BMC: Exploring The `Age Shift’ Of Pandemic Mortality

 

The infamous `W shaped curve’ of the 1918 pandemic clearly shows that the death rates among those in their teens, 20s, and 30s was much higher than was normally seen in previous influenza years. Those over the age of 65, however, saw a reduction in mortality during the pandemic.

 

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Seasonal influenza can strike people of any age, but exacts its greatest toll on the elderly – those over the age of 65 – whose weaker immune systems (and comorbid conditions) often render them less able to fight off the infection.

 

Exact numbers remain elusive, since influenza is only rarely cited as the primary cause of death. If a cause of death (beyond`natural causes’) is given, comorbidities like COPD, heart disease, asthma are far more likely to listed on a death certificate.

 

Still, estimates are that 90% of seasonal flu mortality occurs in those over the age of 65 (cite CDC Pink book).

 

In 2010, (see Study: Years Of Life Lost Due To 2009 Pandemic), researchers estimated the median age of death due to seasonal influenza-related illness in the United States to be 76.

 

In contrast, pandemic influenza strains, at least during the first few years after their introduction, often produce a dramatic `age shift’ downward in mortality. 

 

The CDC’s estimate of average and median age of death due to the 2009 Pandemic virus reads:

 

Based on two CDC investigations of confirmed 2009 H1N1-related deaths that occurred during the spring and fall of 2009, the average age of people in the U.S. who died from 2009 H1N1 from April to July of 2009 was 40. The median age of death for this time period was 43. From September to October of 2009, the average age of people in the U.S. who died from 2009 H1N1 was 41, and the median age was 45.

 

Admittedly, younger fatalities are more likely to be investigated, and documented, than those that occur among the elderly, but still . . . this is a significant shift.

 

And it corresponds closely to the results of the Years Of Life Lost Study mentioned above, which found the mean age of death from the novel H1N1 virus to be half that of seasonal flu, or 37.4 years.

 

In terms of years of life lost (YLL), the average pandemic flu death has a many fold greater impact than the average seasonal flu fatality.   

 

This same pattern was repeated (to greater and lesser degrees) during the 1918, 1957, and 1968 pandemics  . . .  along with the 1977 return of the H1N1 virus after an absence of 20 years.

 

All of which has led to a good deal of speculation.

 

What drives this age shift?  Why were apparently healthy, younger flu victims, with robust immune systems more likely to die from pandemic flu?

 

Although not universally accepted, one popular theory has centered around the production of a `cytokine storm’, which is believed to be the product of a robust immune system typically found in younger, healthier individuals.

 

Cytokines are a category of signaling molecules that are used extensively in cellular communication. They are often released by immune cells that have encountered a pathogen, and are designed to alert and activate other immune cells to join in the fight against the invading pathogen.

 

This cascade of immune cells rushing to the site of infection, that if it races out of control, can literally kill the patient.

 

The patient’s lungs can fill with fluid (which makes a terrific medium for a bacterial co-infection), and cells in the lungs (Type 1 & Type II Pneumocytes) can sustain severe damage.

 

You can find more on this theory in these earlier posts:

 

Study: Calming The Cytokine Storm

Cytokine Storm Warnings

The Baskin Influenza Pathogenesis Study

Pt. 1               Pt. 2            Pt. 3

 

Another theory has held that older populations are more likely to have been exposed to a similar influenza strain in the past and are more likely to carry some level of immunity to the emerging pandemic strain.

 

This was clearly the case in 1977, when the H1N1 virus – supplanted by the H2N2 virus in 1957 – made an unexpected comeback.  Those born after the virus last circulated in the mid 1950s – were the hardest hit age group.

 

Again with the 2009 H1N1 pandemic virus, those born before the early 1950s appeared to have higher levels of immunity, resulting in fewer severe outcomes among older individuals.

 

All of which serves as prelude to a research article, published yesterday in BMC Medicine, that looks at the age shift during pandemic outbreaks.

 

The age distribution of mortality due to influenza: pandemic and peri-pandemic

Tom Reichert, Gerardo Chowell and Jonathan A McCullers

Background

Pandemic influenza is said to 'shift mortality' to younger age groups; but also to spare a subpopulation of the elderly population. Does one of these effects dominate? Might this have important ramifications?

Methods

We estimated age-specific excess mortality rates for all-years for which data were available in the 20th century for Australia, Canada, France, Japan, the UK, and the USA for people older than 44 years of age. We modeled variation with age, and standardized estimates to allow direct comparison across age groups and countries. Attack rate data for four pandemics were assembled.

Results

For nearly all seasons, an exponential model characterized mortality data extremely well; For seasons of emergence and a variable number of seasons following, however, a subpopulation above a threshold age invariably enjoyed reduced mortality. 'Immune escape', a stepwise increase in mortality among the oldest elderly, was observed a number of seasons after both the A(H2N2) and A(H3N2) pandemics. The number of seasons from emergence to escape varied by country. For the latter pandemic, mortality rates in four countries increased for younger age groups but only in the season following that of emergence. Adaptation to both emergent viruses was apparent as a progressive decrease in mortality rates, which, with two exceptions, was seen only in younger age groups. Pandemic attack rate variation with age was estimated to be similar across four pandemics with very different mortality impact.

Conclusions

In all influenza pandemics of the 20th century, emergent viruses resembled those that had circulated previously within the lifespan of then-living people. Such individuals were relatively immune to the emergent strain, but this immunity waned with mutation of the emergent virus. An immune subpopulation complicates and may invalidate vaccine trials. Pandemic influenza does not 'shift' mortality to younger age groups; rather, the mortality level is reset by the virulence of the emerging virus and is moderated by immunity of past experience. In this study, we found that after immune escape, older age groups showed no further mortality reduction, despite their being the principal target of conventional influenza vaccines. Vaccines incorporating variants of pandemic viruses seem to provide little benefit to those previously immune. If attack rates truly are similar across pandemics, it must be the case that immunity to the pandemic virus does not prevent infection, but only mitigates the consequences.

The complete article is available as a provisional PDF.

 

The entire article is worthy of your attention, and the authors delve into a good many areas, including future pandemic mitigation planning, and vaccine strategies. 

 

But essentially the authors propose that all recent influenza pandemics (over the past century) have involved `recycled’ flu strains to which some portion of the population had previously been exposed to.

 

They conclude:

Pandemics do not ‘shift’ mortality to younger ages

From this study, it is evident that pandemics do not ‘shift’ mortality to younger ages. Rather, the
entire mortality level is simply reset to the virulence level of the emergent virus. This reset is accompanied by immunoprotection in older age groups, which is determined by their level of previous experience with viruses similar to that emerging. 

 

In other words, were older populations not carrying some vestiges of immunity from previously flu encounters, these researchers suggest they would suffer the same levels (or higher) of mortality and morbidity as do younger populations.

 

The authors also point out that initial levels of immunity to emerging (or more properly, re-emerging) influenza viruses in older populations tends to wane in subsequent seasons, leading to what they call Immune Escape: `a stepwise increase in mortality among the oldest elderly’.

 

Does this blow the whole cytokine storm theory out of the water?

 

Not necessarily, although it does call into question just how much of an impact it has on the perceived `age shift’ in pandemic flu cases.

 

These two theories need not be mutually exclusive, however, and so I wouldn’t rule out the possibility that both may play a part in driving pandemic mortality demographics.

»» Read More

H5N1 Seroprevalence Among Jiangsu Province Poultry Workers

 

Study location Jiangsu Province – Credit Wikipedia

 

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We’ve a new study that adds incrementally to our knowledge base on human infection by the H5N1 bird flu virus that appeared in BMC Infectious Diseases yesterday. The results of which, I suspect, will end up being used by both sides of the The Great CFR Divide.

 

 

Researchers interviewed and took blood samples from 306 poultry workers from three counties in Jiangsu Province, China between July 1st and August 15th, 2010. None of the workers reported serious respiratory illness in the past, and all dealt with un-vaccinated poultry on routine basis.

 

The open access study may be viewed at:

 

Seroprevalence of avian influenza A (H5N1) virus among poultry workers in Jiangsu Province, China: an observational study

Xiang Huo, Rongqiang Zu, Xian Qi, Yuanfang Qin, Liang Li, Fenyang Tang, Zhibin Hu and Fengcai Zhu

BMC Infectious Diseases 2012, 12:93 doi:10.1186/1471-2334-12-93

Published: 18 April 2012

Abstract (provisional)

Background

Since 2003 to 06 Jan 2012, the number of laboratory confirmed human cases of infection with avian influenza in China was 41 and 27 were fatal. However, the official estimate of the H5N1 case-fatality rate has been described by some as an over estimation since there may be numerous undetected asymptomatic/mild cases of H5N1 infection. This study was conducted to better understand the real infection rate and evaluate the potential risk factors for the zoonotic spread of H5N1 viruses to humans.

Methods

A seroepidemiological survey was conducted in poultry workers, a group expected to have the highest level of exposure to H5N1-infected birds, from 3 counties with habitat lakes of wildfowl in Jiangsu province, China. Serum specimens were collected from 306 participants for H5N1 serological test. All participants were interviewed to collect information about poultry exposures.

Results

The overall seropositive rate was 2.61% for H5N1 antibodies. The poultry number was found associated with a 2.39-fold significantly increased subclinical infection risk after adjusted with age and gender.

Conclusions

Avian-to -human transmission of avian H5N1 virus remained low. Workers associated with raising larger poultry flocks have a higher risk on seroconversion.

 

 

 

The researchers used two different H5N1 reference antigen strains for the seroprevalence analysis; one from 2010 A/Hubei/1/10 (clade 2.3.2)  and an older one from 2005 A/Anhui/1/05 (clade 2.3.4).

 

While the total seropositive rate was 2.61% (95%CI, 1.14%–5.09%), it turned out that none of the blood samples tested positive for the newer (A/Hubei/1/10) strain.

 

Only antibodies to the older A/Anhui/1/05 strain were detected.

 

And of the three locations tested (Gaochun, Jianhu and Gaoyou counties) the percentage of workers testing positive ranged from zero (Gaochun) to 5.38% (95%CI, 2.19%–10.78%) in Gaoyou.

 

In their discussion, the authors state:

 

Several serological studies have been conducted to assess the transmission of H5N1 virus in poultry workers. The reported seropositive rates vary from 0 to 10% [9-11]. In the present study, the overall positive rate we found was 2.61% and in different sampling districts the rates varied from 0 to 5.38%.

 

Many factors could be responsible for the variability, such as the H5N1 infection rate and vaccination rate of the poultry, the precautions and job duties of the workers. In our study, poultry number was identified as a novel risk factor associated with human infection with avian H5N1 virus, which could be accounted for the distinction of seropositive rate among districts and studies.

<SNIP>

Conclusions

Avian-to –human transmission of avian H5N1 virus remained low. Workers associated with raising larger poultry flocks have a higher risk of seropositivity.

 

 

This is a small sampling - a little over three hundred blood tests conducted across three counties in Northern China – so one must be careful in extrapolating these numbers across a wider population.

 

But the lack of seropositivity among poultry workers in Gaochun county suggests a good deal of variability, even among high risk populations.

 

Which means you can’t simply multiply the population of endemic regions by 2.61% in order to come up with a reasonable estimate of the number infected.

 

And there’s a lot we don’t know about the road to achieving seropositivity, including viral load required, mode of infection (or exposure), and differences in the pathogenicity and transmissibility of various clades of the virus.

 

Earlier this week in Differences In Virulence Between Closely Related H5N1 Strains, we looked at two closely related H5N1 strains which produced decidedly different pathogenesis in mice and ducks.

 

With at least 20 clades of the virus identified, and a good deal of genetic variation within each clade, it makes it very difficult to make any general statement about the virulence or transmissibility of the H5N1 virus.

 

Today’s study shows that low levels of H5N1 seropositivity among some poultry workers in China exists.

 

But it is neither uniform nor is it universal. 

 

It’s another data set to consider, along with the handful of other studies we’ve seen. But does not provide a definitive answer, one way or the other, on the transmissibility of the H5N1 virus.

 

For more on H5N1 seroprevalence studies, and the controversy over the Case Fatality Rate of the H5N1 virus, you may wish to revisit:

 

mBio: Mammalian-Transmissible H5N1 Influenza: Facts and Perspective

Science: Peter Palese On The CFR of H5N1

Study: Subclinical H5 & H9 Infections In Humans

The Thailand Serological Study

»» Read More

Peter Doherty On H5N1 Research

 

BSL-4 Lab Worker - Photo Credit –USAMRIID

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Laureate Professor Peter C. Doherty (who shared the 1996 Nobel Prize for medicine for his work in immunology) divides his time between St Jude Children’s Research Hospital in Memphis and the Department of Microbiology and Immunology at the University of Melbourne.

 

I’ve profiled a number of Professor Doherty’s articles in the past, including:

Prof. Peter Doherty On Influenza’s Threat

Professor Peter Doherty On Bird Flu

 

Today Professor Doherty, along with Paul Thomas, PhD. (also from St. Jude Research Center) – have published an open access opinion piece in BMC Biology.

Dangerous for ferrets: lethal for humans?

Peter C Doherty and Paul G Thomas

BMC Biology 2012, 10:10 doi:10.1186/1741-7007-10-10

 

Of concern to these authors is the idea that H5N1 research should only be conducted in BSL-4 laboratories (a rule already adopted in Canada), which would greatly restrict the number of labs – and researchers – who would have access to the virus.

 

I’ve excerpted two paragraphs below, but follow the link above to read the whole piece.

 

While we need to be assured that Taubenberger, Hultin, Fouchier, Kawaoka-type experiments are only done by responsible people working in safe, well-regulated institutions, the problem is that imposing highly restrictive constraints (BSL4 security, in space suits) means that few will be bothered to investigate these pathogens. As a consequence, we will know less about them. The reality is that if scientists want to be funded, they must be productive and publish. It is always easy for a talented researcher to say: 'too hard, too cumbersome, I'll just go on with something else.' Those reviewing the H5N1 situation might ask whether that has indeed happened with the resurrected 1918 virus.

<SNIP>

What must be avoided at all costs is to initiate processes that limit the exchange of information in the influenza field. The overwhelming probability is that any 'human pandemic' H5N1 variant will come out of nature, not a laboratory. The combination of a superbly organized network, first class technology, well-established centers and dedicated professionals means that the global monitoring mechanisms for influenza are the best there can be. The Fouchier and Kawaoka studies identify mutations that these international 'flu detectives' will be watching for. The last thing the influenza surveillance community would want is for their work to become exclusive, especially if that leads to any reluctance to make newly isolated, dangerous H5N1 'field isolates' immediately available for general scrutiny.

»» Read More

Study: Thermal Scanners & Pandemic Influenza

 

 

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A fresh study from the BMC Infectious Diseases journal on the efficacy of thermal scanners used to detect H1N1 influenza among arriving passengers at Japan’s Narita International Airport during the 2009 pandemic. 

 

As you are probably aware, many airports installed thermal scanners during the SARS outbreak of 2003 and during the pandemic of 2009, in an attempt to identify and interdict infected passengers upon arrival.

 

(Thermal Imaging in 2003)

Since fever is often a hallmark of infection, thermal imaging has been promoted as a way to protect the public and (hopefully) delay introduction of a virus into a country during a pandemic.

 

While all of this sounds reasonable, their usefulness has been the matter of considerable debate for years. 

 

The problem is, not everyone who is infected will exhibit a fever.

 

• Some may be silently incubating the virus, and will become symptomatic in another 24-48 hours
• Others may have other symptoms, but no fever
• Some may be taking antipyretics (fever reducers) to ease symptoms or evade detection
• And some may simply be asymptomatic carriers of the virus.

 

Added to these, scanners can be foiled by other factors including the consumption of hot beverages or alcohol, pregnancy, menstrual period or hormonal treatments.  All of which can increase the external skin temperature and cause a false positive.

 

Inversely, intense perspiration or heavy face make-up can have a cooling effect on the skin temperature which can cause a false negative.

 

In February of 2009, several months before the emergence of novel H1N1, I wrote about (LINK) a study that appeared in Eurosurveillance that listed these problems called:

 

International travels and fever screening during epidemics: a literature review on the effectiveness and potential use of non-contact infrared thermometers.

Euro Surveill. 2009;14(6):pii=19115.  

Bitar , A Goubar, J C Desenclos

 

In June of 2009, just as the pandemic was ramping up, I wrote  Vietnam Discovers Passengers Beating Thermal Scanners,  which looked at a Reuters report that a number of sick passengers flying into Ho Chi Minh City in Vietnam took fever reducers (Aspirin, Tylenol, etc) several hours prior to arrival in order to beat the thermal scanners.

 

In December of 2009, in Travel-Associated H1N1 Influenza in Singapore, I wrote about a NEJM Journal Watch of a new study that has been published, ahead of print, in the CDC’s  EID Journal  entitled:

 

Epidemiology of travel-associated pandemic (H1N1) 2009 infection in 116 patients, Singapore. Emerg Infect Dis 2010 Jan; [e-pub ahead of print]. Mukherjee P et al

Travel-Associated H1N1 Influenza in Singapore

Airport thermal scanners detected only 12% of travel-associated flu cases; many travelers boarded flights despite symptoms.

Travelers play a key role in spreading many infections, including influenza. Such was the case with the spread of 2009 H1N1 influenza to Singapore, a major travel hub serving 37 million air passengers annually.

<SNIP>

One quarter of patients were symptomatic when they boarded flights; 15% developed symptoms during travel. Airport thermal scanners detected only 12% of patients overall and only 40% of those with symptomatic infection on arrival.

 

And finally, last June CIDRAP carried this piece on a presentation at last year’s ICEID.

 

Thermal scanners are poor flu predictors

Thermal scanners for screening travelers do moderately well at detecting fever, but do a poor job at flagging influenza, according to researchers from New Zealand who presented their findings today at the International Conference on Emerging Infectious Diseases (ICEID) in Atlanta.

They assessed the performance of the machines from Aug 21 through Sep 12, 2008, on 1,275 passengers arriving from Australia at Christchurch International Airport. The investigators took the travelers' tympanic temperatures and obtained respiratory samples for influenza testing from 1,268 of them.

The positive predictive value for fever was 1.5% for thermal scanners and 4.1% for tympanic thermometers. For influenza, the positive predictive value for the two techniques was 2.8%. None of the 30 passengers who tested positive for influenza had a tympanic temperature of 37.8°C (100°F) or higher, and only 2 had temperatures of at least 37.5°C (99.5°F). Three were asymptomatic. The group concluded that fever is a poor predictor of influenza, which limits the efficacy of thermal screening at entry points.
Jul 13 ICEID abstracts (See Board 168)

 

 

These older less-than-encouraging findings all serve as prelude to today’s study, which finds similar limitations with the use of thermal scanners to detect influenza during a pandemic.

 

Detection rates of H1N1 were found to be just over 22% and thermal imaging sensitivity for detecting fevers ranged from just over 50% to just under 70%.

 

 

I’ve only reproduced the abstract. Follow the link to read this open access study in its entirety.

 

Fever screening during the influenza (H1N1-2009) pandemic at Narita International Airport, Japan

Hiroshi Nishiura  and Kazuko Kamiya

BMC Infectious Diseases 2011, 11:111doi:10.1186/1471-2334-11-111

Published:3 May 2011

Abstract (provisional)

Background

Entry screening tends to start with a search for febrile international passengers, and infrared thermoscanners have been employed for fever screening in Japan. We aimed to retrospectively assess the feasibility of detecting influenza cases based on fever screening as a sole measure.

Methods

Two datasets were collected at Narita International Airport during the 2009 pandemic. The first contained confirmed influenza cases (n=16) whose diagnosis took place at the airport during the early stages of the pandemic, and the second contained a selected and suspected fraction of passengers (self-reported or detected by an infrared thermoscanner; n=1,049) screened from September 2009 to January 2010. The sensitivity of fever (38.0 C) for detecting H1N1-2009 was estimated, and the diagnostic performances of the infrared thermoscanners in detecting hyperthermia at cut-off levels of 37.5 C, 38.0 C and 38.5 C were also estimated.

Results

The sensitivity of fever for detecting H1N1-2009 cases upon arrival was estimated to be 22.2% (95% confidence interval: 0, 55.6) among nine confirmed H1N1-2009 cases, and 55.6% of the H1N1-2009 cases were under antipyretic medications upon arrival. The sensitivity and specificity of the infrared thermoscanners in detecting hyperthermia ranged from 50.8-70.4% and 63.6-81.7%, respectively. The positive predictive value appeared to be as low as 37.3-68.0%.

Conclusions

The sensitivity of entry screening is a product of the sensitivity of fever for detecting influenza cases and the sensitivity of the infrared thermoscanners in detecting fever. Given the additional presence of confounding factors and unrestricted medications among passengers, reliance on fever alone is unlikely to be feasible as an entry screening measure.

 

 

Despite the aggressive use of thermal imagers, passenger interviews, and other screening methods - Japan found it impossible to prevent entry of the H1N1 virus into their country during the early days of the 2009 pandemic.

 

In Japan: Quarantine At Ports Ineffective Against Pandemic Flu  I wrote about a study that suggests between asymptomatic or mild infections, and a silent incubation period of several days, there wasn’t much chance of long-term success.

 

For every person identified, and quarantined, by port authorities  - researchers estimate 14 others infected by the virus entered undetected.

 

First a article from The Yomiuri Shimbun, followed by a link to the study which appears in Eurosurveillance.

 

Quarantine at ports found ineffective against new flu

The Yomiuri Shimbun

The number of people infected with new flu who passed undetected through airport quarantine between April last year, when the new strain of influenza began spreading, and May was about 14 times higher than the number of infected people stopped at the airports, according to a study carried out by Tokyo University.

Eurosurveillance, Volume 15, Issue 1, 07 January 2010

Rapid communications

When should we intervene to control the 2009 influenza A(H1N1) pandemic?

H Sato , H Nakada, R Yamaguchi, S Imoto, S Miyano, M Kami

 

Politically, and in terms of reassuring the public, the deployment of thermal scanners at airports and other points of entry probably has a lot of merit.   And they can provide valuable surveillance information as well.

 

Practically, as an effective way to keep an emerging virus out of a country, these studies continue to show how unlikely that outcome really is.

»» Read More

Study: Viruses With A Ticket To Ride

 

 

 

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In March of 2008 I flew from Orlando to Washington D.C. (changing planes in Atlanta) to attend an HHS sponsored Flu conference.  As this was prime cold & flu season, passengers on all 4 legs of this trip were sneezing and coughing around me.

 

And as is appropriate for returning from an influenza conference, two days later I came down with the the `flu’ (actually an Influenza-like Illness).

 

I’ve no idea exactly where I picked up this nasty viral hitchhiker. It could have been aboard the planes, or it may well have been at the conference (a lot of conversational huddles and handshaking going on), or at the hotel, or during the several hours of waiting in the airport terminals.

 

Surprisingly, during the 2009 influenza pandemic I made two similar airline trips (to Washington D.C. & Minneapolis) to flu conferences, and managed to evade illness both times.

 

Go figure.

 

Which brings us to a study that recently appeared in BMC Infectious Diseases, that looked at the incidence of ARI (Acute Respiratory Infection) presenting within 5 days of train or tram travel in the UK.

 

First a link, and some excerpts from the abstract, then some discussion on why this is interesting on several levels.

 

Is public transport a risk factor for acute respiratory infection?

BMC Infectious Diseases 2011, 11:16            doi:10.1186/1471-2334-11-16

Joy Troko, Puja Myles, Jack Gibson, Ahmed Hashim, Joanne Enstone, Susan Kingdon, Chris Packham, Shahid Amin, Andrew Hayward, Jonathan Nguyen-Van-Tam

ABSTRACT  

Background: 

The  relationship  between  public  transport  use  and  acquisition  of  acute  respiratory infection  (ARI)  is  not  well  understood  but  potentially  important  during  epidemics  and  pandemics. 

Methods:  

A  case-control  study  performed  during  the  2008/09  influenza  season.  Cases  (n=72)  consulted  a  General  Practitioner  with  ARI,  and  controls  with  another  non-respiratory acute  condition  (n=66).  Data  were  obtained  on  bus  or  tram  usage  in  the  five  days preceding illness onset (cases) or the five days before consultation (controls) alongside  demographic details. Multiple logistic regression modelling was used to investigate the  association between bus or tram use and ARI, adjusting for potential confounders. 

Results: 

Recent  bus  or  tram  use  within  five  days  of  symptom  onset  was  associated  with  an  almost  six-fold  increased  risk  of  consulting  for  ARI  (adjusted  OR=5.94  95%  CI  1.33- 26.5).

The risk of ARI appeared to be modified according to the degree of habitual bus and  tram  use,  but  this  was  not  statistically significant  (1-3  times/week:  adjusted OR=0.54 (95% CI  0.15-1.95; >3 times/week:  0.37 (95% CI 0.13-1.06).

 

Conclusions: 

We found a statistically significant association between ARI and bus or tram use in the five days before symptom onset. The risk appeared greatest among occasional bus or  tram  users,  but  this  trend  was  not  statistically  significant.  However,  these  data  are  plausible  in  relation  to  the  greater  likelihood  of  developing  protective  antibodies  to  common   respiratory   viruses   if   repeatedly   exposed.   The   findings   have   differing implications  for  the  control  of  seasonal  acute  respiratory  infections  and  for  pandemic  influenza.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

 

 

One of the difficult questions that public health officials must contend with are what precautions they should recommend to the public during an epidemic.

 

As we saw early in the 2009 pandemic, before the risks of the newly emerged H1N1 virus were well established, the CDC was quick to recommend the closing of schools when cases appeared, and a 7-day period of home isolation for infected cases.

 

Once it became apparent that the virus wasn’t as virulent as first feared - in order to reduce their impact on society - many of those recommendations were relaxed. 

 

In order to make these determinations, much depends on the type and severity of an outbreak, its rate of spread (R0), and the manner in which it is transmitted (ie. aerosolized, large droplet, fomites, orofecal route).

 

And those are factors that must be established for every novel illness.

 

Because, if you’ve seen one pandemic  .   .  . you’ve seen one pandemic.

 

The authors of this BMC study point out that the UK pandemic plan is disrupt the continuity of society as little as possible during a pandemic.

 

The  current UK National Framework  for  Pandemic  Influenza  states  that  during  a pandemic, domestic travel should continue to operate normally but users should adopt good hygiene measures, stagger journeys where possible to reduce overcrowding; and  stay at home altogether if symptomatic with pandemic influenza [1].

 

This advice reflects the need to maintain, as far as possible, business continuity and near normal functioning  of society, but acknowledges that some data exist about the transmission of influenza on  board public transport, notably commercial airliners [2].

 

Not every country is on the same page with this.

 

In Japan - prior to the 2009 pandemic outbreak - we saw a different tactic being tested; the enforced separation (by 1 to 2 meters) of passengers on public transportation (see Japan: Social Distancing Test On Commuter Trains).

 

Granted, these Japanese drills were based on an extremely virulent `bird flu’ type virus.  

 

Understanding how readily viruses may be transmitted in an enclosed environment (like a train, plane, or tram) can help pandemic planners better make crucial decisions. 

 

Interestingly, those who were frequent users of public transportation were slightly less likely to consult their GP for an ARI during this study period, than those who were only occasional users.

 

Since this study was conducted in the month of December, it is possible that more frequent users of public transportation had already been exposed to the `flu’ earlier in the season, although the authors suggest further study on this finding is warranted.

While a six-fold increase in ARI consultations among recent public transport users is compelling, these results must be accepted with caution.  

 

Among other factors: the size of this observational study was small, it was conducted in a single location (Nottingham, UK), and it was conducted during a normal flu season, not a pandemic.    

 

The authors conclude that while the use of public transport is associated with a significant individual risk for acquiring an ARI during the winter, the UK’s current pandemic policy on public transportation during an epidemic is sound.

 

The findings support current public advice to exercise good respiratory hygiene and existing pandemic guidance to refrain from making unnecessary journeys by public transport when  symptomatic.

 

The  findings  do not support the effectiveness of suspending mass urban transport systems as a pandemic countermeasure aimed at reducing or slowing population spread because, whatever the relevance of public transport is to individual-level risk, household exposure most likely  poses a greater threat [3]. 

 

 

Coincidentally, we are once again about to witness the busiest travel period of the year; Chunyun, or the Spring Festival Travel Season (of which Chinese New Years is a central part)

 

It is, quite rightfully, billed as the largest annual migration of humans on the planet. Chunyun begins about 15 days before the Lunar New Year and runs for about 40 days total.

 

This year, the Lunar New year falls on February 3rd, and with it comes a cultural ethic for millions who have moved to the big cities to return home to visit with their families for a few days.

 

During this time, it has been estimated that well over 2 billion passenger journeys are taken, mostly by bus and train, across Asia.

 

With H1N1 still making the rounds, epidemiologists will no doubt be watching to see if a post-Chunyun increase in influenza cases is observed during February across Asia.

»» Read More

Attack Of The Killer `B’s

 

 

 

For now it appears that seasonal H1N1 has been supplanted by novel H1N1, and we are left with four flu strains (novel H1N1, H3N2, and 2 B lineages) in circulation as of the fall of 2010.

 

# 5015

 

We don’t discuss Influenza B very often, because among the influenzas, B strains are regarded as less pathogenic and more stable (and less likely to spark a pandemic) than their highly mutable cousins; influenza A. 

 

And so most scientific research and attention is focused on the more unpredictable and dangerous A strains.

 

But today, we’ll make an exception because Influenza B has been in the news a little this week, including research on Influenza B and bacterial co-infections.

 

First, here is how the CDC describes influenza B.

 

Influenza Type B

Influenza B viruses are usually found only in humans. Unlike influenza A viruses, these viruses are not classified according to subtype. Influenza B viruses can cause morbidity and mortality among humans, but in general are associated with less severe epidemics than influenza A viruses. Although influenza type B viruses can cause human epidemics, they have not caused pandemics.

 

While considered less dangerous, that doesn’t make Influenza B unworthy of our attention.

 

Influenza B was first identified - almost simultaneously - by two researchers back in 1940 (Francis and Magill).  Unlike the A strains, Influenza B was discovered to remain relatively stable, usually for years at a time.

 

 

It often becomes the predominant strain late in the flu season, after influenza A has peaked.

 

 

This graphic from the CDC’s  2009 FluView shows Influenza B making up about half of all positive flu samples from week 11 to week 15.

 

There are two lineages of influenza B that currently circulate around the world (and have since the late 1980s); the Victoria and Yamagata  strain.

 

And each year scientists must decide . . . six months in advance . . .  which of these strains to include in the next seasonal flu shot.  Their record for guessing which strain will dominate has been less than stellar – missing the mark about half the time in recent years.

 

Which has sparked calls to formulate a quadrivalent flu vaccine – one that includes two A strains, and both lineages of the B strain each year (see Two Bs Or Not Two Bs?  April 2010).

 

You can find an earlier but nonetheless illuminating discussion of the advantages and problems of manufacturing a quadrivalent vaccine in this  CIDRAP  report from January of 2009 (Experts consider 4-strain flu vaccine to fight B viruses).

 

Earlier this week CIDRAP reported on Sanofi’s early testing of a quadrivalent vaccine in Sanofi reports trial results for novel flu vaccines.

 

While having a diminished pandemic potential, and producing (generally) less severe illness, influenza B is hardly benign.  It can (and does) contribute to the burden of influenza mortality and morbidity each year –  particularly among children and younger adults. 

 

The following is an account from the Journal of Infectious Diseases, Sept 1980, describing the impact of an influenza B dominated flu season.

 

 

 

Today we’ve a new example of the pathogenic potential of influenza B  which comes by way of a journal article from BMC Infectious Diseases.

 

It  looks at 3 previously healthy women (with no apparent high risk factors) who developed serious pneumonia and sepsis as a result of a co-infection with influenza B.

 

I’ve reproduced the Abstract below.  A provisional PDF of the entire article is available here.  (note the typo in the first sentence: that should read 1918)

 

Co-infection of Influenza B and Streptococci causing Severe Pneumonia and Septic Shock in Healthy Women

Timothy Aebi , Maja Weisser , Evelyne Bucher , Hans H Hirsch , Stephan Marsch  and Martin Siegemund

BMC Infectious Diseases 2010, 10:308doi:10.1186/1471-2334-10-308

Published:
27 October 2010

Abstract (provisional)

Background

Since the Influenza A pandemic in 1819, the association between the influenza virus and Streptococcus pneumoniae has been well described in literature. While a leading role has been so far attributed solely to Influenza A as the primary infective pathogen, Influenza B is generally considered to be less pathogenic with little impact on morbidity and mortality of otherwise healthy adults. This report documents the severe synergistic pathogenesis of Influenza B infection and bacterial pneumonia in previously healthy persons not belonging to a special risk population and outlines therapeutic options in this clinical setting.

Case presentation

During the seasonal influenza epidemic 2007/2008, three previously healthy women presented to our hospital with influenza-like symptoms and rapid clinical deterioration. Subsequent septic shock due to severe bilateral pneumonia necessitated intensive resuscitative measures including the use of an interventional lung assist device. Microbiological analysis identified severe dual infections of Influenza B with Streptococcus pyogenes in two cases and Streptococcus pneumoniae in one case. The patients presented with no evidence of underlying disease or other known risk factors for dual infection such as age (<one year, >65years), pregnancy or comorbidity.

Conclusion

Influenza B infection can pose a risk for severe secondary infection in previously healthy persons. As patients admitted to hospital due to severe pneumonia are rarely tested for Influenza B, the incidence of admission due to this virus might be greatly underestimated, therefore, a more aggressive search for influenza virus and empirical treatment might be warranted. While the use of an interventional lung assist device offers a potential treatment strategy for refractory respiratory acidosis in addition to protective lung ventilation, the combined empiric use of a neuraminidase-inhibitor and antibiotics in septic patients with pulmonary manifestations during an epidemic season should be considered.

 

Bacterial pneumonia is a fairly common complication of severe influenza, but up until now has usually been associated with influenza A infections. 

 

Here, researchers show that influenza B can also open the door for serious (and sometimes fatal) bacterial infections in previously healthy individuals.

 

The entire report is worth reading, particularly if you are a clinician.  

 

The authors contend that since testing for influenza B is less common than for influenza A, it may be behind more hospital admissions than we know.

 

Another example that illustrates that - despite making great strides in recent years in our understanding of influenza - that we’ve still a lot to learn.

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BMC Biology: Q&A On What’s New With H1N1

 

 

 

# 4988

 

After wading through a number of pseudo-scientific and  often misleading media reports over the weekend it is refreshing to find an overview of the (former) pandemic H1N1 virus that is devoid of unbridled hyperbole and supposition.

 

It appears in the open access journal BMC Journal  Biology, and quite capably (and mostly in layman’s language) brings us up to date on what we know about last year’s pandemic virus.

 

The article is comprised of 12 questions and answers.  Among the items covered you’ll find:

 

The World Health Organization has announced the end of the (H1N1) influenza A (H1N1) pandemic - what does this mean?

Does this mean that the pandemic H1N1 influenza virus is no longer a threat?

Is there any sign of reassortment between different viruses?

What about antigenic drift?

Are there any new clues to why susceptibility was so high, especially among younger people, in the first place?

 

This report’s authors hail from such respected institutions as the Department of Microbiology and Immunology, The University of Melbourne – the Department of Immunology, St Jude Children's Research Hospital – and the WHO Collaborating Centre for Reference and Research on Influenza.

 

I’ve excerpted one section below (slightly reparagraphed to improve readability), so follow the link below to read this article in its entirety.

 

Personally, I’m saving this one to my desktop for future reference.

 

 

Q&A: H1N1 pandemic influenza - what's new?

Stephen J Turner , Peter C Doherty and Anne Kelso

Does this mean that the pandemic H1N1 influenza virus is no longer a threat?

Not necessarily, not altogether. Several features of this virus are a continued cause for concern; for example, most hospitalizations and deaths are still in those under 60 years old. This is probably because people in this age group are less likely to be immune.

 

Furthermore, of those people admitted to hospital in the USA with confirmed influenza (H1N1) 2009 pneumonia, almost two-thirds end up in intensive care. Recent clinical studies have identified risk factors for severe disease that include, but are not limited to, obesity, cardiovascular disease and pregnancy.

 

Importantly, however, about one-third of those who have died with (H1N1) 2009 lacked any known risk factors [1].

 

It is also of concern that the human influenza (H1N1) 2009 virus can be found in limited instances within pig populations, the species from which it emerged [2]. This increases the opportunity for the virus to reassort with other avian and swine viruses to produce new influenza strains of unpredictable transmissibility and virulence [3]. (Figure 1 illustrates schematically how new pandemic influenza viruses are thought to arise.)

Figure 1. Mutation and reassortment giving rise to antigenic drift and antigenic shift in different hosts of influenza virus. The surface hemagglutinin and neuraminidase molecules (blue) of influenza viruses, which play an essential part in viral recognition of and entry into host cells, undergo frequent mutation (antigenic drift) in their human hosts, giving rise to new variants (red dots) that can elude antibodies made in many individuals against the parent virus.

 

Less frequently, entire segments of the eight-segment genome of an avian influenza virus and a human virus become reassorted into the same virion, usually through infection of swine by both viruses, and this can result in a virus that is still adapted to infect humans but expresses an avian hemagglutinin or neuraminidase (antigenic shift) to which there is no prior immunity in human populations. These give rise periodically to pandemics. Figure reproduced with permission from Figure 10-17 of: DeFranco AL, et al. 2007 [24].

 

Nicely done, and highly recommended.

»» Read More

Study: Pandemic Mitigation by Early School Closure

 

 

# 4758

 

 

One of the first steps taken by many countries to reduce the spread of novel H1N1 last year was the closing of schools in affected communities.

 

By early May (2009) it was apparent that the severity of this particular influenza virus was less than originally feared, and many public health agencies moderated their recommendations  (see CDC No Longer Recommending School Closures For A/H1N1).

 

But a future, more severe pandemic, the extended closing of schools will once again likely be considered to help reduce the spread of the virus.

 

It isn’t an easy decision, however.  School closings are controversial, and the issues complex  (see The Debate Over School Closures).

 

Working parents rely on schools to watch their kids for much of the year during the day, and many low income families benefit from the school lunch program.  And of course, when schools are closed during a pandemic, some kids may congregate elsewhere and spread the virus anyway.

 

Many parents, however, would take exception to the notion of sending their kids to school during a pandemic.  Not only would it, in their estimation - endanger their children – it increases the odds of them bringing the virus home to the rest of the family as well.

 

So it is important to get some approximation of the benefits that school closings would generate.  To that end we’ve seen several studies over the past year that have produced varying estimates.

 

Study: Student Behavior During Pandemic School Closings

School Closures Revisited

Study: Effect Of School Closures On Viral Transmission

 

Today we’ve another study appearing in BMC Infectious Diseases, this time from the School of Computer Science and Software Engineering at the the University of Western Australia.

 

Here is the abstract (slightly reformatted for readability).

 

Developing guidelines for school closure interventions to be used during a future influenza pandemic

Nilimesh Halder , Joel K Kelso  and George J Milne

BMC Infectious Diseases 2010, 10:221doi:10.1186/1471-2334-10-221

Published: 27 July 2010

Abstract (provisional)

Background

The A/H1N1 2009 influenza pandemic revealed that operational issues of school closure interventions, such as when school closure should be initiated (activation trigger), how long schools should be closed (duration) and what type of school closure should be adopted, varied greatly between and within countries. Computer simulation can be used to examine school closure intervention strategies in order to inform public health authorities as they refine school closure guidelines in the light of experience with A/H1N1 2009 pandemic.

Methods

An individual-based simulation model was used to investigate the effectiveness of school closure interventions for influenza pandemics with R0 of 1.5, 2.0 and 2.5. The effectiveness of individual school closure and simultaneous school closure were analyzed for 2, 4 and 8 weeks closure duration with a daily diagnosed case based intervention activation trigger scheme. The effectiveness of combining antiviral drugs with school closure was also investigated.

Results

Attack rate was reduced from 33% to 19% (14% reduction in overall attack rate) by 8 weeks school closure activating at 30 daily diagnosed cases in a community for an influenza pandemic with R0 = 1.5; whereas combined with antivirals, 19% (from 33% to 14%) reduction in attack rate was obtained.

 

For R0 >= 2.0, school closure would be less effective. An 8 weeks school closure strategy gives 9% (from 50% to 41%) and 4% (from 59% to 55%) reduction in attack rate for R0 = 2.0 and 2.5 respectively; however, school closure plus antivirals would give a significant reduction (~15%) in over all attack rate. The results also suggest that an individual school closure strategy would be more effective than simultaneous school closure.

Conclusions

Our results indicate that the particular school closure strategy to be adopted depends both on the disease severity, which will determine the duration of school closure deemed acceptable, and its transmissibility.

 

For epidemics with a low transmissibility (R0 < 2.0) and/or mild severity, individual school closures should begin once a daily community case count is exceeded. For a severe, highly transmissible epidemic (R0 >= 2.0), long duration school closure should begin as soon as possible and be combined with other interventions.

 

 

George E. P. Box, Professor Emeritus of Statistics at the University of Wisconsin, is often credited with coining the familiar adage:

 

“All models are wrong, but some models are useful.”

 

While imperfect, we use computer models every day to try to mathematically simulate real-life events;  everything from highway traffic flow to weather forecasting.

 

The authors describe some of the limitations to their study, including:

 

As the model is based on a population in a developed country the outcomes may not be applicable to populations in a developing country, where populations may be less mobile and have higher population densities.

 

We have focused on the reduction in the number of daily symptomatic cases and the cumulative illness attack rate as they are used for determining intervention effectiveness rather than focusing on influenza-related adverse events such as hospitalizations and deaths.

 

We also do not take account of possible antiviral drug resistance [40] [41] that may arise due to the implementation of antiviral drug strategies, as our main goal is to suggest refinements to policy guidelines for school closure.

  

In this case, the authors based their modeling on a medium sized (pop. 30,000) town in Western Australia. 

 

They find a substantial reduction in the spread of a future pandemic influenza can be achieved by the (extended) closing of schools at the optimum point in the local spread of the virus.

 

Gauging when and how long to close schools, however, may require information that isn’t always immediately available.  Such as the R0 (basic reproductive number) of the virus, the CFR (Case Fatality Ratio) or, the number of people actually infected in a community. 

 

Despite the fact that life is messy, and computer models aren’t perfect at depicting it, the entire report is worth reading.

 

This is how the authors sum up their study.

Conclusions 

Our simulation results give guidance as to public health policy decisions in the refinement of school closure strategies to be used in a future influenza pandemic. We have systematically evaluated school closure operational issues to determine when schools should be closed and re-opened to achieve the maximum reduction in influenza spread.

 

We found that the optimal timing of school closure depends both on the duration of school closure (which we assume will depend on the severity of the influenza strain, with strains that are more severe in terms of serious infection outcomes making longer periods of school closure acceptable) and on the transmissibility of the influenza strain (which influences the rate of growth and spread of the epidemic).

 

Accurate early estimates of epidemic characteristics such as the basic reproduction number and disease severity are thus necessary to achieve the maximum case reduction from school closure.

 

We found that a policy of allowing schools to close individually was much less sensitive to the precise timing of the intervention than a policy of simultaneous community-wide school closure, a valuable observation given the difficulty in determining the true degree of epidemic spread in the early stages of an outbreak.

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Case Study: Co-infection With HIV and Bird Flu

 

 

 

# 4643

 

 

Despite the occasional `Eureka!’ moment, most of our scientific knowledge is gained incrementally, and over months or even years of research.   A single case study, such as the one presented below, doesn’t necessarily tell us a whole lot.   

 

But it does provide a puzzle piece.  And once you’ve gathered enough pieces, you can then begin to put the puzzle together.

 

Human H5N1 infections remain rare, with only about 500 recorded over the past dozen or so years.  HIV , while more common, affects less than 1% of the global population (although in some countries, that number is as high as 15%).

 

Accordingly, there have been few opportunities for scientists to observe HIV positive patients with an H5N1 co-infection.  

 

We’ve one such case study out of Vietnam, published today in BMC Infectious Diseases.  A hat tip to Tetano on FluTrackers for this link.

 

 

 

Influenza A H5N1 and HIV co-infection: case reportAnnette Fox, Peter Horby, Nguyen Hong Ha, Le Nguyen Minh Hoa, Nguyen Tien Lam, Cameron Simmons, Jeremy Farrar, Nguyen Van Kinh, Heiman Wertheim

BMC Infectious Diseases 2010, 10:167 (14 June 2010)
[Abstract] [Provisional PDF]

Background

The role of adaptive immunity in severe influenza is poorly understood. The occurrence of influenza A/H5N1 in a patient with HIV provided a rare opportunity to investigate this.

Case presentation

A 30-year-old male was admitted on day 4 of influenza-like-illness with tachycardia, tachypnea, hypoxemia and bilateral pulmonary infiltrates. Influenza A/H5N1 and HIV tests were positive and the patient was treated with Oseltamivir and broad-spectrum antibiotics. Initially his condition improved coinciding with virus clearance by day 6. He clinically deteriorated as of day 10 with fever recrudescence and increasing neutrophil counts and died on day 16. His admission CD4 count was 100/ul and decreased until virus was cleared. CD8 T cells shifted to a CD27+CD28- phenotype. Plasma chemokine and cytokine levels were similar to those found previously in fatal H5N1.

Conclusions

The course of H5N1 infection was not notably different from other cases. Virus was cleared despite profound CD4 T cell depletion and aberrant CD8 T cell activation but this may have increased susceptibility to a fatal secondary infection.

 

 

While the `The course of H5N1 infection was not notably different from other cases’, there were a few surprises along the way.

First, the patient showed some clinical improvement after two days of treatment (including oseltamivir).  Despite his HIV status, he was apparently able to begin clearing the virus by day 6, much as might be expected in a non-immunocompromised patient.

 

But the patient’s condition deteriorated around day 10 with relapse of fever, a raised CRP (C-Reactive Protein) level, and neutrophilia (elevated neutrophil white count) – all suggestive of a secondary infection. 

 

Throughout his hospitalization, however, the patient’s lab cultures were negative for bacterial infection, but positive for Candida albicans (and eventually, on 14) Aspergillus fumigatus.

 

Despite aggressive antibiotic and antifungal treatment, the patient died on day 16 of respiratory and renal failure.   A fate, and course of illness, not unlike that which we’ve seen with a great many other H5N1 cases.

 

It is possible, according to the authors, that the administration of corticosteroids early in this patient’s treatment may have contributed to the development of invasive pulmonary aspergillosis.

 

The authors conclude with the following (but read the whole report):

 

In conclusion  the course of H5N1 infection  in  this case was not notably different  in  the presence of HIV co-infection but  it  is possible  that HIV co-infection and profound CD4 T cell depletion  increase susceptibility  to secondary  infection.

The  findings suggest  that CD4 T cells may not be  required  for H5N1 virus clearance.

»» Read More