The largest epidemiological study so far to the COVID-19 epidemic came out on February 18, published by the CCDC weekly by authors from Wuhan, Hubei, China.
Here is my summary; impressions are my own. The reason for me to write about this, is because I want to grasp the risks of living in Shanghai today- maybe the reader will find clues that, at this point in time, with a relatively young and healthy family, my concerns are limited. My interest is also professional in nature. Setting up a company in the domain of sustainable antibiotics, I fear that the loss of antibiotic production in China, due to the 2019-nCoV virus outbreak, will backfire terms of sustainable treatment options globally.
These days, the COVID-19 epidemic may seem to have passed its peak; but the authors from Wuhan warn for a possible rebound now Chinese travelers still plan to return from their extended New Year’s break. Some key takeaways from the study:
- At first: age. COVID-19 patients can be of all ages, with the most dominant age group centered around 50-69 years. Mortality however is very differently skewed. 90% of the deaths occur in people older than 50; 80% in 60+; 50% in 70+. In contrast, no one younger than 10 has died until February 10. Younger people seem to be less at risk to perish.
- Both men and women get infected, but males dominate with 64% in mortality.
- When looking at occupation, it is clear that retirees (following “others”) represent the highest mortality group. People working as farmer/laborer represent a large patient segment, and are slightly more at risk to perish too, compared to service industry and health workers. The mortality age distribution can explain mortality among retirees; but the elevated risk for farmers/laborers is a point of concern, which is not addressed in the paper.
- Given the demographic distributions, it would be important to fully characterize patients that fall ill outside Hubei province – the origin of the epidemic. It can be expected that the epidemic outside Hubei spreads via mobile, younger, people; a subgroup with it’s own spreading and disease characteristics (we have to keep in mind too that objects, such as money and goods, can also contribute to diseases spread). Such spreading information is probably out of scope and not specified in the paper. Such information would nevertheless be interesting for the development of longer-term monitoring and surveillance policies (for instance in and around elderly or health centers).
- When looking at co-morbidity (other illnesses in COVID-19 patients), it becomes clear that the health status of patients is not fully documented. In 53% of the patients, the health documentation is incomplete – and 60.3% of those who died fall within this category.
- We read that hypertension represents the biggest group to suffer from COVID-19. What’s more, this group represents nearly 40% of the mortality cases. Other diseases that increase the mortality are Cardiovascular disease (nearly 23% of all deaths) and diabetes (nearly 20% of all deaths).
- Please note that percentages cannot be simply added, as these diseases can occur simultaneously in one patient.
- Interestingly, COVID-19 being primarily seen as a lower pulmonary threat, those with chronic respiratory disease only represent a small part (2.4% of cases), although then represent nearly 8% of all deaths.
- Last, only people in critical condition have died: the symptom severity is predictive for the mortality risk.
The disease numbers may be the consequence of demographic distributions; if there are, for instance, more farmers, than it can be expected that farmers represent a larger group. It would have been informative if such distributions were provided, to define the disease risk in those categories. What is provided in the paper is the so-called “case fatality risk”, which represents the mortality within each category. The highest case fatality risk is disease severity, followed by age > 70 years; cardiovascular disease; diabetes; chronic respiratory disease; hypertension. (Please note that I have ignored the date of disease onset here).
I’d like to zoom in at the risk into comorbidity, as it may give us some clues on where to look for added risk factors. The following is the result of personal reasoning and not mentioned in the paper (in other words, it’s just a wild guess):
The virus 2019-nCoV that causes COVID-19 needs a landing spot in the human body. This landing spot is a protein called ACE2. ACE2 is a angiotensin converting enzyme, which plays a role in regulating our blood pressure, by decreasing it. People suffering from cardiovascular disease and high blood pressure are often prescribed ACE inhibitors. These compounds inhibit an enzyme called ACE (that increases blood pressure) but not the virus landing spot ACE2 (which decreases blood pressure).
Could ACE2 levels be elevated in case of high blood pressure? It would seem a natural thing to happen. At the same time, it has been found that the use of ace inhibitors can up-regulate ACE2, at least in heart and liver. Not an easy puzzle…
If up regulation of ACE2 happens one way or the other, it would be relevant to investigate this aspect towards COVID-19, for the following reasons:
- ACE2 is the landing spot for 2019-nCoV. The more ACE2, the more landing spots?
- ACE inhibitors have been associated to a vague symptom that relates to the lungs: a cough. Does ACE2 up-regulation lead to pulmonary dysfunction?
- High blood pressure is routinely under-treated in China. According to the WHO “In China, about 270 million people have hypertension; only 13.8% of the patients have their condition under control and not everyone who has hypertension can access treatment.” Does better disease management or prevention makes the population more resilient?
- Hypertension distribution in China follows the same age trend of the mortality due to COVID-19. However, this can also be said of lung cancer mortality, and tuberculosis (tuberculosis data from the UK). This may be coincidence, as aged people are generally more at risk. Having said that, there is a different trend, for instance, for breast cancer mortality. Can we break one trend if we break the other?
Given the challenges of public health globally, many of the issues described above could apply to any country. Also, it is not my intention to claim a potential golden bullet against COVID-19. Epidemics result from a chain of events, some as complicated as evolutionary forces, some as as simple as a contaminated door knob. Nevertheless, every piece of the puzzle could provide a point to prevent further escalation and enable long-term control.
Missing from the study are categories with that would be obvious candidates for risk factors. These include smoking and history of tuberculosis, for instance.
The authors conclude that there still is a lot to find out about the disease origin and transmission; and that developing monitoring and surveillance systems should continue.
Thanks to Boris Tefsen for his suggestions for this article.
This post was originally published on February 19, 2020