Random Analytica

Random thoughts, charts, infographics & analysis. Not in that order

Tag: MERS-CoV

Random Analytics: 100-days of MERS

Given that we are now half-way through the annual Hajj I thought I might spend some time looking at the Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV) which has been with us for some years now but seems to have fallen off the radar in favour of the maladie de jour, Ebola.

What publically sourced data is available is limited. In the past 100-days there have only been 25-notified cases (23 in Saudi Arabia, 1 in the United Arab Emirates and an exported case to Austria). The Kingdom’s updates are as brief as ever, the World Health Organisation (WHO) has clumped together a monthly update with only high-level data while the world’s attention is completely focussed on Texas and West Africa. Not only is the data limited but the Saudi’s have again reviewed their data and found a further 17 cases prior to 3 June that were missed. Ian Mackay wrote an excellent open letter to the KSA Ministry of Health in relation to that oversight (recommended reading).

For lots of reasons I haven’t updated my rudimentary MERS-CoV Db in a couple of months and what I found during my data-entry this morning I thought was intriguing enough to do an infographic with MERS notifications going back just 100-days.

1 - MERSbyCity_141005

The 100-days of MERS infographic details the 25-cases that have been notified between the 29th June to the 6th October 2014. The Riyadh count includes the young lady who travelled from Afif to Austria and one case where the KSA Ministry of Health provided no details (thus the figure is represented as a man).

Just to cover off the basic points in the infographic, there have been 25-cases since 29 June and two notified deaths (assuming that FluTrackers case number #863 is the 76-year old male from Najran who died on 25 September, thus a provisional Case Fatality Rate (CFR) of 8%, which is extremely low compared to the current 42.4% during the outbreak in the KSA. Of the 24-cases with details, four were female, the ages ranged from 27 to 76 and the average age was 54.1

Now to the really interesting data-points, some queries and a counter-factual.

  • A quick look at my Db tells me that during the period July – September 2013 there were approximately 56-cases of MERS (not including any that formed part of the 113 that were belatedly added without details). My first question: Is MERS on the decline given that the epidemiological curve seems to have declined by half since last year?
  • Even though the cases are very low the spread of the disease is extremely widespread. Over the past 100-days MERS has cropped up in Abu Dhabi (882km west from Riyadh via Route 10), Najran (974km south via Route 10), Taif (994km south-east via Route 40) and Arar (1,157km north-east via Route 65). My next question. Can someone explain why the cases are so low but seem to be so widespread?
  • There have been seven confirmed cases in Riyadh which has a population of 4-million and six cases in Taif, population approximately 500,000. Is there any reason why Taif is currently overburdened with the limited amount of cases?
  • The provisional CFR over the past 100-days seems very low at just 8%. Is that due to better care, less cases, better surge capacity, declining potency or another reason?
  • My last data point is really a counter-factual on the data that has been presented over the past three-months. The release of a second tranche of non-notified cases (this time 17 as compared to the previous 113) has to be questioned more deeply. You can always allow for a mistake but two is either a conspiracy or a cock-up. If it is a conspiracy are the Saudi’s ‘juking the stats’ in order to protect travellers from the Hajj? Are the Saudi’s using the current Ebola outbreak to limit the amount of information they are sharing? If it’s a cock-up why was it allowed to happen a second time in the lead up to the Hajj.

In Summary

Looking at the previous 100-days of data has me asking a number of questions. Is MERS on the decline? Why is the CFR so low? Why are the cases so widespread? Why has one small city got as many cases as the capital?

There are two incontestable facts. One: During the past 100-days MERS-CoV has been widespread across Saudi Arabia and the United Arab Emirates. Two: I also know where it hasn’t officially been.

Mecca.

Make of that what you will…

Random Analytics: MERS by Occupation (to >375)

Since my last Middle Eastern Respiratory Syndrome update (21 May 2014) there have been a number of key developments and even some improvements in data quality coming out of the Kingdom of Saudi Arabia.

The big announcement since my previous post was the addition of 113 legacy cases by the KSA Ministry of Health. Of the 113-cases, 42 were Health Care Workers and are included in the following charts.

Almost as importantly, the Saudi’s are now sharing their data with the World Health Organisation (WHO). The Disease Outbreak Notifications, or DON’s, are very comprehensive, light-years away from the Health Ministries updates of the past. With some irony I was pleased to see that Iran and the Kingdom featured together in the most recent DON. Perhaps we are seeing a form of MERS diplomacy occurring.

Here are the latest MERS by Occupation charts.

***** Please note that all infographics for this MERS-CoV article are using publically sourced information to 1200hrs 4 July 2014 (EST) *****

 

01 - MERSbyJobTitle_140704

This first chart looks at those infected with MERS by Job Title or Function.

Key Notes:

  • Retired: The largest group. There are 150-retirees (39.5% of known job titles) represented in this chart but only 2 have been confirmed (1.3%). The bulk of the retirees represented in the chart are included if they did not have a job title or function attributed to them AND if their ages are greater than the official retirement age for their home country.
  • Health Care Workers (HCW): The second largest group. Includes all types of unidentified workers in the Health sector (i.e. Nurses and Doctors).
  • Nurse: I have been able to identify 23-Nurses and in at least two cases, their speciality (ER & ICU).
  • Farmer: Includes both Owners (9/75%) and Employees (3/25%). I suspect the higher weighting toward owners is due to the fact that they are all nationals (from KSA, Qatar and the UAE). The three farm employees that have been identified are all resident workers. Just a thought here. Rich owners get to see the doctor while residents might have a range of barriers which reduce their ability to receive primary care services or choose to work through what they might believe is a bad flu.
  • Pilgrim: Of the 11-Pilgrims I have been able to identify I believe at least 8 were Umrah linked while three were potentially due to the Haj.
  • Doctor: Six identified, including one surgeon and one ICU specialist.This infographic looks at those infected with MERS-CoV by Job Family. In short I think this is a key infographic for MERS as it gives you some confidence in the key narratives (i.e. that Health Care Workers are over represented in the data as an example).

Next chart, Job Families:

02 - MERSbyJobFamily_140704

Key Notes:

  • With the inclusion of an additional 42 Health Care Workers the Non-Participatory (156/18.6%) group (Paediatrics, Students, Retiree’s and the Unemployed) move from the largest to the second largest Job Family.
  • Health Practitioners/Technical Operations (159/19.0%) or HCW as there more commonly known become the largest Job Family represented. This number includes the Nursing Assistant that was identified in Iran (but more on that later).
  • Paediatrics (18/2.1%) numbers have declined since the last update when they represented just 2.8% of the data then. Still seems low and Maia Majumder picked up on this in a recent post.
  • Pilgrim/Tourist (14/1.6%) has seen a slight increase due to some Umrah inclusions recently.
  • Healthcare Support (6/0.7%) numbers remain static so not sure if the Saudi announcement of legacy cases conflates HCW and HCSpt numbers.
  • Construction (2/0.2%) is a new inclusion from the previous update. Given the amount of building going on the in the Middle East, especially in Qatar this number seems on the very low side. I’d expect to see this number increase with more robust reporting.

Last chart.

03 - MERSbyMainJobTitle_140704

The last chart looks at those overall main job families that are most impacted by MERS, specifically Farmers, Travellers, Paediatrics, Retirees, HCW & HCSpt (combined), Other and Unknown.

Key Notes:

  • Farmer (1.7%): With only 14 confirmed cases apart from 2013 you can barely see them across an entire year, quarter or month. Numbers seem low.
  • Traveller (1.7%): Like farming, numbers seem low.
  • Paediatrics (2.1%): As suggested previously, no new paediatric cases since my last update so the numbers have declined somewhat.
  • HCW & HCSpt (19.7%): Health Care Workers and I have also included Health Care Support Workers in this grouping as well. Numbers up on previous update due to the additional 42-cases.
  • Other (2.3%): All other occupations that have been publically released. I’ve actually reduced the number in this group by one from the last update due to improved reporting from Saudi Arabia.
  • Unknown (54.7%): Unknown occupations. Up slightly but with improved reporting I’m hoping that this will reduce (over time).

Final Thoughts (on the difference between a Health Care Worker and Health Care Support

Last month I tweeted that the Iranian Nursing Assistant (FT #827) should be counted as a Health Care Support worker rather than a HCW. I then got a number of return tweets from the likes of Helen Branswell, Ian M Mackay and others who disagreed with that line of thought.

When Helen and Ian ‘guide and advise’ it’s probably worth not disregarding that advice. Upon some personal review I decided that perhaps I had taken a too hard Workforce Planning line to my job functions without fully considering the clinical implications.

I have subsequently reviewed my thinking and have re-organised my data along the following lines.

Health Practitioners/Technical Operations (nee HCW) are any job title or function that is included in the Bureau of Labor Statistics SOC Occupations 29-0000 Healthcare Practitioners and Technical Occupations PLUS any clinical function that is included within the 31-0000 Healthcare Support Occupations, such as Nursing Assistants.

I am continuing to track Health Care Support personnel (there are four job titles already identified in the MERS data including Health Clinic Admin Officer, Health Domain Worker, Hospital Employee, Hospital Receptionist) as I believe the differentiation from HCW is important but I am including their data in job family charts and infographics.

In the end, I made a bad call and I thank those of you who took the time to correct my thinking.

Flublogia is certainly a community and one I truly appreciate being involved in.

Random Analytics: MERS-CoV in the Middle East (to 3 Jun 2014)

1 - MERSinMidEast_Infographic_140603

***** Please note that this infographic of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was updated with public source information to 1800 4 June 2014 EST *****

I was always planning on updating my MERS-CoV infographic at the end of May but the own-goal by the Saudi Ministry of Health, having suppressed the details of at least 113-cases and 92-deaths and the sacking of the deputy Health Minister Professor Ziad A. Memish made this update an absolute necessity.

The MERS-CoV in the Middle East infographic displays cases and deaths according to each reporting country (rather than onset country which has become confused over the course of the disease). The primary data source is the latest ECDC update and the most recent figures released by the Saudi Arabian MoH (to 3 June 2014).

Many journalists and flublogists have already started to comment on the deeper meanings behind the ‘exemption’ of Professor Memish from work and the suppression of data over a very long period. One of the best articles I have read on it today came from Crawford Kilian via H5N1. How MERS Could Topple the House of Saud, and Beyond. Excerpt:

A recent book argues that Saudi Arabia and its Gulf neighbours are “rentier states,” living off the revenues from oil. Some of the oil money is distributed in a kind of ethnic socialism: native-born Saudis and Emiratis get cheap housing, education and fuel, as well as undemanding government jobs. In return, they allow the monarchies to do as they please.

Part of this “ruling bargain” is to import cheap labour in vast numbers, for everything from housecleaning to business management. The money and working conditions are atrocious, but usually better than those available at home. One of the benefits of the ruling bargain is a good health-care system, and the Saudis have an extensive one. In many ways, it is indeed good. The previous health minister, Abdullah Al-Rabiah, is a Canadian-trained surgeon who recently separated conjoined twins.

But that was after he got the sack. As health minister, Al-Rabiah had presided over the rise and spread of MERS as a Saudi disease. While cases were seen in Jordan in March and April of 2012, the virus was first identified in a Saudi patient a few months later. Ever since then, the vast majority of cases have affected either Saudis or visitors to the Kingdom; the other Gulf monarchies have seen cases too, but far fewer.

Al-Rabiah’s strategy was to say as little as possible about the cases and to spin what he couldn’t conceal. While the World Health Organization and other agencies worried about what was going on, the Saudi Ministry of Health stonewalled them. But the minister couldn’t conceal the fact that cases were breaking out right inside Saudi hospitals.

I would agree with most of what Crawford is saying with the exception that the previous health Minister Abdullah Al-Rabiah wasn’t spinning the data, he was ‘Juking the Stats’.

So, what is the difference between spinning the data and juking the stats and why is this important in our understanding of MERS?

The answer is that when a government, organisation, company or individual spins the data what they are doing is looking at relatively ‘clean’ data and then using that information to either spin the results or emphasise a point for a positive or negative outcome. You might not realise this but most Western governments spend a lot of time and treasure on doing this as they try to drive home a political message. A fair amount of my time as a Workforce Planner was spent spinning data (aggressive forecasting of human resources in future quarters as an example).

What the House of Saud has been doing is the authorisation and implementation of ‘Juked Stats’ policy.

In my humble opinion, what this effectively means is that the Minister, the deputy Minister, various minions, governmental hospitals and private hospitals that receive government funding were given a number of MERS reports to state for official publication and that the World Health Organisation would not be informed of the real numbers (which would then become a Disease Outbreak Notification).

Two key points:

Point 1: The fact that we now find that 20% of cases and >30% of deaths went unreported since May 2013 is a clear indication that the Saudi’s had a clear policy of underreporting for political reasons. The fact that Professor Memish got sacked a day after the juked figures were revised was (again IMO) a way to quietly point the figure at the patsy so the regime could say it had cleaned house.

Yet, even as a doctor, Professor Memish was a very highly placed bureaucrat who had been politically vetted by the regime who asked him to deliver a result. When the disease spun out of his control and Memish couldn’t deliver the requirement the regime quietly ‘exempted’ him from the story. Having myself been involved in the ‘Juking of Stats’ I can state without qualification that if my numbers had of been bad my boss would have been quietly let go (with a decent payout) and the CEO would have moved on. That’s the game.

Point 2: The data errors go back as far as May 2013 yet it is interesting that the Saudi’s have ‘come clean’ on their data errors just a month after the first case hit America. That detail alone might be worthy of some deeper investigative journalism.

To finalise, the Saudi’s are telling us that they have now come clean on their data errors. Given they have never been clean to date I still don’t believe them.

Post Note: As Ian Mackay just reminded me, I should also state that I don’t believe the new Saudi data because of a conspiracy theory, because conspiracies require a brain-trust and this looks like just an ongoing cock-up!

Random Analytics: MERS-CoV in the Middle East (to 26 May 2014)

1 - MERSinMidEast_Infographic_140527

***** Please note that this infographic of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was updated with public source information to 1300hrs 27 May 2014 EST *****

MERS-CoV has just hit Iran for the first time so I was trying to get the most up-to-date information on the virus spread but all the numbers are a little dated or tainted at the moment so I thought to make sense of it myself.

The above infographic is a look into the MERS-CoV with specific emphasis on its cases within the Middle East. The data is taken primarily from the latest ECDC update along with the current update from the Saudi Arabian MoH (to 26 May 2014) plus a little guesswork from myself (see appended). Unfortunately, given the five day delay in the most recent ECDC update (and errors within that update including an incorrect total of deaths in KSA) I wasn’t able to match the 680-cases (as per FluTrackers) to the public sourced data.

Here is my best guess today:

Middle East:

  • Saudi Arabia: 562 cases/179 deaths (official KSA MoH total)
  • United Arab Emirates: 67 cases/9 deaths
  • Jordan: 17 cases/5 deaths (+8 cases since 16 May ECDC update & 1-fatality)
  • Qatar: 7 cases/4 deaths
  • Kuwait: 3 cases/1 death
  • Oman: 2 cases/2 deaths
  • Iran: 2 cases/0 deaths (+2 cases since 16 May ECDC update)
  • Egypt: 1 case/0 deaths
  • Yemen: 1 case/1 death
  • Lebanon: 1 case/0 deaths

Europe:

  • UK: 4 cases/3 deaths
  • Germany: 2 cases/1 death
  • France: 2 cases/1 death
  • Italy: 1 case/0 deaths
  • Greece: 1 case/0 deaths
  • Netherlands: 2 cases/0 deaths

Africa:

  • Tunisia: 3 cases/1 death

Asia:

  • Malaysia: 1 case/1 death
  • Philippines: 1 case/0 deaths

Americas:

  • United States of America: 2 cases/0 deaths

The ECDC notes in its 18-24 May Update that:

Nineteen cases have been reported from outside the Middle East: the UK (4), France (2), Tunisia (3), Germany (2), USA (2), Italy (1), Malaysia (1), Philippines (1), Greece (1) and Netherlands (2). In France, Tunisia and the UK, there has been local transmission among patients who had not been to the Middle East, but had been in close contact with laboratory-confirmed or probable cases. Person-to-person transmission has occurred both among close contacts and in healthcare facilities.

No one’s numbers agree so I’m looking forward to the next ECDC update so I can work out the anomaly. That aside, given the newly reported cases in Iran I felt the infographic needed to be updated just to highlight its continuing international spread.

Random Analytics: MERS by Key Occupation (to +300)

After some great suggestions by Anil Adisesh I have found a way to include three levels of complexity into my epidemiological database while only presenting two levels of charts. More work for me but I needed the push from the medical community to make it happen.

For those who have previously looked at my epidemiological/occupational charts (mainly H7N9/MERS) they will see a big uptick in numbers as I add Retirees (Provisional) to my count. The detail will be in my notes but I am now treating those over a certain age (dependent on national legislation) as retirees unless the State in question gives me some the World Health Organisation suggested occupational details.

Presented are the updated Middle Eastern Respiratory Syndrome – Corona Virus (MERS-CoV) by Occupation charts:

***** Please note that all infographics for this MERS-CoV article are using publically sourced information to 1800hrs 21 May 2014 (EST) with n=652 *****

01 - MERSbyJobFunction_140521

This infographic looks at those infected with MERS-CoV by Job Title. Some job titles do ‘roll-up’ in terms of function, thus a Nurse and a Nurse (ICU) are shown under the same horizontal data-point (see Key Notes).

Key Notes:

  • Retirees (1) there are 137-retirees represented in this chart but only 1/137 can be confirmed (less than 1%). According to the Saudi Arabian Shoura Council the official retirement age for citizens is now extended from 60 to 62 (effective 21 May 2014) but this does not include female citizens (55?) or residents (reducing from 60). The other country of interest is the United Arab Emirates where the retirement age is 65. In terms of my occupational data anyone over the age of 63 (KSA) and 66 (UAE) is considered retired unless their occupation data is known.
  • Farm Owners (*2*) includes Camel Breeders & Farm Owners (Camels). Doctor (*3*) includes Doctor (ICU). Farm Employee (*4*) includes Shepherd. Nurse (*5*) includes Nurse (ICU). Hospital Employee (*6*) includes Hospital Domain Worker.
  • Health Care Workers (*7*) excludes Paramedics (6), Dermatologists (1) and Pharmacists (1).***** Please note that this infographic of MERS was updated with public source information to 1800hrs 21 May 2014 (EST) with n= 652 *****Key Notes:
  • This infographic looks at those infected with MERS-CoV by Job Family. In short I think this is a key infographic for MERS as it gives you some confidence in the key narratives (i.e. that Health Care Workers are over represented in the data as an example).

Next chart, Job Families:

02 - MERSbyJobFamily_140521 

This infographic looks at those infected with MERS-CoV by Job Family. In short I think this is a key infographic for MERS as it gives you some confidence in the key narratives (i.e. that Health Care Workers are over represented in the data as an example).

Key Notes:

  • The most represented by the data are Non-Participatory. It should be noted that I don’t believe that this data is a true representation and there is a lot of ‘hidden’ Pilgrims, Employees (unspecified) and Tourists in this data;
  • Healthcare Prac/Tech Ops are overrepresented in the known data, due to significant outbreaks in hospitals across Saudi Arabia. This is now (in my mind) a proven data point as the new Health Minister, Adel M. Fakieh, has effectively suppressed any new data on HCW infections since he took over the job but they still represent 16.7% of my data;
  • Healthcare Support gets a mention (finally). At less than 1% (confirmed) I think the actual number is much higher given the good data comes out of the UAE. The Saudi’s (again) are not discussing HCW but having worked in an Operating Theatre myself as a non-HCW (I was an Anaesthetic Secretary) it is easy to see how these workers become infected;
  • Paediatric(s) only make up 2.8% of the data inputs. Seems low, especially compared against H7N9 but I’m no virologist, just an amateur flublogist.

Last chart.

02 - MERSbyMainJobTitle_140521

The last chart looks at those overall main job families that are most impacted by MERS-CoV (specifically Farmers, Travellers, Paediatrics, Retired, HCW’s, Other and Unknown).

Key Notes:

  • Farmer (2.0%): It is thought that MERS-CoV is initially spread by the handling of camels. Not represented by the known data so probably underrepresented or the wrong narrative.
  • Traveller (1.2%): One of the great concerns was of pilgrims and tourists spreading the disease far and wide. Again, not strongly represented by the data. I suspect it is suppressed data.
  • Paediatrics (2.8%): Any children reported between 0 – 14 years of age are here. Data doesn’t seem to show strong family clusters but I wonder given the P2P data we do know (amongst HCW’s) seem to show strong secondary infections amongst close working colleagues.
  • HCW (16.9%): Health Care Workers of any description but doesn’t include Health Support workers. Often a good indicator of secondary infections potency. Subject Matter Expert(s) on HCW infections are m’coll’s Ian Mackay and Maia Majumder.
  • Other (3.1%): All other occupations that have been publically released.
  • Unknown (53.2%): Unknown occupations. It should be noted that I have ‘guessed’ 136 occupations as ‘Retired’.

Final Thoughts

I now call on Professor Crawford Kilian to add Adel M. Fakieh to the Supari Prize list along with the previous Saudi Health Minister. As many have noted although we saw an initial uptick in publically sourced data from the Saudi MoH the data has now precluded data around occupation (HCW specifically) and expatriate status. This is now pure suppression of data and will no doubt lead to more cases ‘exporting’ from the Kingdom to other countries, including the United States which has now experienced two exported cases and one secondary infection.

Random Analytics: MERS-CoV in the Middle East (to 16 May 2014)

1 - MERSinMidEast_Infographic_140517

***** Please note that this infographic of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was updated with public source information to 2100hrs 17 May 2014 EST *****

The above infographic is a look into the MERS-CoV with specific emphasis on its cases within the Middle East. The data is taken primarily from the latest ECDC update (see appended) plus the most recent update from the Saudi Arabian MoH (care of Al Jazeera). Since I last updated this infographic back in November 2013 the cases have exploded, especially in Saudi Arabia and the United Arab Emirates. New Middle East countries have also been added since November including Egypt, Lebanon and Yemen.

The European Centre for Disease Prevention and Control has released its latest update on the MERS-CoV. Epidemiological update: Middle East respiratory syndrome coronavirus (MERS-CoV) for 16 May 2014. Excerpt:

ECDC notes the decision of Margaret Chan, the Director General of WHO, on 14 May 2014 not to call the Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak a Public Health Emergency of International Concern (PHEIC) as the conditions have not been met yet. This decision was based on the advice of the WHO Emergency Committee under the IHR on MERS-CoV. However the committee indicated that, based on current information, “the seriousness of the situation had increased in terms of public health impact, but that there is no evidence of sustained human-to-human transmission.”

Since April 2012 and as of 16 May 2014, 621 cases of MERS-CoV infection have been reported globally, including 188 deaths.

On 11 May 2014 a second imported case of MERS-CoV was confirmed by the United States’ Centers for Disease Control and Prevention.

On 13 May 2014, National Institute for Public Health and the Environment (RIVM) in the Netherlands reported the first imported case of MERS-CoV in the country. On 15 May 2014 a second case, who travelled with the first case, was reported.

Confirmed cases and deaths by region:

Middle East:

  • Saudi Arabia: 511 cases/160 deaths
  • United Arab Emirates: 67 cases/9 deaths
  • Qatar: 7 cases/4 deaths
  • Jordan: 9 cases/4 deaths
  • Oman: 2 cases/2 deaths
  • Kuwait: 3 cases/1 death
  • Egypt: 1 case/0 deaths
  • Yemen: 1 case/1 death
  • Lebanon: 1 case/0 deaths

Europe:

  • UK: 4 cases/3 deaths
  • Germany: 2 cases/1 death
  • France: 2 cases/1 death
  • Italy: 1 case/0 deaths
  • Greece: 1 case/0 deaths
  • Netherlands: 2 cases/0 deaths

Africa:

  • Tunisia: 3 cases/1 death

Asia:

  • Malaysia: 1 case/1 death
  • Philippines: 1 case/0 deaths

Americas:

  • United States of America: 2 cases/0 deaths

Most cases have either occurred in the Middle East or have direct links to a primary case infected in the Middle East. Local secondary transmission following importation was reported from the United Kingdom, France, and Tunisia.

Random Analytics: MERS by Occupation (to 150 confirmed)

According to Flutrackers there have been 580-cases of MERS-CoV that have been clinically diagnosed. The fatality count is a little harder to gauge given the poor data that comes out of the Middle East but Dr Ian Mackay via his blog Virology Down Under believes the number to be 161 out of 571-cases (a Case Fatality Rate of 28.2%). His total does not include the three deaths that were announced by the Saudi Ministry of Health (MoH) overnight.

In the past 24-hours the Centers for Disease Control and Prevention (CDC) have announced the second imported case of the Middle Eastern Respiratory Syndrome (MERS-CoV). All the details have not yet been confirmed but the second case, like the first was in a returning Health Care Worker.

Since the 28th April the Saudi MoH has cut all details about cases involving Health Care Workers and resident/citizen status. Even so, I have been able to detail 151-job titles including the most recent Health Care Worker who travelled from Saudi Arabia to the United States and was hospitalised in Florida.

1 - JobTitle_MERS_Top20_140513

 

Looking at the Job Titles the stand out point is that 47.7% of the data is associated with the occupation of ‘Health Care Worker’. This could be anyone occupied as an anaesthetist, dentist, doctor, lab-tech, midwife, nurse, optometrist, pharmacist, surgeon or even veterinarian. One of my chief complaints about occupation data being given (outside of outright suppression) is that the term ‘Health Care Worker’ lacks detail and is little more than a ‘throw-away line’.

That aside the leading occupations are Health Care Worker (47.7%), Nurse (13.9%), High School (12-14) at (4.6%), Primary School (5-11) and Pilgrims (both at 3.3%).

Points of interest:

  • There are currently 9 different Health Care Workers job titles that have confirmed… They include Nurse (21); Paramedic (6 – currently counted as a HCW), Doctor (4), Nurse (ER – 1), Health Domain Worker (1), Doctor (ICU), Pharmacist (1 – currently counted as a HCW), Respiratory Therapist (1) and a Surgeon (1).
  • The current average age of the 22 confirmed Nurses is 37-years;
  • Of the 22 confirmed Nurses, 17 are expatriate workers and five have not been confirmed by the relevant Ministry as either a resident or citizen;
  • Nine Farm Owners have been confirmed but only two Farm Employees which might suggest that Farm Owners (citizens) are being tested but their Farm Employees (often poor residents) have not been tested or their details are being suppressed.

2 - JobFamily_MERS_140513

The key data-point in the Job Family chart is that 74% of the occupation data is unknown. When we roll up all the Job Titles that we do know into their relevant Job Families the top-3 groups are:

  • Healthcare Prac/Tech Ops (67.7%) comprising Doctors, HCW, Nurses, Specialists and Surgeons);
  • Paediatric (10.6%) a new group that I have created recently to split apart Non-Participatory into more useful datasets. The Paediatric groups comprises Child (0-4), Primary School (5-11) and High School (12-14);
  • Farming, Forestry and Fishing (7.3%) comprising Camel Breeder, Farm Employee, Farm Owner and a Shepherd.

Of interest:

  • I just cannot believe that only four Pilgrims and four Tourists have become infected. I think this is a key area of data suppression and probably due to the fact that the Hajj and Umrah bring in huge tourism revenues into the Kingdom. According to Albawaba the Hajj alone added 3% to Gross Domestic Product in 2012 (or roughly $16.5-billion);
  • Paediatric cases only make up 2.8% of the data. I don’t see a lot of virology commentary on this but it seems low given that MERS seems to be able to spread within family and hospital clusters.
  • The MERS data has thrown up the first Healthcare Support worker, a Hospital Receptionist who was diagnosed in Jeddah, KSA. I also suspect the Health Domain Worker to be in this category but without specific detail I left it in the Healthcare Prac/Tech Ops Family.

FINAL THOUGHTS

With just one in four cases being confirmed for occupation I’m not sure that any reporting on the subject adds much to the level of public knowledge about the causes and progress of MERS outside of the fact that the spike in HCW in April points to a lack of infection control in Saudi hospitals.

Suppression is a strong term but as noted in the opening paragraph the Saudi’s have not provided any detail into occupation or resident/citizen states since the 28th April.

The Saudi’s have their reasons for this (and they cannot be good). Sometimes a lack of data can be just as enlightening as lots of it.

Random Analytics: Comparing H7N9 and MERS by Key Occupations

“Theatre Staff Nurse | King Faisal Specialist Hospital, Riyadh! Excellent tax-free income | 54 days annual leave | Free & secure furnished accommodation | Free medical insurance & emergency dental | and much more!” Online advertisement (7 May 2014).

There has been volumes written recently about the amount of Health Care Workers who been impacted by the Middle Eastern Respiratory Syndrome (MERS-CoV) in the past month after a surge of Saudi Arabian cases in April. Given the discussion I thought I might add my two cents worth.

Here are two charts, focusing on the H7N9 outbreak in China and one for MERS:

01 - H7N9_MainOccupations_140507

***** Please note that this infographic of H7N9 was updated with public source information to 1800hrs 7 May 2014 (EST) with n=435 *****

01 - MERS_MainOccupations_140507

***** Please note that this infographic of MERS was updated with public source information to 1800hrs 7 May 2014 (EST) with n=506 *****

H7N9 & MERS by Key Occupation

The first chart displays three key occupations, an age cohort and two other groups for H7N9 (China). The groups include:

  • Farmer (21.4%): It is thought that H7N9 is spread primarily by the handling and eating of incorrectly cooked poultry so the publically sourced information on occupation type has focussed on farming as a key vector for H7N9.
  • Retired (14.3%): Chinese retirees have been adversely impacted by this disease, it is thought because they take on significant family responsibilities such as shopping (at live markets) and cooking.
  • Paediatrics (6%): Any children reported between 0 – 14 years of age.
  • HCW (0.5%): Health Care Workers of any description. Often a good indicator of secondary infections potency.
  • Other (18.6%): All other occupations that have been publically released.
  • Unknown (39.3%): Unknown occupations.

The second chart displays three key occupations, an age cohort and two other groups for MERS-CoV (Middle East). The groups include:

  • Farmer (1.4%): It is thought that MERS-CoV is initially spread by the handling of camels.
  • Traveller (1.2%): One of the great concerns was of pilgrims and tourists spreading the disease far and wide. Although not a primary occupation while on pilgrimage or holiday you are not working so created a new non-employment type for this activity.
  • Paediatrics (2.8%): Any children reported between 0 – 14 years of age.
  • HCW (20.4%): Health Care Workers of any description. Often a good indicator of secondary infections potency.
  • Other (1.6%): All other occupations that have been publically released.
  • Unknown (72.9%): Unknown occupations.

Looking in the Wrong Direction

To the best of the Flublogia community’s knowledge, the Chinese medical authorities have worked very diligently on updating the World Health Organisation on key information. Many WHO updates have included an update on individual cases exposure to chickens and if there occupation was farming. Some provincial governments also release more detailed information which includes the person’s occupation. One of my issues with the Chinese occupational data is the level of detail, especially around farming (my whinge can be found here).

As for the MERS occupational data the first point that needs to be made is there is not enough data (publically available occupation data for MERS sits at just 27%). What data that is there is dominated by Health Care Workers who represent 74% of the known occupations (at least according to my Excel and I dig a little harder for this stuff than most other flublogists that concentrate on the medical side). Two points to be made here:

  1. The fact that Health Care Workers dominate the occupational space in MERS-CoV is important but given that HCW are usually secondary infections it is not as important as finding a possible primary occupational vector. An example of a primary occupation might include farming or racing, especially those that might relate to the camel industry.
  2. If you are going to explore the surge in Health Care Worker cases then start to limit the use of the term ‘Health Care Worker’. Health Care Workers are legion in titles, roles, functions and job families. Without going into detail about grades a great example would be a Nurse with specialities in A&E, Aged Care, Child Health, Community, ICU, General, Midwifery, Neo-Natal, Paediatric, Psych and Theatre. I commenced this blog with a live job ad for King Faisal Hospital in Riyadh looking for Australian and New Zealand Theatre nurses (Registered, two years minimum Theatre experience).

To sum up, the attention given to Health Care Worker cases in the current MERS-CoV outbreak and the almost 7 out of 10 lack of detail on other occupations might make for scary charts but it is not the main game. Stop MERS in the field and you stop MERS in hospitals.

Upcoming Occupational Data Issues

I also wanted to list some other ongoing concerns I have with the level of information coming out about H7N9 and MERS-COV as it relates to occupation data.

H7N9

  1. The level of occupation data supplied by China has dropped significantly in 2014. I note that to the end of 2013 that information was publically available for 75% of all cases but over the past four months that figure has dropped to 60%. Of the past 50-cases occupation have only been supplied on 5 (just 10%).

MERS-CoV

  1. The Kingdom has buried any mention of pilgrims catching the disease and the only real confirmations come from those who travelled to or through Saudi Arabia and returned to Europe, Tunisia or Malaysia. 1.2% for pilgrims and tourists is way to low and I would expect that a fair section of the unknown(s) is in this category. I’ll continue to chase up.
  2. I noted that I could account for five ‘Farm Owners’ but of all the cases I can only identify one ‘Shepherd’. Where are all the farm employees on this list? (My guess is they could lack access to medical facilities as they are more likely to come from poorer migration countries).
  3. On that note, The Guardian recently released a story detailing the almost 1,000 construction workers who have already died building the FIFA World Cup facilities in Qatar. One of the main causes of death listed is a heart attack. Many of these workers live in cramped and neglected accommodation (if it can spread in hospitals…) As yet I haven’t seen any construction occupations included in the publically available information. Could there be Qatari migrant workers dying of MERS and not being investigated.
  4. Although the previous KSA Ministry of Health news releases were noted for their lack of content one change that should be noted is that under the new system the difference between citizen and resident cases is no longer being noted. In a country that is made up of 20% foreign workers linking this data (along with expatriate country) can be critical in seeing patterns, such as issues with secondary hospital infections.

There is more but that’s enough for now.

QuikStats: MERS-CoV in the Arabian Peninsula (Nov 2013)

“No to slavery … That is not a world we will accept … Not here. Not overseas. Not anywhere.” Former Prime Minister of Australia, Julia Gillard (8th March 2013) who will be speaking at the 2013 WISE Summit: Reinventing Education for Life in Doha, Qatar (29-31 October 2013)

1 - MERSinMiddleEast_Infographic_131120

***** Please note that this infographic of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was updated with public source information to 1200hrs 20 November 2013 EST *****

The world’s top virology experts have watched the recent Hajj very closely, as has the world’s media since it first came on the scene in April 2012. It initially sprung up in Jordan but was soon exported to Saudi Arabia which has taken the hardest hit from the disease. As I write this blog 125 persons are confirmed to have caught the disease in the Kingdom, with 54 of them dying).

Of concern were the 2-million pilgrims who would be travelling together to the various sites (numbers were down approximately 1/3rd on recent years, possibly due to MERS-CoV). Although sometimes cramped the Hajj is generally well organised and supported including health and vaccination facilities. Some very good writers have expressed doubts about the data coming out of Saudi Arabia but the Hajj is behind us now. It seems that outside of some individual cases, as the possible French case highlights, major concerns about Saudi Arabia and the Hajj might have overblown.

Perhaps those same concerns should be directed at Qatar and the conditions of those who are building the FIFA World Cup stadiums for 2022?

Qatar has a population of just 1.9-million, of which only 15% are Qatari. In 2012, the country’s Gross Domestic Product per capita was the richest in the world at $89,736 (compare that to Australia $62,003, Canada $51,554, US $48,113, KSA $24,116 or Yemen $1,361). Yet a lot of the country is actually populated by very poor foreign workers who make up 94% of its total workforce.

Recently The Guardian newspaper has highlighted the abject conditions of those working on construction sites. In the first article the International Trade Union Confederation has estimated that at current numbers the construction of FIFA World Cup facilities will cost around 4,000-lives mostly via heat related illness or workplace incidents, although the data is sketchy at best (and non-existent at worst).

In another article Revealed: Qatar’s World Cup ‘slaves’ the newspaper investigates and documents multiple cases of workers being abused and living in awful conditions. Excerpt:

According to documents obtained from the Nepalese embassy in Doha, at least 44 workers died between 4 June and 8 August. More than half died of heart attacks, heart failure or workplace accidents.

The investigation also reveals:

  • Evidence of forced labour on a huge World Cup infrastructure project.
  • Some Nepalese men have alleged that they have not been paid for months and have had their salaries retained to stop them running away.
  • Some workers on other sites say employers routinely confiscate passports and refuse to issue ID cards, in effect reducing them to the status of illegal aliens.
  • Some labourers say they have been denied access to free drinking water in the desert heat.
  • About 30 Nepalese sought refuge at their embassy in Doha to escape the brutal conditions of their employment.

And another excerpt which mentions the living conditions:

The Guardian’s investigation also found men throughout the wider Qatari construction industry sleeping 12 to a room in places and getting sick through repulsive conditions in filthy hostels. Some say they have been forced to work without pay and left begging for food.

“We were working on an empty stomach for 24 hours; 12 hours’ work and then no food all night,” said Ram Kumar Mahara, 27. “When I complained, my manager assaulted me, kicked me out of the labour camp I lived in and refused to pay me anything. I had to beg for food from other workers.”

For those working and living in cramped filthy conditions or working long arduous days without proper food or hydration would be more at risk to just a seasonal flu. What about the practice of going to work when ill or ‘presenteeism’? How many of the 85% of non-Qatari’s in the monarchy have access to decent medical help.

With 44 Nepalese dying in just 66-days and a further 82 Indians dying in the first five months of this year in work related incidents it seems trite to concern ourselves with a relatively small outbreak of a disease which only caused two deaths in 2013.

As I write this post in late October MERS-CoV has been confirmed in just seven cases in Qatar with two onsets in recent weeks.

I’m not trying to suggest that all migrant workers in that country are going to get the virus it does seem a more likely vector than the better organised and supported Hajj pilgrimage.

As I did with the recent MERS-CoV infographics I’ll keep the infographic updated as new information comes to hand through to the end of November. Here is a copy of the original infographic posted with data to 29 October 2013:

2 - MERSinMiddleEast_Infographic_131029

Acknowledgements: Data for this infographic was sourced largely from CIDRAP, H5N1, FluTrackers and the WHO. Background reading supplied mainly via Pandemic Information News, Ian at Virology Down Under and Helen Branswell.

Updates

30 Oct 2013 – Via H5N1Oman: Sultanate reports first MERS case;

1 Nov 2013 – Via H5N1: Dr. Mackay reflects on the latest MERS cases;

3 Nov 2013 – Amendments to infographic as suggested by Crawford Kilian (detailing methodology);

7 Nov 2013 – Via H5N1: Dr. Mackay has questions about the Spanish MERS case;

8 Nov 2013 – Via CIDRAP: UAE, Saudi Arabia report 3 more MERS cases;

9 Nov 2013 – Via H5N1: Qatar: New MERS case is an expatriate;

11 Nov 2013 – Via H5N1: Oman reports first MERS death;

12 Nov 2013 – Via GulfNews.com: Omani visitor dies from Mers virus in Abu Dhabi emirate (h/t Helen Branswell);

17 Nov 2013 – Via H5N1: CIDRAP: MERS death toll rises as WHO confirms 2 cases and Kuwait: Some details on the second MERS case;

20 Nov 2013 – Via H5N1: CIDRAP: Saudi Arabia reports 2 more MERS cases;

QuikStats: MERS-CoV in the KSA (October 2013)

“People need to be careful in a very generic way, such as ensuring good hand hygiene. We would normally tell people to avoid very crowded situations, but obviously in this case, with the Hajj, that is unrealistic.” (Richard Brown, Regional adviser for communicable disease surveillance and epidemiology for WHO’s South East Asia Regional Office, 4 October 2013)

1 - MERSinKSA_Infographic_131101

***** Please note that this infographic of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was updated with public source information to 1200hrs 1 November 2013 EST *****

With just days to go until the HAJJ, the largest gathering of Muslims in one place each year and more than a year after the first cases of MERS-CoV came to our attention I thought it might be worthwhile concentrating on the Kingdom of Saudi Arabia this month.

The above infographic shows the distribution of MERS-CoV by onset province in the Kingdom. I have chosen to use the FluTrackers.com methodology and include one of the first victims who was actually a UK citizen, thus my numbers won’t match those that are officially noted by the Kingdom of Saudi Arabia Ministry of Health.

Two points that were made clear to me during my research into the KSA MERS-CoV figures is that the basic data is awful; a far cry from what has been made available from the Chinese during their H7N9 outbreak. I won’t say too much more on that as many including Helen Branswell, Crawford Kilian and Ian M. Mackay have all commented about this for some months now but I would ask if anyone can see an error in the infographic please correct me and I’ll remedy ASAP.

A lot of discussion has taken place about the potential for MERS-CoV to utilise the HAJJ as a springboard for a rapid escalation of spread. The second point and key take-away from the infographic has been that the Kingdom is a very large country with a concentration of cases in the Eastern side of the country. At the date of initial publishing (8 October) 92 of the cases were in the Eastern and Riyadh regions, making up 78% of the cases with at least 21 of those cases involving the Al-Ahsa medical facility cluster which should be a singular event. That’s not to say that MERS-CoV will not spread but certainly to date the axis of the disease in removed from the massive concentration of peoples in the Western part of the country.

Here is a copy of the original infographic posted with data to 8 October 2013:

1 - MERSinKSA_Infographic_131008_2of2

As I did last month with the global MERS-CoV I’ll keep the infographic updated as new information comes to hand.

For those that are travelling for HAJJ, safe travels and let’s hope there is not much in the way of news.

Inshallah.

Acknowledgements: Data for this infographic was sourced largely from CIDRAP, H5N1, FluTrackers and the WHO. Background reading supplied mainly via Pandemic Information News, Ian at Virology Down Under and Helen Branswell.