Tag: death

Age of COVID-19 deaths in Maryland

After my previous post on the age of COVID-19 cases in Maryland, it was logical that I write about the age of COVID-19 deaths in Maryland. So far, media and State Departments of Health all agreed that the older someone is, the more risk this person has to die from coronavirus.

So far, this is unfortunately also true in Maryland. In the graph below, we clearly see that people 50-59 years old have more than 250 deaths, people 60-69 have more than 500 deaths, people 70-79 have more than 750 deaths and people 80+ have nearly … 1,5000 deaths! The graph at the bottom also clearly shows that people in age categories 60 and above provide most of the new daily deaths due to COVID-19 (even if we came back down from a peak at about 40 deaths in 80+ at the end of April).

The simpler section at the latest date for which death data by age is available (i.e. today, July 9th, 2020) also shows this curve highly skewed towards older age groups (at the bottom, compare that to cumulative cases, on top):

The two graphs below confirm that people in old age are at much higher risk of death due to COVID-19. On top, if we report the deaths in each age group by the population they actually are in Maryland, we also see that deaths in 80+ disproportionaly affect this age group, reaching a COVID-19-specific mortality rate of 629 per 100,000 pop.!!! The table under the graph gives all the data points.

And when we look at it to see the relative importance of each age groups compared to the total number of cases, we see again that people aged 80+ have 46% of all deaths, followed by people 70-79 (25%) and people 60-69 (16%).

Age group (years old)COVID-19-specific mortality rate (per 100,000 pop.)
0-90
10-190.1
20-292.2
30-394.9
40-4913.1
50-5928.8
60-6970.8
70-79180.1
80+629.8
COVID-19-specific mortality rate, by age group, in Maryland, on July 9th, 2020

As opposed to cases by age, we don’t see here any shift in most affected age group: the older some is, the more risk of dying from COVID-19 exists (and part of the problem is the close living conditions in nursing homes). There aren’t 1,000 solutions to protect them: wear a mask and practice physical distancing, especially when there is a risk to meet elderly people and transmit the disease to them!

To be continued …

As usual, you’ll find other graphs on my page about COVID-19 in Maryland (and figures above are updated with new data as they appear) and the data, code and figures are on Github (including these ones).

MD counties COVID-19-specific death rate

Since a few weeks, I report the raw number of COVID-19 deaths in Maryland counties. If this gives an idea of the cumulative number of deaths – which is interesting – it doesn’t reflect the fact that some counties have more inhabitants than others. That’s why I plotted below the number of COVID-19 deaths adjusted for the population (i.e. the COVID-19-specific death rate):

(click to see more details)

Today (May 16, 2020), in terms of absolute number of deaths, Montgomery, Prince Georges and Baltimore County are the top 3 counties (this is the same for cases but not in the same order). In terms of confirmed deaths per 100,000 population, the top 3 counties are Kent, Prince Georges and Montgomery.

Rank on May 16, 2020Absolute # of COVID-19 deathsCOVID-19 deaths per 100,000 population
1Montgomery (423)Kent (66.9)
2Prince Georges (399)Prince Georges (43.5)
3Baltimore County (223)Montgomery (40.2)
4Baltimore City (192)Carroll (39.0)
5Anne Arundel (133)Charles (35.8)

Overall in Maryland so far, 1,842 deaths were reported – for a total population of 6,141,808. This gives a COVID-19-specific death rate of 29.9 per 100,000 pop. For comparison, the CDC reported a flu-specific death rate of 2 per 100,000 pop. (for the whole US, 2017) and 863.8 deaths per 100,000 pop. for all-cause deaths.

Source of Maryland County population: projections from the Maryland Department of Planning.
As usual, you’ll find other graphs on my page about COVID-19 in Maryland and the data, code and figures are on Github.

Edited a few minutes after publication to add a paragraph with the comparison with Maryland and flu; adapted the y-axis label following Michael Brown‘s comment on Twitter (thanks!); and specified the flu-specific death rate from CDC following Melissa Schweisguth‘s comment on Twitter (thanks too!).

Trend in Coronavirus cases in Maryland (3)

Following up on my two previous posts (here and here), I am writing a third post on COVID-19 in Maryland because I believe we enter a new phase.

Before continuing, please note that the same disclaimer as in my previous post applies here (in short: read the CDC and MDH websites for official information).

In the first phase, the importance was to detect and make sure COVID-19 patients were treated (also: make sure not to overwhelm the healthcare system, flatten the curve, lower the baseline, & stay at home!). My two previous posts were following these efforts, thanks to daily data released by the Maryland Department of Health (MDH) on its dashboard. My second post will still be updated with the latest data from there, go read it!

This first phase is not over yet but we started to see metrics states and governments will consider in order to “reopen”. Hence this second phase is adding specifically these metrics, again thanks to the Maryland Department of Health (MDH) on its dashboard (and probably other data sources that will be linked as I use them).

In Maryland, the Governor issues a Roadmap to Recovery on April 24, 2020. In this (easy to read) document, a lot of aspects are introduced and here is what will be tracked and for how long:

  • state public health officials should review the numbers of new COVID-19 daily case counts, hospitalizations, and deaths carefully” and “The results of reopening decisions will take 2 to 3 weeks to be reflected in those numbers.
  • the White House’s gating guidelines state that a 14-day downward trajectory of benchmark metrics – or at least a plateauing of rates – is required before recovery steps can begin, and before each additional recovery step can move forward

That’s why Governor Larry Hogan tweeted his focus on April 24:

Governor Hogan’s focus was informed in part by the Johns Hopkins Center for Health Security’s Guidance for Governors about Public Health Principles for a Phased Reopening During COVID-19 (PDF). There the proposed principles for action are:

States should consider initiating the reopening process when (1) the number of new cases has declined for at least 14 days; (2) rapid diagnostic testing capacity is sufficient to test, at minimum, all people with COVID-19 symptoms, including mild cases, as well as close contacts and those in essential roles; (3) the healthcare system is able to safely care for all patients, including providing appropriate personal protective equipment for healthcare workers; and (4) there is sufficient public health capacity to conduct contact tracing for all new cases and their close contacts

Public Health Principles for a Phased Reopening During COVID-19: Guidance for Governors, Johns Hopkins Center for Health Security, April 17, 2020.

On April 27, 2020, this is what we currently have … On the first chart, the number of positive tests is increasing (probably due to the increase of testing done), hospitalizations and deaths are slowly going up, overall. On the third chart, it seems the number of people in ICU is plateauing. Below these charts, I’ll post the updated charts as days are passing …

Updated charts (look at the date at the bottom right):

To be continued …

Evolution of the number and causes of death in Belgium (2010-2014)

Statbel, the Belgian governmental organisation for data and statistics, just released mortality data for 2014 (press release in French, dataset). The headline of their press release was that, for the first time, tumors were the first cause of death for Belgian men. Diseases of the circulatory system remains the main cause of death in Belgium, for women and for both sex together.

While the death of someone is a bad news in itself, I’m more interested here in the evolution of death causes. I’m interested in the evolution of causes of death because it might be a consequence of the evolution of the Belgian society and, as a proxy, of any (most) developed, occidental countries.

If you look at the data, the number of Belgians dying is stable and natural death is still the main cause (and also stable, around 93%). Note that if we look at data before 2010, it seems that mortality is slightly increasing since around 2005.

Evolution of the number of deaths in Belgium, all causes, 2010-2014

If the total number of deaths seems stable, the press release seemed to indicate that tumors (cancers) are on the rise, especially in men. The breakdown in categories is made following the international classification ICD-10 and, because the names of the different chapters are quite long for graphs, I will use the corresponding chapter numbers instead. Here is the key:

Chapter Header
I Certain infectious and parasitic diseases (A00-B99)
II Neoplasms (C00-D48)
III Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism (D50-D89)
IV Endocrine, nutritional and metabolic diseases (E00-E90)
V Mental and behavioural disorders (F00-F99)
VI Diseases of the nervous system (G00-G99)
VII Diseases of the eye and adnexa (H00-H59)
VIII Diseases of the ear and mastoid process (H60-H95)
IX Diseases of the circulatory system (I00-I99)
X Diseases of the respiratory system (J00-J99)
XI Diseases of the digestive system (K00-K93)
XII Diseases of the skin and subcutaneous tissue (L00-L99)
XIII Diseases of the musculoskeletal system and connective tissue (M00-M99)
XIV Diseases of the genitourinary system (N00-N99)
XV Pregnancy, childbirth and the puerperium (O00-O99)
XVI Certain conditions originating in the perinatal period (P00-P96)
XVII Congenital malformations, deformations and chromosomal abnormalities (Q00-Q99)
XVIII Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified (R00-R99)
XX External causes of morbidity and mortality (V01-Y98)

One thing to notice is that, for chapter IV, Statbel only counts categories E00 to E88 while the WHO includes 2 more, from category E00 to E90 ; I would assume here that it has no important impact. Also note that, below, R ordered the chapters in a strange way – I’ll see how to fix that.

Excluding natural causes, we see that indeed, diseases of the circulatory system (chapter IX) are still the first cause of death, followed by neoplasms (chapter II) and diseases of the respiratory system (chapter X). If we compare the relative ratio of all these causes (second graph below), we also find the same conclusion – but the relative decline in deaths due to diseases of the circulatory system is better shown. And we can see that neoplasms take back approximately the same relative percentage of death, in 2014 (although they returned to the absolute number of deaths of 2012, approximately).

Causes of death in Belgium, 2010-2014

Causes of death in Belgium, 2010-2014, relative numbers

The available data set doesn’t go into more details than numbers by ICD-10 chapters. Therefore we cannot tell from that what kind of neoplasm is the most prevalent or what kind of infectious disease is the most present in Belgium, for instance. The press release however mentions that respiratory, colorectal and breast cancers are the top three killers and that flu was not very present in 2014.

As the cancer occurrence is increasing with age, and as the Belgian population is aging, one of the explanation for a high number of deaths due to neoplasms can be age ; however we don’t see a dramatic increase of neoplasms (fortunately!). Another potential factor is the impact of screening for cancers. Due to a very intelligent political split (sarcasm!), prevention (and therefore screening) is not a federal duty. Therefore regions started different screening programs, at different times, with different results. Screening data and their results are therefore difficult to obtain. The Belgian Cancer Registry doesn’t publish data on screening in oncology – although its latest report (revised version of April 2016) very often mentions screening as a main factor for change in the number of cases diagnosed. In its 2016 report (PDF), the Flemish Center for the Detection of Cancer (Centrum voor kankeropsporing) indicates that they increased the number of women screened for breast cancer by more than 8% between 2011 and 2015 (especially in 2015), with a quality of test between 90% and 95%. They also showed an increase in cancer diagnostics (without linking it directly to the increase in screening).

screening-flanders

This is by no means an exhaustive review of the data. There are other potentially interesting things to look at: the geographical disparities between the three regions, the gender ratio evolution (as some of these diseases are known or by definition affecting more one sex than the other), etc.

It would also be interesting to follow these trends as some changes occurred recently in the Belgian curative landscape. New drugs in cancer immunotherapy were recently authorised and reimbursed, for melanoma, lung – and other indications will follow. These costs have a price (less than what is in the press, however, I may come back on this in a future post) but they delay death (unfortunately they don’t avoid it). However, for some of them, in some indications, their administration and reimbursement is sometimes also linked with screening, testing and prior treatment failure ; that might decrease their impact on overall mortality. New drugs for Hepatitis C also arrived in 2015 and 2016 and the Belgian health minister decided to reimburse these drugs for patients in their early stage 2 of the disease. Studies showed that treating at this stage may prevent hepatitis C from progressing to later stages and, in some cases, studies showed patients cured from the disease. This is an opportunity to see a decline in mortality due to this infectious disease (although it is already quite low – compared to other diseases).

The Top 5 Killers of Men

From Delicious, I saw that Yahoo had an article about the top 5 killers of men. I thought it would be nice to see from where they get there data.

First, I have to mention that the article is really about American men, nothing else (not about mankind, not about men around the world, not about women, children, etc.). The article is related to the US National Men’s Health Week (the US National Women’s Health Week was in May 8-14, 2011). Although the article is giving advices, there are no sources of information.

However, it’s rather easy to obtain these numbers …

For the US, the CDC FastStats website is a hub to data about health in the US. Here is the CDC ranking for the top 5 killers in 2007 (in both US women and men):

  1. Heart disease: 616,067 deaths
  2. Cancer: 562,875 deaths
  3. Stroke (cerebrovascular diseases): 135,952 deaths
  4. Chronic lower respiratory diseases: 127,924 deaths
  5. Accidents (unintentional injuries): 123,706 deaths

If you look at the whole world (data from the UN), the picture is somehow different! The UN ranking for the top 5 killers in 2008 (in both women and men) is:

  1. Lower respiratory infections: 1.05 million deaths
  2. Diarrhoeal diseases: 0.76 million deaths
  3. HIV/AIDS: 0.72 million deaths
  4. Ischaemic heart disease: 0.57 million deaths
  5. Malaria: 0.48 million deaths

All of them causes more than 45% of deaths around the world. These diseases with high-mortality vary in an important manner when we compare the USA and the whole world. The main caveat is that the data I presented above are for men and women. It would be interesting to use the UN data API project to dig further into details.

Jamie Oliver: Teach every child about food

In the latest TED Prize wish, Jamie Oliver, the “Naked Chef”, talks about teaching every child about food. His wish is:

I wish for your help to create a strong, sustainable movement to educate every child about food, inspire families to cook again and empower people everywhere to fight obesity.

Although I have a child and I’m obviously interested in his idea, I was also interested in the simple bar chart depicting the leading causes of death in the USA. In the tiny Flash video, the text is unfortunately barely legible and I was interested in knowing where he got his data from.

Leading causes of death in the USA from Jamie Oliver's TED talk

The answer is really easy: the leading causes of death in the USA are compiled every year by the (American) National Center for Health Statistics and the results are available on their FastStats website. So, for 2007 (the latest results at the time of writing), the 15 leading causes of death in the USA are (ordered by decreasing number of cases):

Rank Cause Number
1. Diseases of heart * 616,067
2. Malignant neoplasms (cancers) * 562,875
3. Cerebrovascular diseases * 135,952
4. Chronic lower respiratory diseases 127,924
5. Accidents (unintentional injuries) 123,706
6. Alzheimer’s disease 74,632
7. Diabetes mellitus * 71,382
8. Influenza and pneumonia 52,717
9. Nephritis, nephrotic syndrome and nephrosis 46,448
10. Septicemia 34,828
11. Intentional self-harm (suicide) 34,598
12. Chronic liver disease and cirrhosis 29,165
13. Essential hypertension and hypertensive renal disease 23,965
14. Parkinson’s disease 20,058
15. Assault (homicide) 18,361

The exact ICD-10 codes are in this report ; you can find their exact meaning here. Causes with an asterisk are related to food intake, according to Jamie Oliver.

Now you have the numbers, the origin of the data and the methodology used to collect these data. You can watch the presentation:

You’ll find a critique of Jamie Oliver’s talk by Presentation Zen.