone or on comment from conflicted health decision makers, but to view the information for themselves.”

Dr. Fiona Godlee, BMJ Editor: “We need the commitment of organisations and drug companies to make all data available, even if it means going back 20 years. Otherwise we risk another knee-jerk reaction to a potential pandemic. And can we really afford it?”

Dr. Harlan Krumholz, Yale Professor, wrote an accompanying editorial in the BMJ. In addition to describing the surprising need for more studies 15 years after the drugs were approved and listing the current and outdated public health guidelines he emphasized that "from a health system perspective, the enormous expenditures do not appear to have commensurate benefit."

UPDATE: CDC Says Stay the Course; Main reason appears to be that observational data were not included in Cochrane analysis. Of course, it is unethical to do an RCT in a pandemic, so much of the data required for decision making around pandemic preparedness wouldn't be from RCTs.

Additional References:
1) Heneghan et al. Zanamivir for influenza in adults and children: systematic review of clinical study reports and summary of regulatory comments BMJ 2014

2) Jefferson et al. Oseltamivir for influenza in adults and children: systematic review of clinical study reports and summary of regulatory comments. BMJ 2014

Well child, Sick child

Who doesn't get a little bit nervous in a pediatric clinic waiting room? Even in an office that divides “sick” from “well” waiting areas, kids tend to move pretty freely, and of course the pathogens contained in respiratory droplets move even more freely. I always assumed that the risk from these exposures (of the “well-children” to the “sick-children” in ambulatory clinics) was fairly small, at least compared with the usual community exposures kids have at home, at day care, at the children’s museum, etc.

Our colleague Phil Polgreen and his group analyzed some “Big Data” (the Medical Expenditure Panel Survey) to try to determine if well-child visits are indeed a risk factor for subsequent influenza-like illness (ILI). Their findings are published in this month’s issue of Infection Control and Hospital Epidemiology, and confirm the suspicion that the ambulatory pediatric clinic is likely to contribute to viral respiratory pathogen transmission. The odds ratio for ILI after a well-child visit (within prior 2 weeks) was 1.54 (95% CI, 1.43-1.66), which seems pretty large, though the absolute risk was modest (~3% increased risk). However, if you consider the total number of such visits annually, the number (~800K) and cost ($500 million) of excess ILI cases is substantial.

Lisa Saiman has an excellent editorial discussing the implications of these findings, the main message being that we need to pay more attention to infection prevention in ambulatory settings. My only additional suggestion (which, admittedly, may be unrealistic for many clinics): forget about separate waiting rooms, instead have physically or temporally separate clinics for well-child versus sick-child visits (with clear signage to direct kids who happen to be sick during a well-child visit to the “sick-child” clinic).

Image: The Sick Child, by Gabriel Metsu, 1660

Flu: A ground-level view

This flu season seems to be having a huge impact, though the data from CDC don't seem to be giving a complete picture. It is clear that many states continue to be experiencing widespread activity, but the national data don't capture the severe morbidity and the mortality that is occurring in young adults due to H1N1. Just at my hospital we have had several young adults require ECMO. We have heard reports of hospitals having to borrow ventilators due to the number of patients with influenza associated ARDS, and we are aware of deaths due to hospitals exceeding their capacity to provide ECMO. There is the perception among many clinicians that the severity of disease seen this year exceeds that seen during the 2009 H1N1 pandemic. Part of the problem, at least in Virginia and many other states, is that influenza deaths in adults are not reportable, nor do we have accurate data on patients requiring mechanical ventilation or ECMO. Perhaps it's time to rethink influenza surveillance particularly since diagnostic testing has improved significantly over the past few years.

Infectious Art

The University of Iowa College of Public Health has a fascinating new fund raising event - Infectious Art.  The College collaborated with a local design group to create jeweled representations of a wide variety of human pathogens and vectors. The aim was "to present the dichotomy between the aesthetic beauty of pathogens and the havoc they wreak on humanity." Ever wanted a Borrelia ring (one ring to bring them all and in the darkness bind them), Influenza A cufflinks, or HIV earrings? Me too. All proceeds will go to support the College of Public Health. Items may be viewed and purchased online or at American Public Health Association Annual Meeting Nov. 2-6 in Boston, Mass., at the University of Iowa College of Public Health's booth (#1331).

Aspergillus Pin

h/t Cassie Cunningham

Influenza Vaccine Has Miracle Powers After All*

This blog hasn't always been kind to the humble influenza vaccine. So in fairness to our trusty old vaccine friend, I'd like to highlight a recent study published in Lancet ID by Jeffrey Kwong and colleagues in Toronto. They utilized 19 years of data (1993-2011) from the universal health care system databases in Ontario Canada to assess the risk of Guillane-Barré Syndrome (GBS) after influenza vaccination and after influenza infection. They accomplished this using a self-controlled, risk-interval design. This design compares the risk of GBS in a predefined risk interval after exposure to the vaccine or infection and compares it to the risk in the control period outside the selected exposure period. In this case, the exposure period was the first 6 weeks post exposure and the control period was weeks 9-42. Importantly, the patients were conditioned on having GBS in either the risk or control period and each patient served as their own control, which eliminates selection bias. Outcome of GBS was determined using ICD-9 or ICD-10 primary billing codes, which have reported positive predictive values in the 60% range. This is a limitation of the study.

They identified 2831 patients with GBS.  Within the 42 week period, 330 cases were preceded by influenza vaccination and 109 cases were preceded by influenza infection.  The risk of GBS was 1.5 times higher in the initial 6 weeks post vaccination compared to weeks 9-42. The risk peaked in the third week post vaccination with twice the risk. The risk was higher in patients ages 18-64 compared to older adults. Importantly, even this increased risk adds up to one GBS admission per 1 million vaccinated. I also don't think we can rule of influenza infection causing this post vaccine risk since people are more likely to receive vaccine when influenza virus is circulating in the community.

In the 6 weeks post influenza-coded healthcare encounter, the risk of GBS was 15 times higher than baseline and peaked at 61 times higher in the first week post infection. Pending a formal competing risk analysis, patients should continue to be informed of a small increased absolute risk of GBS associated with the vaccine, but also a large risk associated with the infection. Of course, there other benefits associated with influenza vaccination, which should also be discussed with patients. To be clear, influenza vaccine IS a miracle when it's compared to influenza infection.

Image source: wikipedia

*Title is just playing off the title of one of our prior posts on influenza vaccine. Nothing in medicine has miracle powers, since medicine is a science. However, if there is anything close to a miracle it would be vaccines. Antibiotics would be a close second.

Infection control rule #1: if you're sick, stay home.

A new study from the University of Pittsburgh Graduate School of Public Health uses epidemic modelling to determine the impact of reducing presenteeism on workplace transmission of influenza during a pandemic, such as the one we experienced with H1N1 in 2009.

The investigators compared the status quo (72% of employees with paid sick days stay home with flu, while 52% of those without sick days do not) to three other scenarios: (1) all employees have access to paid sick days, (2) all also have access to 1 flu day, or (3) all also have access to 2 flu days. The concept here is that employees are specifically paid to stay home when ill with influenza.

The findings:

• Universal paid sick days resulted in a 6% reduction in workplace transmission (applied to Allegheny County, PA [population 1.2 million] that is equivalent to nearly 4,000 fewer infections).
• Adding 1 flu day resulted in a 25% decrease in workplace transmission (15,000 infections averted)
• Adding 2 flu days resulted in a 39% decrease in workplace transmission (26,000 infections averted)

Bottom line:  Efforts to reduce presenteeism (a horizontal infection prevention strategy) can have significant impact. 

Implication:  If we're really serious about reducing infections transmitted to patients in hospitals from staff, we must start thinking about how to reduce presenteeism. And that's a lot harder than firing healthcare workers who refuse to take their flu shot. 

Photo:  Man by Virgil Cantini, 1965, bronze and steel sculpture on Parran Hall at the University of Pittsburgh Graduate School of Public Health.

H7N9 Mortality

A week ago, in response to some scary reports, I tweeted this:

I wanted to see how my public prediction held up in the H7N9 outbreak after an admittedly short 7 days and approximately 2 weeks after the outbreak gained widespread attention. To do this, I simply plotted the reported mortality rate using the daily case and mortality counts available through the @WHO twitter feed between April 1st and April 16th.

While the case counts have gone from 3 to 63 over this period, reported deaths have risen more slowly from 2 to 14 and the mortality rate has fallen from 67% to 22%. When I made the prediction it was 30%. If I had included data from April 17th, the mortality rate would have fallen further to 20.7%, 17 deaths and 82 cases. I've plotted the daily mortality rate below. Good news, but still a ridiculously virulent virus. Hopefully, as more surveillance specimens return, the mortality rate will continue to fall. Hopefully.

Addendum: Immediately after posting this, several twitter discussions began. To clarify, I know many of the sick patients are still hospitalized in the ICU. Even cases that appear to initially recover could succumb to secondary bacterial infections. Helen Branswell made the important observation that two of the three cases in the recent NEJM report were infected with Carbapenem-resistant Acinetobacter baumannii and at least one of them didn't appear to receive appropriate antibiotic therapy. Hopefully, as recognition increases, so will early diagnosis and early antiviral therapy along with effective antibiotic therapy (if available).

Influ-Venn-Za

Having trouble keeping those H's and N's straight? Here's a great graphic from Information is Beautiful.

Did Google Flu Trends Miss the Mark This Year?

There is a nice review of how various influenza-like illness surveillance systems performed during the 2012-2013 influenza season by Declan Butler at Nature.com. There is some good news and some bad news. The good news is that the timing of the start and peak of the epidemic appear pretty well-aligned between the three methods. However, it appears that the "Google Flu Trends" peak was much higher than the CDC and "Flu Near You" peaks. Reasons for the possible divergence include timing of non-influenza ILIs in the community, a bad norovirus season and excess media coverage including CDC's alert of a bad/early season in early December 2012.

I think these reasons and others given in the article have a lot of face validity and certainly follow what many were feeling as the epidemic progressed. One thing I haven't seen in the coverage is whether the "peak" count of ILI is all that important. I'm more interested in the timing of the epidemic's beginning and the peak and not so interested in an absolute count. I suspect that the absolute number of infections helps in future years, but the timing is more important in the current year. I hope someone will comment or covertly tell me why the peak amount matters so much. It's not like ILI is the greatest definition anyway.

Another assumption I haven't seen discussed is whether Google Flu Trends actually got it wrong or was it the other methods which missed the mark. When you have an imperfect definition, it's hard to call any of these three methods a gold standard. Any attempt to pick a winner seems a bit arbitrary. If the intent is to match the CDC so rates can be compared from year-to-year, that's one thing. But what if we are burdening ourselves with a suboptimal gold standard. A lot of sunk costs go into any legacy system, but it's at least worth wondering occasionally if the legacy is worth continuing.

Image source: http://www.nature.com/news/when-google-got-flu-wrong-1.12413

Living and breathing = aerosol-generating procedure

Eli, who is busy this week attending ScienceOnline2013, pointed me to this newly published study in Journal of Infectious Diseases on influenza transmission. Werner Bischoff and colleagues at Wake Forest measured influenza virus RNA concentrations in air samples taken between 1-6 feet from influenza-infected patients’ heads during routine care. Among the 61 influenza patients they analyzed, 26 released measurable influenza RNA into room air, and 5 did so in very high concentrations. The figure below, from the paper, shows that small particle aerosols containing influenza RNA could be detected 6 feet from the patient’s head (for 9 patients, at levels exceeding their low estimate for a 50% human infectious dose).

What does this mean? Well, this report confirms that some of our influenza patients (those we’ve previously termed “superspreaders”) expel airborne virus in small particles (capable of long-distance spread) even when they aren’t undergoing an “aerosol-generating procedure”. Life with influenza, for them, is an aerosol-generating procedure.

How to translate this into reduced transmission in healthcare settings is tricky, and Caroline Breese Hall’s commentary is worth reading in this regard. A couple things to keep in mind—these investigators measured RNA, not viable virus. And even if we assume transmissibility from the RNA numbers, only a small number of the 61 influenza patients were high-concentration small-particle aerosol emitters. These data alone don't support making sweeping changes in practice for all patients with influenza-like illness (e.g. N95 masks, negative pressure rooms). The challenge is to learn how to identify potential “high risk emitters” early, or to identify specific settings when practice change is needed (based upon dynamics of the community outbreak, etc.).

Influenza Vaccine Effectiveness Study Author Responds

Late last week, Dr. Jackson, one of the co-authors of the recent MMWR influenza vaccine effectiveness report, sent me an email response to my posts discussing how and why they measure influenza vaccine effectiveness the way they do. I thought that in the interest of fairness, I should post his full email, rather than pasting his response into a largely hidden comment section. I will likely post a follow-up to this at some point. Additionally, I want to thank Dr. Jackson publicly for responding in this fashion, both professionally and academically. The intent of my posts was academic, and I am pleased that he responded the way he did.

Dear Dr. Perencevich,

I am one of the co-authors on the MMWR article on influenza vaccine effectiveness, and I read your blog posts about that article. I believe I can clear up some of your questions. I tried posting this as a comment on the blog, but the website wouldn't let me, so my apologies for e-mailing you instead. Feel free to post this as comment on the website if you are able.

 (1) Regarding your first point, this study used what is known as a “test-negative” design. In the test-negative design, we enroll patients with a medically attended acute respiratory illness (MAARI). We then test these enrollees for influenza, and assess who was previously vaccinated and who was not. The test-negative design is based on an assumption that the rate of MAARI caused by pathogens other than influenza is the same in both vaccinated and unvaccinated persons. If this assumption is true, than our test-negative subjects are representative of the population from which the influenza-positive cases came, and our study does give an estimate of how well the vaccine reduces the risk of getting sick enough to visit the doctor.

 Although the paper refers to cases and controls, this is not a true case-control study, since a true case-control study requires that we know who is a case and who is not before we sample them. The design is closer to the “indirect cohort” method proposed by Claire Broome for studying pneumococcal vaccine effectiveness [NEJM 1980; 303:549-52]. The real advantage of the test-negative design is that it controls for differences in healthcare-seeking behavior. If we did the full cohort study you proposed, there would be variation among the cohort members in how often they seek healthcare, and these variations would be related both to their likelihood of being vaccinated and to their likelihood of going to the doctor if they got influenza. By only sampling people who come to the doctor, we control for those differences.

(2) Regarding your second point and third points, the relative risk (RR) is not an appropriate measure of association for this study design. The RR is (obviously) a measure of risk, which would be based on the cumulative incidence of disease in some defined cohort. In this study, we do not sample the full cohort; we simply use the influenza negative subjects to estimate the frequency of vaccination in the cohort. Using the RR in this setting would give a biased estimate of vaccine effectiveness, which is seen in the sample calculations you provided.

Sampling in a test-negative design is conceptually similar to incidence density sampling in a case-control study. When using incidence density sampling, the exposure odds ratio is a direct estimate of the incidence rate ratio and not an approximation to the RR. 

(3) Finally, regarding your final question about including the flu B cases in the estimate of VE against flu A: As mentioned above, the test-negative design assumes that the rate of non-flu MAARI is the same in vaccinated and unvaccinated persons. If we included flu B in the non-case group, we would be violating this assumption, because the vaccine does protect against B, and the rate of non-flu A MAARI would no longer be the same in vaccinated and unvaccinated persons.

 I hope this clears up your questions!
~Mike Jackson, Group Health Research Institute