Avian influenza A(H7N9) virus cases hit 400

While everyone was looking at Guinea and the Ebola Zaire outbreak, that stealthy H7N9 has gone and infected a total of 400 people that we know of. It is of course, just another milestone and not an indication of anything changed about the virus. In fact the trend for few cases per day is continuing. One constant in s sea of change and new things.

Another constant, the up-to-date nature of the FluTrackers case list - check it out here. 

I have to run - much to learn about Ebola!

References...

1. FluTrackers H7N9 case list
   http://www.flutrackers.com/forum/showthread.php?t=202713

Google Flu Trends: What did you expect?

I posted this on Crawford Kilian's H5N1 blog in response to his positing yet another story whacking Google Flu Trends for its "failure".

In case you can't tell - I'm a little sick of the number of electrons being wasted on writing the same thing about this paper in Science. I know, there is no shortage of electrons. Still, I hope to see this same degree of ire elicited by and directed toward other places, corporations and States who have trouble providing data to the public within the expected realms of accuracy. I'd also hope for more focus on what and how we test now and how representative that is of what a virus is doing; or what we might be missing.

I think Olson et al said it well when noting GFT's earlier failure to predict the H1N1 2009 pandemic's influenza-like illness activity..

"Current internet search query data are no substitute for timely local clinical and laboratory surveillance, or national surveillance based on local data collection"

The post...

Okay. Google Flu Trends (GFT) was not 100% accurate. Wow. Who'd would have thunk it? Who could possibly have guessed this would happen? The disappointment is clearly widespread. A predictive computer-based system set up for devising regulatory guidelines, formulating vaccine formulations, ensuring suitable laboratory testing capacity and preparation or national surveillance guidelines failed. Wait. What? It wasn't setup for any of that! It’s really just a pretty thing you can go look at to get an estimate of flu activity near you; much easier to wade through than some country's public health efforts. Estimate. When did we expect an estimate to be perfect?

Come on people-interpreting-this-paper. GFT isn't a failure unless you were honestly expecting it to be 100% correct.

Of course it couldn't ever be that. THERE. WAS. NO. VIRUS. TESTING. Not done by GFT anyway. Some lab testing went into it apparently, but even that was a sliver of a slice of a shard. And if you know anything about respiratory virus testing, then you know that even the testing we do, represents only a tiny fraction of the amount of virus-positive cases out there, extrapolating from those. That testing even varies from place-to-place in type, quantity and extent of reporting. The choice of what to test (sampling) is itself biased in a number of ways, not the least of which is that we favour testing pretty sick people or those that feel crook enough to present to a Doctor. We’re comparing GFT’s “fail” to an estimate. You’re all comfortable with using that to lambaste GFT? You’re comfortable to call that a total fail?

"The folks at Google figured that, with all their massive data, they could outsmart anyone."

Really? Is that what the folks thought? Did Google really get bitten by the flu bug?; can Google truly not track the flu? Certainly catchy headlines one and all. I guess no-one would read something entitled "Google Flu Trend's estimates not in agreement with some national testing data which also represents only a portion of those who get infected". I can see where that might not be a real mouse-wheel turner.

GFT was and could only ever be a predictive system. Just like that shiny App you have on your phone that predicts the weather forecast. Let's drag "big weather" through the interwebs flailing it at every turn so we can suitably express our righteous indignation at its failure to predict the rain we wanted on the weekend. It failed! OMG! Now I have to water my lawn to stop it from drying up. But that's all I have to do. No-one died when the clouds held their watery payload. My child was no more or less safe because the weather bug bit the Bureau of Meteorology here in Queensland. I didn’t have to get a new lawn because it is now 24-hours drier.

Does GFT's overestimate of the number of predicted cases by 0.5-2 fold (depending on the story you read) really have a real-world impact on anyone? Seriously? Keep in mind that its estimates still followed the trend of flu activity pretty closely; they peaked when actual flu was peaking, just not (my other estimates) perfectly. But apparently someone 100% concordance between lab sampling and GFT estimate data.

GFT has been doing a perfectly good job given what it is and what it could ever hope to be in its current setup. Perhaps centralizing and plotting the WORLD'S lab-based data alongside Google “flu”-related search-result data would be a useful next step for GFT. Then we could make up our own
minds.

In the meantime, keep it in context people.

References...

• Crof's blog post
  http://crofsblogs.typepad.com/h5n1/2014/03/why-google-flu-is-a-failure.html
• The Parable of Google Flu: Traps in Big Data Analysis
  http://www.sciencemag.org/content/343/6176/1203.full

More camel mentions among MERS-CoV cases...

Click on image to enlarge.

Special thanks to Professor Andrew Rambaut ([4]; @arambaut) for keeping such great track of the number of human cases in which camels has been mentioned.
Also thanks to Prof Rambaut and Ellen Knickmeyer  (@EllenKnickMeyer) for putting up with my stupid questions.

The current tally is now 11 human cases with a link to camels; 3 more than my earlier post on this topic.

The charts still show that cases outside of the Kingdom of Saudi Arabia (KSA) are proportionately more likely to identify human contact with camels than are MERS cases acquired within the KSA. 

The first case from Qatar with a camel link was from Sept-2012; from the United Arab Emirates (UAE) on Oct-2012; from Oman 20-Dec-2013. The very first (index) case of MERS-CoV to be announced to the world on Sept-2012, that from a 60-year old man living in Bisha in the KSA, also had contact with his 4 pet camels which we learned of in an article in the New York Times ([1] and later in an article late February 2014 [3]). 

I have not added the case of a Qatari male who owned a camel and goat farm [5], because the report in Eurosurveillance notes he claimed no direct contact with sick animals. I do wonder about contact with healthy or asymptomatic animals though. 

References...

1. New York Times article on Prof Memish et al's mBio paper.
   http://www.nytimes.com/2013/08/22/health/mystery-virus-thats-killed-47-is-tied-to-bats-in-saudi-arabia.html
2. Prof Memish et al's mBio paper (does not mention camels though)
   http://wwwnc.cdc.gov/eid/article/19/11/13-1172_article.htm
3. Alagaili et al's paper noting camels were a contact of 60M index MERS case
   http://mbio.asm.org/content/5/2/e00884-14.full.pdf+html
4. Professor Andrew Rambaut's MERS-CoV case list
   http://epidemic.bio.ed.ac.uk/coronavirus_background
5. Eurosurveillance contact study of 45-year old male from Qatar (FluTracker's Case #6)
   http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=20406

MERS-CoV in camels... [CORRECTED]

The top pie chart shows the distribution
of all human cases containing the word 
"camel" in their case notes, by the site where
the human was likely to have acquired their 
MERS-CoV infection. The bottom bar 
graph shows those data in terms of the
 proportion of cases at that site for which
"camel" contact was possible.
Click on chart to enlarge.

Thanks very much to Nicholas Evans (@neva9257 via Twitter) for asking me to back up my gut feeling about there having been more camel-links among MERS-CoV cases outside the Kingdom of Saudi Arabia (KSA) compared to inside.

I live to serve and so using those data I have to hand I've made a couple of charts. I'll keep these updated from now on too. 

I'd be grateful if anyone wanted to shout out human cases where camel contact was mentioned. I currently have 8 in total on my list of 201 lab confirmed MERS-CoV cases. (see the figure up there for where my cases are sourced). There may be many I have missed though.

One obvious question arising from the bottom bar graph is why does such a low proportion of camel-associated cases occur in the KSA but not elsewhere? 

For the sake of simplicity, I'll exclude the possibility that MERS-CoV jumps off its camel hosts at a border. Because the latest 68M from UAE may well have acquired his infection while visiting his camels in the KSA I have now listed him as a KSA acquisition...until I hear differently). We also know that camels in the KSA get actively infected (see earlier posts, listed below, on these findings [1,2,4]). 

So do these charts, by highlighting that so few camel links are to be found in the KSA (site of >80% of MERS-CoV human cases), discount camels as a source of infection? I don't think so. We have some very compelling evidence for camels hosting MERS-CoV [4], for camels being present in mass gatherings [5], and nothing but an absence of epidemiology to counter their role as a host and source.

I suspect the graph shows that MERS cases in the KSA won't admit to camel contact. Alternatively, perhaps contact, in its many possible direct and indirect forms is not being adequately sought or listed in case reports and in "gumshoe epidemiology" efforts (Ian Lipkin's comment, [6]). But why would camel contact not be listed, reported or collected? Perhaps it is seen as a bad thing? There may be stigma associated with acquiring an illness from a camel. Or perhaps stigma attached to the way in which that illness was acquired.

Perhaps it is a simpler explanation. There is likely to be fear, or a real risk, of social and economic fall-out of "naming and-shaming" camels as a major source of infection/disease. Camels fill many important and significant roles in the lives of those around the Arabian peninsula; from food, drink, religion to tourism and fun. But not identifying camel links in the spread of MERS-CoV, if indeed more links do exist, won't stop KSA's locals from acquiring infection and MERS. 

If there is a deficit in reporting camel exposures in the KSA, for whatever reason, it does one thing particularly well; it delays the understanding of how to protect people and reduce their exposure to MERS-CoV. I think that understanding is probably inevitable, so it may be better for the KSA Ministry of Health to get out in front of the issue; be proactive in finding the source of infections and openly discuss and plan for the implications. But I may be seen as living in a world of unicorns and fairies (again) to suggest that will eventuate. My cynicism is based on 2-years and 201 cases of a virus that's been very well virologically and molecularly detected and characterised outside the KSA, while its basic aetiology and epidemiology inside the KSA has left much to be desired.

I would very much like some locals to weigh in on this topic. Here (in the comments below) or by email or on Twitter. The bar graph simply highlights a discrepancy that could be cleared up with a better understanding (perhaps just by me) of what may  underlie the difference in the apparent roles for camels among countries sharing borders.

References...

1. Dromedary camels are a host of MERS-CoV...
   http://virologydownunder.blogspot.com.au/2013/12/middle-east-respiratory-syndrome.html
2. Middle East respiratory syndrome coronavirus (MERS-CoV): camels, camels, camels!
   http://virologydownunder.blogspot.com.au/2014/02/dromedary-camels-are-host-of-mers-cov.html
3. MERS in the UAE....[UPDATED]
   http://virologydownunder.blogspot.com.au/2014/03/mers-in-uae.html
4. Dromedary camels are a host of MERS-CoV...
   http://virologydownunder.blogspot.com.au/2014/02/dromedary-camels-are-host-of-mers-cov.html
5. Middle East respiratory syndrome coronavirus (MERS-CoV) cases rise in march: Festival-related?
   http://virologydownunder.blogspot.com.au/2014/03/middle-east-respiratory-syndrome.html
6. Receptor for new coronavirus found: Virus might have many animal reservoirs.
   http://www.nature.com/news/receptor-for-new-coronavirus-found-1.12584

MERS in Kuwait...

It's a "MERS-in.." kinda day. 

The World Health Organization todayannounced a fatal case of confirmed MERS-CoV infection diagnosed in Kuwait [1].

Summary of the case details:

1. The infected person was a 60-year old male
2. A Syrian national
3. Hospitalised 13-Feb-2014
4. Died 6-Mar-2014
5. Lab confirmed 9-Mar-2014
6. He had comorbidities

A few things here worth noting I think:

• There was quite a gap (24-days) between being hospitalised (not sure when the case started showing signs of illness) and having a laboratory confirmation (also 3-days after death)
• While this is the 3rd case identified within Kuwait, it seems to be the first case that could be nailed down as having been acquired in Kuwait. I tend to try and list my numbers and maps by where the case was acquired rather than where they were diagnosed. Two previous MERS-CoV cases (FluTrackers #158 and #159; includes 1 case with camel contact noted) diagnosed in Kuwait had travelled outside Kuwait blurring the ability to see where they had picked up the virus

.@setiogi @MackayIM @FluTrackers Not the first Kuwaiti case. and infection acquired in #Kuwait, we believe. #MERS
— Gregory Härtl (@HaertlG) March 20, 2014

References...

1. WHO Disease Outbreak Notification 20-Mar-2014
   http://www.who.int/csr/don/2014_03_20_mers/en/
2. FluTrackers thread on Kuwait MERS-CoV case #1
   
   http://www.flutrackers.com/forum/showthread.php?p=514258#post514258
3. FluTackers on Kuwait MERS-CoV case #2
   
   http://www.flutrackers.com/forum/showthread.php?p=528694#post528694

MERS in the UAE....[UPDATED]

For the second time this month, there has been a case of Middle East respiratory syndrome coronavirus (MES-CoV) infection confirmed in the United Arab Emirates (UAE; Abu Dhabi to be precise). 

What added to my confusion (as you'll know if you were following me on Twitter this morning) was that both cases, apart from being from Abu Dhabi, were also 68-year old males and both have had camel contact. 

Today's 68M UAE case frequently visited his camel farm in the Kingdom of Saudi Arabia (KSA; had just returned from there 5-days earlier, thus in my mind making this a likely KSA acquisition) while the earlier 68M UAE case owns his farm in the UAE where he contacted animals including camels which he breeds.

This raises another question from me; why do we see proportionately more camel contact outside the KSA than we do inside the KSA (I haven't done the maths so this may just me my unfounded gut feeling)? Is it something simple like better epidemiological investigations conducted by Qatari and UAE investigators or are things, yet again, different somehow inside the KSA than they are outside the KSA? 

Surely there are some clues in there for investigators to use either to either improve how the epidemiology investigations are conducted or to look beyond camels in the KSA at other sources of acquisition?

Any differences in the sex of avian influenza A(H7N9) virus cases in different areas of China?

a) Male (blue) and female (lavender) lab-confirmed H7N9 human cases broken into the Province or Municipality of likely acquisition. b) The proportion of total H7N9 positives at each site of acquisition that are female (lavender).  The proportion of females in Wave 1 (Range of weeks beginning 18-Feb-13 to 20-May-12) and Wave 2 (07-Oct-13:current) are also shown as a horizontal line for comparison.
Click on chart to enlarge.

This new chart idea was just a look-see at whether there is anything out of the ordinary about the sex distribution of H7N9 human cases in the different areas of China. These are total numbers from both Waves of H7N9 season.

I've included case numbers in Part a) as well as proportion of females in part b) to show that a value of 100% must be place in context of only 1 POS!

Nothing much to see here folks.

MERS-CoV: sex, age and accumulating death

A few more charts, just to fill out the set for today's Middle East respiratory syndrome coronavirus (MERS-CoV) update.

First Chart.
Click on chart to enlarge.

The first chart shows what everyone knows; MERS, as it has been for the past 2-years, is a severe disease principally of the people of the Kingdom of Saudi Arabia (KSA). 

The route of human acquisition of MERS-CoV remains unknown and will not soon be discovered judging by the lack of any evident plan in the most recent Editorial on MERS-CoV from the KSA's lead author, Prof Ziad Memish. An even less addressed topic is why this disease has such an impact in this particular country given that neighbouring States share aspects of lifestyle, belief and habit.

Second chart.
Click on chart to enlarge.

The second chart reinforces that MERS, in the severe form we see in hospitals, is principally a disease of men (66% of all case are male;  77% among the fatal cases) aged 50 and above (median age is currently 53-years). Something this chart does not show is the that MERS-CoV is a particularly opportunistic virus causing serious disease and death particularly among those who present with an underlying disease (at least a third of cases have a comorbidity of some sort).

Third chart.
Click on chart to enlarge.

In the third chart we can see the human cases by month. Nothing to add for 2012 or 2013 but that steady climb in 2014 should be watched. Why is it there? Why, 2.04 years since we learned of MERS-CoV thanks to the endeavours of an Egyptian scientist named Dr Ali Zaki, are there no public conversations on what is/could/should be done to staunch the trickle of new infections and deaths? Will we see a take-off of cases in April 2014 as we did in 2013? What is happening in Riyadh (where most cases have been of late)? I've added in the Janadriyah festival too because why not?

And in the fourth chart we can see that trickle of new cases but they have thankfully not (yet) been matched by an equivalent rise in fatalities judging by the proportion of fatal cases (PFC) which has dropped a little. The PFC still sits at the "killer virus" level of 42% of all laboratory confirmed cases dying. Not my phrase. 

To generalise, MERS-CoV infection is mainly a cause for serious concern among a particular adult population within the KSA. 

A question I'd like to see answered by studies from the KSA is what is the epidemiology and clinical spectrum of human coronaviruses 229E, NL63, HKU1 and NL63? I believe that would be an interesting study yielding results  that may well put MERS-CoV in a very different context.

Yet another reason for every State to test its population for respiratory viruses I suppose, because then one has a baseline for the known viruses which can help judge the impact of newly identified or emerging viruses.

Influenza viruses in Queensland, Australia: 03-Mar-2014:09-2014.

Map of Queensland's Hospital and Health service
areas. Adapted from
http://www.health.qld.gov.au/maps/hhs_facilities.pdf.
Click on image to enlarge.

Sure enough, as promised on the 12-Mar, the new Queensland flu numbers are out (I post a week after the next new numbers come out publicly; its just the deal I have). So this follows on from last Wednesday.

This is the next week's numbers which follow on from my earlier post on the increased number of influenza cases and the media reports of influenza A(H1N1)pdm09 virus  predominance.

The Queensland Health Statewide Communicable Disease Surveillance Report for the week 03-Mar:09-Mar has some extra detail, this week. The extra detail outlines that most (860; 94%) of this year's 918 influenza notifications (2.3X the 5-year year-to-date mean value) to date are located in the following Hospital Health Service (HHS) areas (see the map above):

• Metro South: 192 (21%)
• Metro North: 176 (19%)
• Gold Coast: 110 (12%)
• Cairns and Hinterland: 106 (12%)
• Townsville: 73 (8%)
• Darling Downs: 52 (6%)
• Sunshine Coast: 50 (5%)
• Cape York: 46 (5%)
• West Moreton: 28 (3%)
• Mackay: 27 (3%)

The median age of cases is 41-years and 50% are male. The highest rate of notifications is in the 50-59-year age group at 24.8/100,000.

Percentages represent the proportion of all 80 
notifications for this reporting period.IFAV-Influenza A virus; IFBV-Influenza B virus.
Click on image to enlarge.

This report also has some typing (Flu A or B) and subtyping data (H3N2 or H1N1).

These data are very much appreciated  since this is ahead of the traditional "flu season" reports. 

Many thanks to all associated with the Communicable Diseases Unit, Queensland Health, for adding this detail in. 

The chart above makes it very clear that H1N1 dominates the Qld influenza landscape so far. Specifically...

• 80 notifications with signs and symptoms during the reporting period
• 68 were typed as influenza type A viruses (85%)
• 13/14 were subtyped as H1N1 (pdm09 I presume; 93% of the FluAs that were subtyped)
• 1/14 H3N2
• 12 were typed as influenza type B viruses

Respiratory viruses: the viruses we detect in the human respiratory tract

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