Pushing the Needle on Influenza Vaccination

Despite continued debates about the use of influenza vaccination mandates in healthcare settings (see prior discussions just on this blog here, here, here, here, and here), facilities continue to move toward implementing some form of ‘mandatory’ program to ensure sustained high levels of influenza vaccination coverage among their staff.  A new article published in JAMA Network Open documents this increase with an update to a multi-year survey project asking about facility infection prevention practices.  I use the word ‘mandatory’ in quotes above on purpose because, as I detailed in an accompanying editorial, the definition of a mandate, when it comes to vaccination policy, is not standardized.

“…Most importantly, it does not appear that mandate was defined. Among respondents who reported having a vaccination mandate, only 74% reported having penalties for noncompliance and 13% allowed declination without a specified reason. Of those reporting no mandate, 21% reported penalties for noncompliance with hospital policy on influenza vaccination and 41% reported requirements for wearing masks if unvaccinated. An article in a bioethics journal⁵ offers the following criteria for using the term mandate in this setting: limiting acceptable reasons for refusal, penalizing nonparticipation, and enforcing these expectations. By these criteria, it is not clear how many programs described in this survey should appropriately be referred to as mandatory—the number may be higher or lower than that reported, although an increase over time seems likely.”

The authors of the survey article also note that the VA is moving to a mandatory vaccine or mask policy this year, which will again increase the number of facilities using some type of mandate.  Hopefully, the VHA will take advantage of their more comprehensive healthcare delivery system to evaluate the impact of the program on both inpatient AND outpatient influenza among their patients, something that has been a persistent gap in prior reports.

ALSO, did you appreciate how easy it was to click the link and access the whole article?  Note that the article and the accompanying editorial are in JAMA Network Open, a new, fully open access journal “in which all content is made freely available to all readers immediately on publication. ….[they] will publish online only, every Friday.” Read more here.

New evidence supports high-dose influenza vaccines

People older than 65 years are at particularly high risk for influenza-related medical complications including hospitalizations and death. In 2009, the FDA approved a trivalent inactivated vaccine with four-times the hemagglutinin antigen per strain, which was thought to improve immune response in seniors.

Background data has largely supported high-dose vaccination among seniors. In a multicenter, randomized controlled trial of high vs standard dose vaccine that included almost 32,000 patients during 2011/12 and 2012/13, 1.4% of high-dose and 1.9% standard-dose patients had an influenza-confirmed influenza-like illness, resulting in a relative efficacy of 24%. Adverse events were slightly, but significantly lower in the high-dose group but 3 high-dose recipients had serious vaccine-related events (which all resolved) vs none in the standard-dose group. A very large Medicare study during 2012/13 and 2013/14 reported similar benefits but only during 2012/13 when H3N2 was more common. Perhaps it is difficult to measure a benefit during more mild, H1N1 seasons? There have been other studies supporting the effectiveness and cost-effectiveness (at least during the 2011/12 and 2012/13 H3N2 seasons) of high-dose vaccine.

One of the larger groups of seniors in the US are patients in the Veterans Health Administration (VHA) system, so it makes sense to measure the benefits of high-dose vaccine using the VHA integrated EMR. In the June 1st JID, authors reported results of a large (industry-funded) retrospective cohort study completed using data from the 2015/16 influenza season (an H1N1 year) that included seniors with at least one inpatient or outpatient visit during the prior year (2014/15). The primary outcome was any hospitalization for pneumonia or influenza. The study used a number of nice methods to adjust for confounding including matching on baseline characteristics and the Care Assessment Need (CAN) score, that is a proxy for frailty. They also adjusted for residual confounding using the prior event rate ratio (PERR) method, which you can read more about here. Basically, PERR adjusts for outcome rates in the baseline period (before vaccination) by dividing the relative rate post-vaccination by the relative rate pre-vaccination (in the baseline period).

The final cohort (before matching) included 104,965 standard-dose and 125,776 high-dose recipients during the 2015/16  influenza season. The matched cohort had 49,091 standard-dose and 24,682  high-dose patients. Using the unmatched and matched cohorts, and using the PERR method with each, the relative vaccine effectiveness of high-dose influenza vaccine was 23% and 25%, respectively. This suggests that high-dose vaccine was effective in preventing influenza or pneumonia-associated hospitalizations among VHA patients.

These results are encouraging since they were from a more mild H1N1 season. Even more encouraging, the authors plan to automate the data extraction process and report vaccine effectiveness within 3 months of the end of each influenza season. But one note of caution, having a high-dose vaccine that is 25% more effective isn't a huge improvement, since influenza vaccines in general aren't very effective. So high-dose influenza vaccine is a small step in the right direction - but more research and new influenza vaccines are needed.

Reporting bias: Missing the point of HCP influenza vaccine mandates

We invited our good friends Hilary Babcock and Tom Talbot, distinguished epidemiologists and co-authors on the SHEA statement regarding mandatory influenza vaccination of healthcare personnel (HCP), to respond to our previous posts on this topic.  Thanks, Tom and Hilary!

Disclaimer: This commentary solely represents the opinions of the authors and does not represent an official statement from SHEA

Nothing seems to ignite the fires of the Controversies blog like a few key infection prevention topics: CAUTI as an HAI metric, bare below the elbows, and the topic of a recent blog post, mandatory HCP influenza vaccination and the SHEA 2010 Position Paper. As authors on the 2005 and 2010 SHEA papers, we provide a different perspective on the issue.

A key misconception of opponents of mandatory influenza vaccination programs is the claim that the 4 cluster RCTs referenced in the recent post are the only evidence underpinning the position of SHEA (and the numerous other professional societies also endorsing such policies). The 2005 SHEA paper has 100 references while the 2010 paper has 63, a majority of which are peer-reviewed publications in the medical literature. The 4 RCTs noted are far from the only “papers on which SHEA based its recommendation,” as Dr. Edmond states and the De Serres paper implies.

These studies are not perfect by a long shot and the challenges of accurately studying the impact of HCP vaccination on patient outcomes have been nicely highlighted in analyses of these trials, of which there are several – the De Serres paper highlighted in the blog, a CDC analysis that came to different conclusions (and surprisingly was never featured as a blog post), and three separate Cochrane analyses (are there not enough topics out there for them to review??). We also encourage readers to closely review the detailed editorial that accompanied the De Serres paper for an excellent response to the many assumptions in their analysis. If only other infection prevention proposals were scrutinized as heavily as these 4 studies (cough, cough, we’re looking at you bare below the elbows . . . ). Of note, the limitations of these 4 trials were noted in the 2010 SHEA paper, which also cites the first Cochrane analysis in that discussion (despite claims to the counter).

What is missed in the arguments against mandatory programs (including the recent blog post) is the biologic rationale and additional supporting evidence for this strategy as part of a comprehensive infection prevention program. We refer readers to the 2005 and 2010 papers for more detail but summarize briefly here:

1. HCP (like our patients) can become infected with influenza.
2. Persons infected with influenza may not present with classical ILI symptoms. This is often missed in criticisms of vaccine effectiveness. Babcock et al demonstrated how poorly the ILI definition captures hospitalized adults with laboratory-confirmed influenza. Thus studies that look just at vaccine impact on ILI will likely miss true influenza outcomes, while also capturing infections due to other viruses not covered by influenza vaccination. Since clinical testing is usually prompted by stereotypical ILI symptoms, lab-confirmed influenza outcomes are also likely under captured. In addition, since hospital length of stay is shorter and most facilities do not have post-discharge surveillance for influenza, the impact in acute care facilities is more challenging to assess than in long term care settings. 
3. Persons infected with influenza can shed virus even with minimal or no symptoms. While not to the same degree as a coughing, febrile person, the role of asymptomatic infection has been noted in numerous studies of households and experimental challenges. A 6-year study from Hong Kong of a cohort of 824 households with an identified 224 cases of secondary influenza infection examined the relationship between symptoms and viral shedding (as detected on nasal and throat swabs). Shedding was detected before onset of respiratory symptoms in influenza A-infected persons but peaked on the first 2 days of clinical illness, while influenza B shedding peaked up to 2 days prior to symptom onset. So relying on HCP to stay home when ill (which they don’t anyway, see below) will not protect patients. 
4. HCP work while ill. Sadly, this is a huge issue, as nicely noted in several posts on this blog. Studies consistently note ~75% of HCP with febrile ILI admit to working while ill, a startling yet unsurprising fact that does not capture those with atypical, mild, or even asymptomatic infection. We completely agree that this is a major infection prevention issue. The SHEA 2010 paper notes the importance of “restriction of ill HCP from working in the facility” as part of a “comprehensive infection control program” to prevent healthcare-associated influenza (and other respiratory infections). We definitely support a stronger stance on the infection risk of HCP working while ill and the various disincentives for staying at home (e.g. leave policies where sick days and vacations days are in one lump “bucket”). Perhaps we need a new chapter of the Compendium focused on the prevention of healthcare-associated respiratory infections?
5. HCP have contact with patients at higher risk for complications from influenza than the general public. The privilege of that close relationship carries an obligation to do all we can to protect those patients. 
6. Many patients won’t be adequately protected by receiving the vaccine themselves. Proponents of mandatory vaccination frequently note the moderate effectiveness of the vaccine, and we completely agree on the need for a better vaccine. The suboptimal effectiveness only emphasizes the need to optimize immunity among those who are more likely to respond in order to prevent transmission of influenza in healthcare settings (to protect the “herd”). Most HCP are healthy and therefore more likely to have a robust immune response to vaccine than already ill patients, many of whom are elderly and/or immunosuppressed. 
7. Most agree that HCP should be vaccinated against influenza, though they may disagree with a ‘mandate.’ Extensive literature now demonstrates that a mandate is the most effective way to increase HCP vaccination rates. If it is an outcome (HCP influenza vaccination) that we all support, should we not encourage its use through the most effective method for high vaccination rates? 

Fortunately, as more institutions have employed a mandatory program, new evidence that further supports the need for HCP immunization that was not available when we wrote the 2010 paper has emerged:

• Researchers at the Denver Health Medical Center reported a decrease in employee absences during the influenza season following implementation of their mandatory program when compared to prior seasons of similar influenza activity. 
• In an analysis of the province-wide vaccination with masking policy in British Columbia, researchers noted a significantly reduced rate of HCP absenteeism due to all-cause illness in vaccinated vs. unvaccinated HCP during the first season of the policy. 

Even more important than the impact on HCP illness is the impact on patient outcomes:

• MD Anderson Cancer Center implemented a mandatory vaccine with masking policy and examined the impact of increasing HCP influenza immunization over the course of 8 years. The proportion of influenza infections that were healthcare-associated among patients significantly decreased and was significantly associated with increased HCP vaccination rates. 
• A cluster randomized trial in the Netherlands of HCP at six medical centers, where the intervention arms offered vaccination to HCP vs. no vaccination at control facilities, noted a significantly lower rate of healthcare-associated influenza among internal medicine patients at the facilities with the higher rates of HCP influenza vaccination (3.9% vs. 9.7% of patients). 
• In a study encompassing 7 influenza seasons and over 62,000 hospitalized patients, a significant association was noted between increasing influenza vaccine coverage among HCP and decreasing healthcare-associated ILI among patients at an Italian acute care hospital.
• Finally, a nested case-control study in France noted a significant association between lower rates of laboratory-confirmed healthcare-associated influenza among patients and higher vaccination rates among HCP.

We don’t have time to go into the ethical arguments for HCP vaccination or the need to broaden these programs to include all recommended immunizations for HCP, but we close with a noteworthy pronouncement made by the Board of the National Patient Safety Foundation’s Lucian Leape Institute: there are two “must do’s” for HCP to ensure patient safety, hand washing and HCP influenza vaccination. 

Time to stop re-analyzing those 4 poor cluster RCTs – that horse has been beaten to death.

The almighty influenza vaccine

A recent study in Clinical Infectious Disease that analyzed the effectiveness of the influenza vaccine for the 2014-15 season was sent to me by a colleague. Wow. Overall effectiveness (for influenza A and B combined) was a whopping 19%, but for influenza A was 6%. Honestly, placebo is more effective than that. For the 2015-16 season, overall effectiveness was 47%, and 55% for influenza A.

CDC used to cite that the flu vaccine was 70-90% effective, but more recently they have revised that significantly. I was quite surprised when I looked at the CDC website today and I made the graph below from their data.

In 12 consecutive flu seasons, effectiveness hit 60% just once. If you average those 12 seasons, the effectiveness was 41%. We are sorely in need of a better vaccine. The CDC analysis begs many questions: Should hospitals make this weakly effective vaccine a condition of employment? Should SHEA take another look at its guideline? Does anyone still believe that we should fire healthcare workers that are not vaccinated with a vaccine that provides such poor protection? How many hospitals fire employees who come to work sick with influenza? Would you rather be hospitalized at a hospital with a mandatory flu vaccine policy or a hospital that makes a serious attempt to minimize presenteeism?

Mandatory Influenza Vaccination for Healthcare Workers: Agreeing to Agree

This is a guest post from Sanjay Saint, MD, MPH, the George Dock Professor of Internal Medicine at the University of Michigan, the Director of the VA/University of Michigan Patient Safety Enhancement Program and the Chief of Medicine at the Ann Arbor VA Medical Center.

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I begin by thanking my friend and colleague, Dr. Eli Perencevich, for allowing me use of “Controversies in Hospital Infection Prevention” for my first blog post. 

Our recent editorial in The Wall Street Journal on mandatory flu vaccination for healthcare workers elicited strong opinions, especially on social media. The impetus for our editorial was a recent paper published in Infection Control and Hospital Epidemiology in which we found through a national survey of lead infection preventionists that 42.7% of nonfederal hospitals had a policy mandating flu vaccinations for healthcare workers while only 1.3% of VA hospitals did.

In his 22 December 2015 blog post, Eli clarified his position by writing that he is “in favor of mandating influenza vaccination of healthcare workers (for now)”. I am in agreement. While the data supporting mandatory healthcare worker flu vaccination is perhaps not as robust as researchers would like – when is it? – in my opinion, it is compelling enough to move forward unless new data emerge that reveal the mandate to be unnecessary or ineffective.

What are the most compelling studies supporting mandatory vaccinations?

The first is a systematic review from Faruque Ahmed, PhD -- a senior scientist in the National Center for Immunization and Respiratory Diseases at the Centers for Disease Control and Prevention (CDC) – and four other CDC researchers.  I paste below the Results and Conclusions from their abstract:

Results. We identified 4 cluster randomized trials and 4 observational studies conducted in long-term care or hospital settings. Pooled risk ratios across trials for all-cause mortality and influenza-like illness were 0.71 (95% confidence interval [CI], .59–.85) and 0.58 (95% CI, .46–.73), respectively; pooled estimates for all-cause hospitalization and laboratory-confirmed influenza were not statistically significant. The cohort and case-control studies indicated significant protective associations for influenza-like illness and laboratory-confirmed influenza. No studies reported harms to patients. Using GRADE, the quality of the evidence for the effect of HCP vaccination on mortality and influenza cases in patients was moderate and low, respectively. The evidence quality for the effect of HCP vaccination on patient hospitalization was low. The overall evidence quality was moderate.

Conclusions. The quality of evidence is higher for mortality than for other outcomes. HCP influenza vaccination can enhance patient safety.

How could influenza vaccination affect all-cause mortality? I am not sure but previous studies have found influenza vaccination reduces cardiovascular events and venous thromboembolism.  How vaccination may affect these outcomes is not known - but it isn't irrational to also include all-cause mortality as an outcome given the myriad benefits of influenza vaccination.

The second study (not included in the aforementioned systematic review, but mentioned in the postscript), is a cluster randomized trial of hospitalized patients in the Netherlands published in June 2013. I paste the abstract below:

Nosocomial influenza is a large burden in hospitals. Despite recommendations from the World Health Organization to vaccinate healthcare workers against influenza, vaccine uptake remains low in most European countries. We performed a pragmatic cluster randomised controlled trial in order to assess the effects of implementing a multi-faceted influenza immunisation programme on vaccine coverage in hospital healthcare workers (HCWs) and on in-patient morbidity. We included hospital HCWs of three intervention and three control University Medical Centers (UMCs), and 3,367 patients. An implementation programme was offered to the intervention UMCs to assess the effects on both vaccine uptake among hospital staff and patient morbidity. In 2009/10, the coverage of seasonal, the first and second dose of pandemic influenza vaccine as well as seasonal vaccine in 2010/11 was higher in intervention UMCs than control UMCs; all p<0 .05="" span=""> At the internal medicine departments of the intervention group with higher vaccine coverage compared to the control group, nosocomial influenza and/or pneumonia was recorded in 3.9% and 9.7% of patients of intervention and control UMCs, respectively (p=0.015). Though potential bias could not be completely ruled out, an increase in vaccine coverage was associated with decreased patient in-hospital morbidity from influenza and/or pneumonia.

A third study (from another group in the Netherlands) used decision-analytic modeling to estimate the effects of healthcare worker influenza vaccination in the hospital setting.  The abstract is below:

Nowadays health care worker (HCW) vaccination is widely recommended. Although the benefits of this strategy have been demonstrated in long-term care settings, no studies have been performed in regular hospital departments. We adapt a previously developed model of influenza transmission in a long-term care nursing home department to study the effects of HCW vaccination in hospital wards. We study both the effectiveness and efficiency in reducing the hazard rates of influenza virus infection for patients. Most scenarios under study show a similar or higher impact of hospital HCW vaccination than has been predicted for the long-term care nursing home department. Therefore, it seems justified to extend the recommendations for HCW vaccination, based on results in the long-term care setting, to short-term care settings as well.

Eli recently wrote: “There is no data supporting the benefits of healthcare worker vaccination in acute care hospital settings…We are basing acute-care hospital policy on one observational study.” I would thus modify this by stating we are basing acute-care hospital policy on a cluster randomized trial done in a hospital setting, an observational study performed in a hospital setting, a decision analytic model explicitly focusing on an acute-care setting, and 4 randomized studies from long-term care settings as part of a well-done systematic review.

While the opinion of professional societies is not always correct, I am impressed by the strong support in the scientific community for mandatory influenza vaccination for healthcare workers.  The list of societies that support mandatory influenza vaccination for healthcare personnel includes: American Academy of Family Physicians, American Academy of Pediatrics, American College of Physicians, American Hospital Association, American Public Health Association, Association for Professionals in Infection Control and Epidemiology, Infectious Diseases Society of America, National Patient Safety Foundation, and Society for Healthcare Epidemiology for America.

Finally, is mandating flu vaccination for healthcare workers ethical? For guidance I turn to Arthur L. Caplan, PhD, one of the country’s foremost medical ethicists and whose opinion about white coats was highlighted on this blog. Writing in 2013, Professor Caplan states:

“The moral case for limiting health care workers' choice concerning influenza vaccination rests on 4 principles: the professional duty to put patients' interests first, the obligation to do no harm, the requirement to protect those who cannot protect themselves, and the obligation to set a good example for the public. It is hard to see how the invocation of personal liberty claimed by some health care workers who oppose mandates could overcome this powerful “four-legged” moral case in support of an influenza vaccination mandate…Mandating vaccination is consistent with professional ethics; benefits many, some of whom must rely on health care workers to protect them; and sets an example that permits honest engagement with the public in educating them to do the right thing about all recommended vaccines.”

Festivus Grievances: Are Mandatory Influenza Vaccination Policies and Banning White Coat Ceremonies Ethically Equivalent?

"Welcome, new comers. The tradition of Festivus begins with the airing of grievances. I got a lot of problems with you people! And now you're gonna hear about it!"  - Frank Costanza

BB8 is for BBE

(Warning: Mild Star Wars spoiler at the end, although I surveyed folks here and no one complained)

Outside my recent posts on influenza vaccine mandates, I have very few infection control grievances to air this year. To start, 2015 saw the return of original science to the annual SHEA spring meeting, a tradition that will continue in the May 2016 meeting chaired by Silvia Munoz-Price and Tom Talbot. And the year ended with NIH planning to spend $461 million in FY 2016 on antimicrobial resistance research, an increase of $100 million over FY 2015. On a personal note, University of Iowa was selected as one of CDC's new Prevention Epicenters. Our team is honored and excited to join the other 5 new centers for the kick-off meeting this January. Thus, things are truly looking up in our fight against antimicrobial resistant bacteria. If we can convince congress, NIH and CDC to continue to gradually increase research funding over the next decade, we should have many things to celebrate in 2025. That is, if we can fix the ID fellowship match and the reimbursement issues that have plagued us the past 10+ years.

...but back to influenza vaccine mandates. Several folks have wondered how we bloggers could support banning white coats and at the same time question influenza vaccine mandates, especially since both interventions have similar levels of evidence (i.e. biological plausibility, math models, observational data, limited RCT data). This is an interesting question. Just to clarify, Mike is against compulsory influenza vaccine policies and I grudgingly support them and neither of us wants to ban white coats - we favor voluntary policies that make it OK not to wear a white coat - which is exactly what Mike instituted at VCU and plans here at Iowa, starting in 2016.

Yet ignoring our policy stances, the assertion that bare below elbow policies are somehow equivalent to vaccine mandates from an ethical standpoint is incorrect. Let's consider the current situation in the US with white coat ceremonies and the pressure that medical students, housestaff and faculty are under to wear white coats. If white coats are harmful (and many would agree that it is equally likely that white coats harm patients as influenza vaccines protects patients), then the current situation would be the ethical equivalent of forcing healthcare workers to not get vaccine.

That is, white coat ceremonies force healthcare workers to cause harm to their patients, which is not morally or ethically the same as requesting healthcare workers to help protect themselves and their patients by receiving an influenza shot. In a Star Wars context, forcing FN-2187 to murder villagers on Jakku (wearing white coats) is not ethically equivalent to requesting that Finn defend the people of Takodana from a First Order attack (influenza vaccine). 

Forcing healthcare workers to wear white coats that they deem to be harmful is wrong. We need to eliminate white coat ceremonies and stop coercing healthcare workers into wearing white coats.

Root causes underlying the emergence of influenza vaccine mandates

Those that follow me on twitter or the blog have probably noticed my recent focus on trying to understand the emergence of compulsory influenza vaccination of healthcare workers. Before moving on from this topic, I wanted to share what I've learned in the process.

(1) There doesn't appear to be any estimate of the burden of nosocomial influenza in the US. We know healthcare-associated influenza does occur, but we don't have estimates for the proportion of influenza cases that occur in hospitals. Even if we did know the incidence, we don't have reliable estimates for what proportion is acquired from healthcare workers vs. visitors or family members. It seems like we'd need those numbers before pushing for a mandate.

(2) There is no data supporting the benefits of healthcare worker vaccination in acute care hospital settings. If we look at the CDC systematic review everyone quotes, there were only 4 randomized trials and all 4 were from long-term care settings. If we generously include the observational studies, 3 were from long-term care and only one was from a hospital setting. We are basing acute-care hospital policy on one observational study.

(3) Again from the CDC systematic review, "HCP vaccination rates ranged from 48% to 70% in the intervention arms and 5% to 32% in the control arms." Thus, there is no evidence that raising vaccination above 48% or 70% is beneficial in long-term care settings. Thus, if we have vaccination rates near 50%, do we need a mandate?

The last two things I learned are that none of the above matters. Science is not what is driving the push for mandates, unless you consider the studies showing mandates raise influenza vaccination rates among healthcare workers. Probably didn't need a study to show that.

(4) Yesterday, I wrote a post trying to bias the respondents of a twitter survey in favor of being cared for by a masked unvaccinated healthcare worker over a vaccinated one. As you can see by the results (below), despite my efforts, the large majority want their healthcare worker to be vaccinated. This is critical - despite the science, we just want people to be vaccinated. A huge driver behind influenza vaccine mandates must be this desire. Additionally, it's likely that masks are viewed negatively by patients. Vaccine mandates make folks feel safe and masks don't - very patient centered.

(5) The finally bit that occurred to me is that the reason vaccine mandates exist is because CMS and other governing bodies require hospitals to collect and report influenza vaccine coverage among their workers. There is also a target of 90% coverage that must be met. Thus, we have a QI target that exists despite minimal scientific evidence that it protects patients but we have to meet the target. And the only way to meet such an arbitrary target is through mandates. QED

Influenza Vaccine Mandate Math

Last week, I described five steps individual hospitals, systems and society should take when implementing compulsory influenza vaccination of healthcare workers. One component of many influenza vaccine policies is mandatory surgical masks for healthcare workers who refuse or otherwise cannot receive the vaccine. Does masking unvaccinated healthcare workers even make sense? Or rather, who is more likely to spread influenza in hospitals - an unmasked, vaccinated healthcare worker or an unvaccinated, masked healthcare worker? Let's look at the numbers.

Let's assume influenza vaccine is 50% effective. In 2014-15, overall effectiveness was 19% while in 2012-13 and 2013-14 it was 49% and 51%, respectively. I'll give the vaccine a mulligan last year since during the prior decade, vaccines were far more effective. Let's further assume with vaccine mandates, 90% of healthcare workers receive the vaccine and 10% do not.

If 90% receive a vaccine that is 50% effective, we will have 45% of healthcare workers in our hospital protected and 45% unprotected. The tricky thing is that we won't know who is protected or unprotected. And what if the 45% vaccinated but non-immune healthcare workers assume they are immune and work while sick? You can imagine them saying - "I'm sick, but it's not influenza because I was vaccinated, so I'll do my ICU shift." Any mandatory vaccination policy should consider that scenario or it's possible that the mandate could make hospitals less safe. But what of the 10% required to wear masks? I suspect they'd be more likely to stay home if sick, but even if they don't they'll be wearing a mask!

Finally, if I had a choice between being cared for by a vaccinated, unmasked healthcare worker or a masked, unvaccinated healthcare worker, I'd chose the mask. That is, until we implement influenza prevention bundles that focus on presenteeism.

Note: Mike wrote a fantastic quantitative post (in 2010!!) comparing a vaccine mandate to a presenteeism reduction policy. His conclusion: "Reducing presenteeism by 1 percentage point (from 70% to 69%) would have the same impact as increasing vaccination from 70% to 98%." It's too bad not many read the blog back in 2010...

Mandatory Influenza Vaccination of Healthcare Workers: The end or just the beginning?

"Just don't let the human factor fail to be a factor at all" - Andrew Bird, Tables and Chairs

We are all in favor of protecting patients from preventable harm. No question. With that aim, the intervention du jour (in the US) is mandatory influenza vaccination of healthcare workers. SHEA, IDSA and PIDS support such a policy, yet a recent Cochrane review stated "there is no evidence that only vaccinating healthcare workers prevents laboratory-proven influenza or its complications (lower respiratory tract infection, hospitalization or death due to lower respiratory tract infection) in individuals aged 60 or over in LTCIs and thus no evidence to mandate compulsory vaccination of healthcare workers."

Yet given the inevitability of mandatory influenza vaccine policies in the US, what can we do to protect our patients from healthcare-acquired influenza and other viral illnesses since mandates would be expected to have minimal or even negative effects on nosocomial influenza transmission? To explain this further, compulsory vaccination policies are technical interventions which are relatively simple to implement. But we have seen over and over that ignoring the human equation or socio-adaptive factors behind infection prevention initiatives leads to failure. As Sanjay Saint and Sarah Krein have written eloquently in their recent book: "Our research has shown that the principle reason is the failure of the hospitals to win their staff's active support of the infection prevention initiatives. In their focus on the technical aspects of an initiative, these hospitals have give short shrift to the human aspects." (You can read my Doody review of their book at Barnes & Noble here)

What are the additional components that we need to consider when implementing an influenza vaccine mandate? Some suggestions:

1) First, acknowledge that we know the vaccine is imperfect through the develop of communication strategies that highlight the proven benefits of the influenza vaccine to the individual health care worker. Since the data supporting direct benefits to patients is more theoretical at this point, highlighting the protective effects for the individual receiving the vaccine - including reduced risks of cardiovascular outcomes could improve acceptance of the mandate.

2) Next, mandate additional components in our influenza prevention bundle, especially those highlighted in the Cochrane review which included "hand-washing, masks, early detection of influenza with nasal swabs, antivirals, quarantine, restricting visitors and asking healthcare workers with an influenza-like illness not to attend work."

3) Offer additional sick leave to healthcare workers required to receive the vaccine. Policies that include bans on presenteeism (working while sick), should be accompanied by additional paid sick leave. In this specific instance, influenza vaccine is associated with fever (especially high-dose vaccines that are associated with benefits in older adults). Providing additional sick leave shows our understanding of vaccine side-effects, demonstrates support for staying home sick and most importantly, respects the individual health care worker.

4) Include in the mandate bundle a plan to de-implement the vaccine mandate if future studies demonstrate that they're ineffective. Doing this will gain more trust with our healthcare workers, which may, counterintuitively, improve the effectiveness of the mandate.

5) Finally, fund large studies evaluating the efficacy, effectiveness and implementation (i.e. barriers) of influenza vaccine mandates in our health care systems. Funding research acknowledges that the data around vaccine mandates isn't perfect, but we are doing the best we can to protect patients now, while simultaneously validating the safety and efficacy of this policy to protect future generations of patients AND our healthcare workers.

There are many things we need to consider as we implement mandatory influenza vaccine policies. The mandate is just the beginning. We have a long road ahead before we can state convincingly that our hospitals are safe from hospital-acquired influenza.

"And how 

How I wish 

I, I had talked to them 

And I wish they fit into the plan"

-Andrew Bird, Tables and Chairs

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.

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

Part 2: Influenza Vaccine Effectiveness - The Test-Negative Control Design

Before going further, I want to highlight the purpose of yesterday's and today's post. Occasionally, it is important to question standard practice in epidemiology when something doesn't make sense to you. I've experienced this first hand 3-4 times in infectious disease epidemiology and consider it an important exercise and critically important to our field. You can read this post if you want to read more about how we've questioned the ID epidemiology dogma around control-group selection, quasi-experimental design methodology and inappropriately controlling for intermediates in the causal-pathway of outcomes studies. Of course, this doesn't prove anything in this instance but rather explains my motive.

Yesterday, I posted my initial thoughts on how the CDC calculated the preliminary influenza vaccine effectiveness for the 2012-2013. I've now had several informal discussions on the phone and in person with several vaccine experts and am starting to understand how/why they conducted the study the way they did. I'm even more convinced now that design considerations (e.g. which patients are included in the cohort) are influencing the statistical analysis, which should be separate considerations. I will explain this further below.

It appears that the current standard study design in vaccine effectiveness (VE) is called the "test-negative" control design. This design is a modified case-control design where controls are required to have been tested for influenza but have been found "test negative". This appears to be a useful design when the specificity of the diagnostic test for influenza is low (Orenstein EW 2007), which is not the case in the current MMWR report. Another reason mentioned for selecting this design is that it is thought to reduce the bias, since vaccinated individuals may be more like to seek medical care vs. unvaccinated individuals. However, this benefit would apply to any patient seen in the outpatient clinic and not necessarily require diagnostic testing for influenza. 

In favor of cohort studies over case-control or test-negative designs, is the fact that "if specificity was 100%, the cohort method VE estimate was equivalent to the true VE, regardless of test sensitivity or ARs of influenza- and non-influenza-ILIs." (Orenstein EW 2007) The Orenstein paper's stated purpose was to study the impact of sensitivity and specificity of influenza testing on VE estimates across these study designs. Any benefits for the test-negative approach appear to evaporate when using a great diagnostic test, like the rt-PCR used in the MMWR report.

From what I can tell, the Orenstein paper is frequently cited to justify the test-negative design, but given current conditions, the design doesn't seem to be as useful as it once was. I also remain unconvinced that a cohort of patients already being seen in a doctor's office can tell us anything about risk factors for "medically attended" influenza. More importantly, I'm still very concerned with how the cohort was analyzed. Even if there are very good reasons to enroll a cohort of patients who presented to a clinic in order to avoid bias from vaccinated patients presenting differentially to clinics and even if all were tested for influenza, it doesn't follow that you need to use an odds-ratio approach to measure vaccine effectiveness when the relative-risk approach is more accurate. It appears that correcting one wrong (differential medical care seeking in vaccinated vs unvaccinated) is leading to a countervailing wrong when the analysis is done incorrectly. If they had just called this a cohort of tested patients or a "tested cohort", perhaps this wouldn't have happened.

Oh, and I'm still not sure why they are excluding influenza B positive patients from their VE calculation  for influenza A. Shouldn't they have to look at each A strain separately then? Well, that's another post for another day.

How should we calculate influenza vaccine effectiveness?

You know, I probably should've just been happy with the reports that 2012-2013 influenza vaccine was 62% effective and called it a day. But this morning I read this nice report by Helen Branswell of the Canadian Press describing why vaccine-virus match isn't the only factor that impacts vaccine effectiveness and then I made the mistake of looking at the early-release CDC MMWR report more closely.  Now, I'm an ID physician epidemiologist and led the influenza response at the University of Maryland, Baltimore and UMMS during the 2009 H1N1 pandemic. Thus, I'm no stranger to reading these reports, but for some reason, today, they just didn't make sense. It occurred to me that perhaps if I'm perplexed, others might be, so I've decided to post my questions and concerns and hopefully, as I get answers, I'll post them here.

Some Background: Read the CDC MMWR report from January 11th. and focus on Table 2 (below). This table summarizes the vaccine effectiveness data for the vaccine vs. influenza A, influenza B and both.

Initial Observations: One, it appears that CDC is using a prospective cohort of 1155 sick patients who presented as outpatients for acute respiratory illness, and not a group (cohort) of all patients eligible for vaccination. Ideally, you'd want to determine the likelihood that influenza vaccine prevents clinical illness, visits to the doctor, hospital admission and mortality. The vaccine effectiveness in the MMWR report can't tell us that and I'll explain why in #1, below. Additionally, the MMWR report determines vaccine-effectiveness using a case-control method and not a cohort method. This might seem to be an esoteric point, but it could have a big influence on how effective we think a vaccine is. I will try to explain this in #2 and #3, below. Finally, I'm not sure how they decided which patients should be included in the uninfected group for their calculations. I'll explain this a bit more in #4 and show how it could bias the estimates of vaccine effectiveness.

1) Why does CDC utilize outpatient, sick controls in their estimates of vaccine efficacy?  I suspect this is an issue of expediency and cost-effectiveness. It would be more expensive to enroll 1000 patients in September and track them weekly to see if they get the vaccine and then if they develop symptoms and test them. Of course, they can't easily do randomized studies in the US or elsewhere since the vaccine is recommended for just about everybody, so randomizing to no vaccine would be unethical. Whatever the reason, selecting an entire cohort of patients, already sick enough to visit their doctor, does not tell us how effective the vaccine is in preventing illness, preventing visits to the doctor, preventing hospitalization or preventing death. The MMWR report can only tell us how effective vaccine is in preventing an influenza infection vs. another infection conditional on already being sick enough to go to the doctor's office. What does that mean for people trying to decide if they should get vaccinated?

Also, could it be that selecting this cohort biases the findings in other ways? What if vaccinated patients would be more likely to seek medical care for their symptoms? What if those that develop acute respiratory illness are different or sicker than healthy controls in a systematic way?  These could impact the measure of vaccine effectiveness.  Additionally, using outpatient, sick controls leaves out two very important groups: hospitalized patients and healthy populations that never developed an illness in the first place.  I suspect that declining funding for CDC and other groups is behind this - you get what you pay for. However, none of the reports I've read explain this limitation when reporting vaccine effectiveness. They should.

Note: I've added a second post describing a bit more why CDC selected this cohort of patients.

2) Why does the CDC measure vaccine effectiveness using odds ratios even when they have a cohort of patients?  To explain further, a case-control study would be one where they find 1000 (or any number) of influenza positive patients and then look back and see if they were vaccinated and then find another set of 1000 influenza negative controls (healthy, sick, whatever) and see if they were vaccinated. Here they identified a cohort of patients with acute respiratory illness first and then determined their influenza status and vaccine status retrospectively. Thus, this is a "retrospective" cohort study. Just because the cohort was established conditional on them having an outpatient visit for a respiratory complaint, does not invalidate that this is a cohort. This matters since they report odds ratios and not relative risks. And as a reminder, when baseline or initial risk is high, the odds ratio can over-estimate the relative risk. To find out how and why this is important read this BMJ article.

3) Did measuring vaccine effectiveness using an odds ratio (OR) method (as it appears the CDC did) vs. the relative-risk (RR) method, as normally used in cohort studies, matter? The question here is not a theoretical one, as above, but rather I'm asking if we used the exact numbers in the MMWR report but used a cohort or relative-risk method, would we get a different estimate of effectiveness?  Short answer: Yes

If we take the table showing attack rates in vaccinated vs unvaccinated for influenza A only (from Table 2 here), we get very different results based on the method used to calculate efficacy.

Using the CDC or OR method, vaccine effectiveness (VE) = (1-OR)*100 or (1-ad/bc)*100. Using that method, the calculated VE=53.4% (CDC reports 55% in their table, since they adjusted for site)

Using the RR (cohort) method, the VE = (1-RR)*100 where the RR= (a/(a+b)) / (c/(c+d)). Using that method, the calculated VE=44.1%

This is a very big difference with a 9.3% absolute reduction in effectiveness by method alone! It seems that since site level variation is not a big driver of the effectiveness, the RR approach might be more accurate. Of note, when you do the above analysis for the vaccine vs influenza A or B, the VE falls from 62% using the = OR approach to 47% using the RR approach.

*I hope someone can explain why they are analyzing cohort data using case-control methods. For more information on how I calculated these estimates, see this paper by Walter Orenstein, et al from 1985. It appears this case-control method is standard in the influenza vaccine literature.

4) Why did CDC leave the influenza B positive patients out of their calculation of the effectiveness of the vaccine versus influenza A and vice-versa? When looking at Table 2 above, one thing struck me as odd. When doing the three effectiveness calculations, they used the same control group. To me, if you don't have influenza A, you should be included in the "uninfected group" for testing the effectiveness of the vaccine against influenza A.  To see if this matters, I added in the 180 patients who were influenza B positive AND influenza A negative that the CDC left out of their calculation. Here is the new 2x2 table:

Here, if I use the CDC (case-control or odds-ratio method) I find a VE = 41% and if I use the cohort method, I find a VE = 34.4%. These results are so different from those reported in MMWR, that I'd be very interested to know why they chose to leave influenza B patients out.

OK. For influenza A, the vaccine effectiveness was reported as 55% in the MMWR report. Depending on how I calculated the vaccine effectiveness, I found that it ranged from 53.4% to 34.4%, with the more accurate estimate likely closer to 34%.  A pretty huge range, don't you think?  Perhaps these reports should calculate effectiveness in a number of different ways and provide them in a sensitivity analysis.  Better yet, we should fund prospective cohort studies that include healthy patients and measure the true effectiveness of the vaccine. Even better, a universal influenza vaccine would render this all moot, but that's in the future...

ADDENDUM:

Please see the other two posts in this thread: (1) My discussion of the test-negative design and (2) the MMWR author's explanation of why they study influenza vaccine effectiveness the way they do.

Don't be one, get one...

Rick Mercer is a Canadian comedian and political satirist - his "Talking to Americans" bits were pure genius. Recently, he was kind enough to offer up two minutes of his valuable time to convince Canadians to get the flu vaccine. I agree - this could be the best public service announcement ever.

Universal Influenza Vaccine Update: ICAAC 2012

Donna Ambrosino and Zachary Shriver (both from Visterra) discuss their monoclonal antibody approach. Wendy Keitel, originally scheduled, unfortunately missed the session.

By the way, can you tell by my last 3 posts that I wish I was at ICAAC?

Seasonal Flu Vaccine and Pandemic Severity: ICAAC 2012

Talk and discussion from Dr. Danuta Skowronski, BC Center for Disease Control, Vancouver, BC, Canada. Did receipt of seasonal flu vaccine increase the risk of pandemic virus infection?


More videos will be posted during the conference on MicrobeWorld's YouTube Channel

Helen Branswell, Canadian Press, covered this topic in an excellent article yesterday.

Odds and ends

Here are a few odds and ends that I've been mulling over--some related to infection prevention, some tangentially related, and some, well not at all.

• A new paper in the International Journal of Obesity looks to see whether response to influenza vaccine is impacted by obesity. This is important since during the H1N1 pandemic obesity was found to be a risk factor for morbidity and mortality. Interestingly, in this study of nearly 500 participants the investigators found that antibody production is not affected by BMI, but as BMI increases there is a significant decrease in antibody detected at 12 months. The implications of this paper could be huge given the increasing prevalence of obesity in the US.
• I just read Steven Berk's recently published book, Anatomy of a Kidnapping, on a quick trip to Vermont. Berk is an infectious diseases physician and medical school dean, who was kidnapped at gunpoint from his home in 2005. He writes that equanimity helped him to stay cool through the entire ordeal. Though this may have saved his life, I think it robbed some of the emotion from his prose, and I was left with little connection to what should have been a very compelling story. And if I were not on a plane without anything else to read, I would have closed the book for sure when he articulates his view that individuals should be allowed to purchase and own assault weapons.
• Coldplay's new album, Mylo Xyloto, is simply amazing. I can't quit listening to it. It's already setting records for the rate (there's a tie to epidemiology!) of digital downloads it's receiving.
• Dick Wenzel, the most famous hospital epidemiologist since Semmelweis, has in his "retirement"  published a novel and danced the tango for charity. This week he will debut in VCU's production of the musical Grease. He plays the DJ, Vince Fontaine. He still has a day job, too--this week he's attending on the Transplant ID Service.