Snapdate: influenza H7N9 cases in humans, by the numbers...

An updated chart.
[SNAPDATE'S are snap updates that don't have lots of detail and chat...although they almost always end up having lots of chat!]

A summary of the monthly, weekly and daily data graphing human avian influenza A(H7N9) virus infections in humans reported from the hotzone, China.

Daily weekly and monthly H7N9 numbers, taken from the
FluTrackers curated line list [1] and the World Health
Organization disease outbreak news reports.
Click on image to enlarge.

References...

1. http://www.flutrackers.com/forum/showthread.php?t=202713
2. http://www.who.int/csr/don/en/

SNAPDATE: MERS by the years...

When it comes to Middle East respiratory syndrome coronavirus (MERS-CoV) infections, the years  and the comorbidities - really do take a toll. 

The graph below helps to highlight how the median and average ages of MERS-CoV positive cases and deaths are distinct from the median age of the total Saudi Arabian population - among whom most MERS-CoV infections have been reported. ...although there is the issue of expatriate workers who also get infected - do they contribute to the Kingdom's median age?

Click on image to enlarge.

SNAPDATE: MERS-CoV around the world...

A quick snap update to show how the Middle East respiratory syndrome coronavirus (MERS-CoV has been travelling around the world in the pat 4 years, using a cumulative curve.

Click on image to enlarge.

Snapdate: Confirmed Ebola virus disease cases - the end in sight?

I think we're a little bit beyond "jinxing" something by pointing it out, so here is graph of the confirmed Ebola virus disease cases based on the World Health Organization report date (Situation summary or Situation Report), including a basic model to predict when cases may hit zero, if nothing changes.

The P-value for this linear trend model is 0.00067. The standard error = 19.29;R-square = 0.14.
Click on graph to enlarge

I use Tableau Desktop Public Edition v9.0.0 for my graphs these days - and have taken advantage of its inbuilt linear trend model for this chart. This "model" accounts for precisely nothing apart from the trend based on the numbers that are available and have been plotted in this particular way, on this day, near a full moon. 

Reported numbers or outbreaks could flare up tomorrow or dry up overnight. 

I can say that over the past 2 weeks, data from each new summary or report have moved the predicted "end" data closer - from mid-June to now early June.

I am not an expert at modelling or statistics so please just take this at face value. The line suggests that if all things stay the same, we will reach zero considered cases per report around the 3rd of June 2015.

Please let it be so. 

Realistically, we may be heading for another "step down" - followed by a smaller trickle of ongoing cases for some period, ahead of a final push to zero. But there are experts who will know more about this than I.

Once we get to zero, the 42 day count begins.

Snapdate MERS-CoV chart update

Just a quick look at some updated Middle East respiratory syndrome coronavirus (MERS-CoV) detection figures. 

For 2-days this past week we had zero cases reported, but we still had a number of deaths. On the 27-May alone there were 5 deaths across 3 regions.

Weeklies chart.
Number of lab-confirmed cases on the left upright (y-axis), the cumulative weekly
average can be read from the right y-axis and the bottom (x-axis) lists data by week, usually week when signs & symptoms onset otherwise by hospitalisation date or
reporting if nothing else is available.
Click on image to enlarge.

The dailies chart shows that detections have reached zero. Been a while since that happened-earl April was the last time. This will possibly change as cases from coming days fall out with onset dates in this week. 
Or perhaps there won't be any cases in the coming week. We can only hope.

Dailies chart.
Number of lab-confirmed detecteions on the left y-axis and the x-axis lists data by day,
usually day of when signs & symptoms onset otherwise by hospitalisation date or reporting
if nothing else is available.
Click on image to enlarge.

I haven't added a healthcare worker (HCW) to my line list for the past 63-detections. That's the longest period without an HCW in the history of MERS! Is that true or are those data now withheld form the Kingdom of Saudi Arabia's numbers? Don't know. But here's what it looks like as yet another healthcare-related outbreak subsides.

Cumulative number of lab-confirmed detections among HCWs on the left y-axis while the right y-axis shows the proportion of MERS-CoV detection who were HCWs that week. The x-axis lists data by week, usually day of when signs & symptoms onset otherwise by hospitalisation date or reporting if nothing else is available.
Click on image to enlarge.

Snapdate: MERS-CoV detections by where they were probably acquired...

...yeah its "probably" because sometimes it's just not clear to anyone. I've about 14 (554 in total) more cases attributed to a likely source in the Kingdom of Saudi Arabia (KSA) compared to the Ministry of Health tally on their website (540), but such is life.

Anyway, I haven't updated this chart for 17-days (woah - sorry about that). The latest version now has the two major hospital-related outbreaks shown in pink - I'm still liking the Janadriyah festival as the possible source of community cases that then filter back throughout the country as visitors and tourists return to different areas or travel afterwards for other reasons. That would be on my 2015's "festivals that need to be tweaked to avoid camel contact" list.

As per yesterday's post, these accumulation curves highlight that new detections of MERS-CoV have slowed right down in the KSA and in the United Arab Emirates (UAE). However, the UAE are now the reporting slow pokes, if the last batch posted by the World Health Organization is anything to go by, so we should stay tuned to what's happening there (and also stay tuned to the extent of upper respiratory tract signs and symptoms in those cases which continue to bug me).

Click on image to enlarge.

Snapdate: MERS-CoV detection by month...

We are living in the 2.17th year, or 113th week, since the first known MERS-CoV-related illness affected a 25-year old Jordanian.

April stands out as the biggest MERS-CoV detection month ever, with 286 cases either becoming ill, being hospitalised or being reported as positive. But don't be confused by the differing values on the axes in the chart below. For all that May looks like a smaller cousin of April, its tally has already outstripped every other month of 2012 or 2013. 

72 cases so fall into May. But the rate of cases this month is slower than in April (see previous post). 

The tally of detections announced officially through WHO (which remains in a galaxy far, far, far away when it comes to detail on April-May cases) and from various Ministries of Health brings my worldwide tally to 580 MERS-CoV detections listed of which ~166 people have died of MERS. I'm still awaiting detail from WHO or UAE on 4 MERS-CoV cases that I do not list.

38% of May's case have died compared to 13% of April's (where I'm able to assign fatal cases to a month).

Click on image to enlarge.

H7N9 Snapdate: some quick charts...

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I don't have a lot of time tonight so this is just a quick post of some updated charts with a few summaries of some key features of the influenza A(H7N9) virus situation in south-eastern China. At writing it was at 432 detections with media reporting 128 deaths

Click on image to enlarge.

Guangdong is where H7N9 is still most active and it is this province that is the source of the continued cases trickling off Wave 2's peak.

Most H7N9 cases overall have been in Zhejiang and Guangdong provinces but lately, post-peak of Wave 2, there has been continued activity in Jiangsu province including a recent healthcare worker with no mention of "contact with poultry"; the absence of which stands out in World Health Organisation (WHO) reports because most cases are followed by affirmation of that phrase.

Click on image to enlarge.

In  the  survival chart above we see that most of the fatal cases, shown in red, are defined by an older age. Unfortunately, a lot more of the fatalities have been reported through the media without identifying details (48 of 128), than have come through official Chinese channels and out via the WHO. This lack of detail makes it impossible to clearly link a lot of the deaths to the case announcements. Only the custodians of these data know what this chart should really look like. NB: Since making the chart this morning I've found a handful more case details at FluTrackers, but public detail on fatal cases remains the weakest of any of the H7N9 data.

Click on image to enlarge.

We can see in the weekly chart on the right that the two H7N9 waves differed in timing, the width of their bases (more cases in Wave 2) as well as how "tight" their peaks were. Wave 2 has tailed off, but continues to spit out cases, while Wave 1 comprised both a steep climb and a steep decline in human cases.

Click on image to enlarge.

If we zoom in on Wave 2 we can see by looking at cases per day in the chart on the left, that between 0-4 illness onsets per day are being reported, as they have been since late Feb-2014. 

Is this the legacy of those regions whose live bird markets remained open or were only shut temporarily for disinfecting and restocking? Those regions with markets that were shut for much longer, or for good, do not seem to have contributed much to the continuing leak of H7N9 infections despite being key contributors during the peak periods before markets were closed.

Click on image to enlarge.

In zooming in on Wave 2's cases by week, but this time based on the region of likely acquisition of infection, we see that Guangdong province (brown line) has been the most consistent contributor of human H7N9 infections both late during the 2nd of the Wave 2 peaks, but also after the peak's decline almost everywhere else in south-east China. There was considerable publicised unwillingness from poultry producers to permanently close markets in this Province, a location with a major role in the nations poultry production. And so this little experiment incubates further and I have little doubt we will see the impact of that unwilingness late in 2014. 

Click on image to enlarge.

As noted above, public H7N9 death data do not allow good linkage with official case announcement data for about 48 fatalities, so my second-last chart tonight uses both public and media-release numbers to try and illustrate how the proportion of fatal cases (PFC) has changed across both Waves. The PFC seems to be holding fairly steady now between 17% and 30% (depending on source of numbers).

Click on image to enlarge.

And finally we see that the age and sex distribution across all cases (both Waves) is skewed to wards older males. Same as usual. If we look at this distribution (ran out of time to put in here) for the fatal cases, it is much more tightly grouped around the >60-year olds, but that females appear to dominate males in deaths during Wave 2, whereas it was the other way around for Wave 1.

Snapdate: Middle East respiratory syndrome coronavirus (MERS-CoV)

Click on image to enlarge.

Chart update time for human cases of the MERS-CoV.

Chart #1: lab confirmed(Ministry announced) human cases of MERS by region of acquisition. MERS is a disease with its activity firmly rooted in Saudi Arabia.

Chart #2: age and sex distribution pyramid. MERS is a disease of older males.

Click on image to enlarge.

Chart #3: here we see total and just the fatal MERS-CoV cases in humans, by month and year. I've kept the same value on the y-axis (left side) for ease of comparison. This chart highlights that there is no obvious seasonality for cases. In 2014 we're seeing more in Jan and Feb than we did in 2013 and in 2013 cases trickled along at similar levels from April onwards. This, if anything, supports the sporadic acquisition of cases and rejects the idea that, at least among the hospital-based population that is the main one to have been tested to date, MERS-CoV is not a seasonal virus.

Click on image to enlarge.

Chart #4: this one shows as the slowly spreading outbreak. More disturbingly, it shows the very gradually increasing PFC. Currently, 43% of MERS cases have died; 2 in 5. Guess its worth remembering that MERS-CoV may a puny virus in camels and in terms of transmission efficiency; but not at all puny in regards to what it does to the older usually male and mostly already ill people it infects. It is quite an efficiently lethal virus in that sub-population.

H7N9 snapdate: epidemic curve as Wave 2 looks to be ending...

Click on image to enlarge.

This image is another way of showing that the current wave of human cases of avian influenza A(H7N9) virus is ending and that we are solidly within a period of "tailing" (cases only ticking over at low levels in the lead-in or lead-out of the main peak).

BUT: These data are based on figures that are publicly available. As we learned overnight, those numbers can come in fits and starts, if at all. The addition of a large number of deaths without any identifying information linking to the case onset, supports what some have been suspecting for a while; we don't have a full picture of what's happening with H7N9. 

There are now up to 48 more deaths due to H7N9 infections, depending on where your base count is taken from (verified updates or or the media) than we knew about 12-hours ago.

More on that topic later today.

H7N9 snapdate: latest hotzone map

Avian influenza A(H7N9) virus human cases by region of acquisition.
Click on image to enlarge.

H7N9 snapdate: accumulating cases by region of acquisition

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This is what happens when you do nothing to stem the possible source of an influenza outbreak in your back yard. 

Nothing. Nothing changes.

The infection keeps spreading. 

Very clearly the H7N9 hotzone in China has now shifted from Zhejiang province to Guangdong province (the brown line that represent the second highest number of human cases of disease..75 cases representing 21.3% of all H7N9 cases.

As we read today, this province has just shut some of its poultry markets. By the look of this rate of new cases, the people of Guangdong province could be in for a tough 2-3 weeks and will be hearing a lot more about "bird flu" much to the poultry industry's disgust.

H7N9 snapdate: H7N9 totals by month, 2013 vs 2014 to date

Click on image to enlarge.

January has so far tallied 1.6x more cases than the peak month of 2013 which was April. And those cases are still being reported.

But only 2 lab-confirmed cases were added to the list last night, perhaps things have started to slow at last? 

That is extrapolating a bit much from 1 night of reporting with low numbers, but let's wait and see what happens tonight (today for you guys up north!). Seems to be the mantra for this sort of stuff.

H7N9 snapdate: cumulative case chart

Click on image to enlarge.

This is a new idea for VDU's blog: the snapdate or "snap update". It covers those times when I have little more to say beyond what a chart conveys yet still more words than a Tweet can cover.

This is a snapdate of 205 avian influenza A(H7N9) virus cases.

That Zhejiang slope looks eerily familiar. I know 205 is only 6 more than 199, but crossing a multiple of 100 is "a thing" for me. 

Something I tweeted yesterday that I thought was interesting when comparing the earlier "bird flu" to (one of many of) the latest...

• >200 H7N9 cases in <1-year
• >645 H5N1 cases in >15-years

Despite all the papers and press, it still feels like the fluff over H7N9 has been less all-encompassing than that for H5N1 was/is, even though H7N9 reached its first 100 cases in fewer than 2-months.