Epi Ren’s Journal Club: Type B Influenza

With the flu being all the rage these days (because we’re smack in the middle of the flu season in the United States), I thought I’d share with you this interesting journal article published in the American Journal of Public Health in March of 2013. It is titled “The Burden of Influenza B: A Structured Literature Review”. (The full citation is at the end of this blog post.)

The authors looked at 393 peer-reviewed papers (of which 124 were deemed relevant) published between 1995 and 2010 on influenza type B. Remember, there are three types of influenza: A, B, and C. Forget about C. Type A is the one that causes pandemics and epidemics. Type B causes localized epidemics. It doesn’t cause pandemics because it is antigenically more stable than type A and also has a limited number of hosts (namely, us and seals). Well, through the review of these articles, the authors found, not surprisingly, that influenza type B shares a lot of the guilt for how miserable people get in the winter.

From the methods section: “We conducted a systematic literature search, by using MEDLINE (accessed via PubMed). We limited searches to studies of influenza B virus in humans published between 1995 and 2010 in English-language journals. This time period was chosen to include the most recent, relevant literature and to minimize variation in case definitions and testing methods.”

A big limitation that they encountered was that a lot of the epidemiology was missing from those papers. Rather than focusing on population-level burden of influenza type B, the authors of the papers that were reviewed focused on clinical cases/outcomes and subpopulations. So it was probably difficult for the authors of this paper to really get the full epidemiological picture of influenza type B. What epidemiological data they did find was based on surveillance systems. (I’m not surprised.) From that, they found that the distribution of influenza type B in the population varied from one year to the next and from one geographic location to the next. This is something that we see all the time in influenza surveillance. The extent, severity, and distribution of the flu varies because the types of populations it hits vary as well with regards to age distribution, urban vs. rural, and access to healthcare/immunization.

From the results section: “Several studies on the burden of influenza B in the general population were based on surveillance data from local reporting systems.106–115 Year to year, the frequency of influenza B fluctuated, which likely reflects changes in circulating influenza B virus activity. In the United States, Proff et al. reported the frequency of influenza B among hospitalized patients between 2004 and 2008.107 Frequency of influenza B was similar in the first 2 seasons (13.0% in 2004–2005 and 2005–2006), but jumped to 34.2% in 2007–2008. In the Netherlands, the frequency of influenza B ranged from 0% to 82.4% across the 1992−2007 seasons.108 In a similar manner, in one region of Italy, frequency of influenza B ranged from 0% in the 1999−2001 seasons to 80.0% in the 2001−2002 season.109 Other studies from Australia and Brazil reported frequency of influenza B between 2.0% and 16.1% in adult populations.112,114,115 In Cambodia, the frequency of influenza B was highly variable, increasing from no activity in the 2006−2007 season to 57.7% in 2007−2008 and down again in 2008−2009 to 34.0%.113″

Population-level effects aside, what did the authors find with regards to type B influenza and clinical severity? They found that the papers they reviewed showed that the clinical presentation (how the patient is feeling when they are seen by the provider) was different between type A and type B influenza and between age groups being studied. That is, we all experience the flu differently, and our symptoms will vary based on different factors.

The authors also found that the rate of hospitalization and the length of stay in the hospital varied by the population being studied, but it was generally somewhere close to the rates seen with influenza type A.

Again, from the results section: “The influenza B–attributable primary respiratory and circulatory hospitalization rate in the United States was a substantial 81.4 per 100 000—midway between the primary respiratory and circulatory hospitalization rates for seasonal A (H1N1) and A (H3N2) at 55.9 and 99.0 per 100 000, respectively.123″

And how deadly is influenza type B? More from the results section: “Eleven studies reported influenza-related mortality among nonpediatric populations.83,98,101,103,104,112,114,124,131–133 Thompson et al. reported an annual average of 8349 all-cause excess mortality, the preferred metric for quantifying influenza mortality as introduced by Simonsen et al.134 in the United States from 1990 to 1999, with a range from 404 in the 1993–1994 season to a high of 19 030 in the 1992–1993 season.124 From 1976–1977 to 1998–1999, 48.6% of excess all-cause deaths in children younger than 5 years were attributed to influenza B, more than estimates for either influenza A (H1N1) or A (H3N2).124″

In essence, influenza type B is deadly, just like type A, and deadlier in some populations.

The authors agree that there are some gaps in the knowledge about the impact of influenza type B when it comes to other things like its economic impact or its impact on daily living. In my opinion, based on what I have seen in influenza surveillance for the last six years, it is safe to assume that the impact is similar to type A influenza, especially in those seasons where type B is predominant, or at the time of the season (usually toward the end) when it is predominant.

From the discussion section: “Reported influenza B frequencies should be interpreted with caution. As noted previously, frequency is not synonymous with incidence. Furthermore, variability in the way influenza B was detected may have had an impact on the reported frequency, limiting the ability to compare across studies. Clinical criteria used to identify influenza patients differed by study, and case definitions were quite disparate.96 In addition, not all studies reported time from symptom onset to viral testing, but when reported this time varied on the order of days. Because timing is important in the likelihood of a positive test, variability in viral test timing further confounded attempts to summarize findings across studies. Finally, few studies examined data from the same influenza season, which itself was inconsistently defined, such that comparison of frequencies across geographies or different populations during the same season was nearly impossible.”

As I’ve explained before, the quadrivalent influenza vaccine is somewhat of a game-changer because it includes both circulating strains of type B influenza. In previous years, the type B component of the trivalent vaccine (one containing two type A and one type B strain) was a mismatch, and we saw that in the surveillance epidemiology. Those years, the number and proportion of type B influenza cases was larger than the years when the match was a good one. Even with its limitations, this paper by Glezen et al shows that, yes, type B influenza can be bad, very bad, while also warning us that we need to do a better job in collecting the knowledge we gain from studying it and distributing it to our colleagues and the public.

Full citation: W. Paul Glezen, Jordana K. Schmier, Carrie M. Kuehn, Kellie J. Ryan, and John Oxford.  The Burden of Influenza B: A Structured Literature Review. American Journal of Public Health: March 2013, Vol. 103, No. 3, pp. e43-e51.

I'm a doctoral candidate in the Doctor of Public Health program at the Johns Hopkins University Bloomberg School of Public Health. All opinions posted here are my own, of course, and they do not necessarily reflect the opinions of my school, employers, friends, family, etc. Feel free to follow me on Twitter: @EpiRen