Updated on April 1st 2020, written by Dr David Owens.
Understanding COVID-19 in 9 simple questions.
All new diseases pose a potentially serious threat. As we discover more about this disease it seems to be less severe than first thought on a case by case basis. It mostly affects older people with coexisting illness, but if it spreads widely it can still have a significant impact on health systems. The final number of deaths will mostly be determined by the size of the epidemic and how widely it spreads. Delaying this spread gives us time to prepare, to develop tests and treatments and to minimise and ameliorate the potential long term cost in population terms. Here is an explanation of the rationale of the public health measures. The early containment in China has been unprecedented and has significantly reduced the potential size of the epidemic. We are fortunate to be living in a city with world class systems and expertise in the management of epidemics of infectious disease.
Mortality rates are calculated by dividing the number of deaths by the total number of cases of a condition. Early in epidemics we do not have an easily available test to diagnose the cases and there tends to be a bias to testing the sickest patients who tend to go to hospital. Measuring deaths in hospital (hard data) is always easier than measuring mild cases in the community (soft data) so hospital mortality rates early in epidemics tend to overestimate the final mortality. It is currently too early to say what the mortality rate of COVID-19 will be.
Imagine a condition of a new disease in which 100 people were admitted to hospital and 10 of them died. This would give a hospital case fatality rate of 10%. But now imagine that we develop a test which shows that only one in every 100 people who developed the illness in the community became unwell enough to go to hospital. The other 99 go to bed at home or some even keep working with sore throats or a mild cough. In this situation, there are actually 10,000 people with the illness, 100 who go to hospital and 10 who die. This means that the true mortality rate of this disease is 0.1%. This is the mortality rate of influenza. Here is a further explanation. This is also why the higher number of milder cases of COVID-19 that we find the less severe it will end up being on a case by case basis.
We will not be able to honestly critique and learn lessons until we have all the data available. It is easy to be wise after the event and hindsight is always 20/20. This epidemic has shown unprecedented and extraordinary collaboration in fighting a new disease about which, by definition, we had no information in December 2019.
1. Information about the Disease:
This helps to answer ‘what will happen to me or my family if we catch this illness? How severe is it? Will I die? Most questions and almost all media reports focus on this information.
2. Information about the epidemic:
This is information about how the disease travels and how it is behaving in different situations. This information allows us to assess the risk of catching the illness and how that risk is changing over time.
Of course an understanding of both is important but the disease gives information about the bad thing that may happen. This is the “What If?” question. This is like asking “What happens if I get struck by lightning?”. The answer is that you may die. In order to assess this risk and change behaviour it helps to understand the changing risk. Are you equally worried about being struck by lightning when you are playing golf in a lightning storm as you are sitting in the office working on a sunny day? The human brain is wired to mix up the severity of an event and the likelihood of an event happening. I have explained the implications of this glitch, with regards to epidemics, in a previous article.
It looks like this disease will have a mortality of 1% or less. However, the most important question is how likely is any individual to catch this illness. So far there have been 715 cases and 4 deaths in Hong Kong in a population of 7.4 million compared to more than 350,000 cases and 357 deaths from influenza last winter. The epidemic in China seems to be coming under control. This may change and the current very small risk may increase. To understand this change in risk it is important to understand the epidemic. I am updating the information about the epidemic and the epidemic curves here.
It is important to realise that there is a difference between taking this situation seriously and it posing a serious risk on an individual basis. This is a very serious illness in certain situations. For most people, it will be mild. The public health measures are aimed at protecting both the most vulnerable members of our society (the old, those with other illnesses and the socially disadvantaged) and preventing a surge on our hospitals and health system.
A more detailed explanation of the difference between a disease and epidemic can be found here.
The epidemic of anxiety is more pernicious, more infectious and more dangerous than the disease. The negative cognitive processing and the catastrophizing thoughts are leading to poor decisions. Financial markets are classically said to be driven by greed and fear. This is an extreme example of decisions being made in a way which are irrational but predictably so, given an understanding of the psychology of human decision making.
It seems inevitable that the negative impact of the economic fallout of COVID-19 will dwarf the mortality of the disease itself, whatever that may eventually be. Poverty is the single most important determinant of global health1 and economic growth is the most powerful determinant for reducing poverty2.
I discussed the risk benefit of the public health decisions in a previous article. China is now well on the way to normalising activity within the restrictions of ongoing containment. This epidemic has a doubling time of 7 days. Every week we have twice as much data as the week before. We have world class containment, control and mitigation systems in Hong Kong and if we do not want the economic damage here to harm the poorest members of our community we will eventually need to get the economy working again.
If this disease spreads widely it may well be declared a pandemic. This essentially means that there are clusters of infection spreading in multiple locations. H1N1 (Swine flu) was declared a pandemic in 2009. It is important to appreciate that controversy around the declaration of a pandemic is similar to the initial decision to label COVID-19 as a global emergency. There will be political factors in the decision which again balance the benefits of the release of funding and human capital against the increasing anxiety, confusion and potentially harmful decisions which may result from a label which has negative connotations beyond its meaning on the ground.
Uncertainty and lack of control are key features in stress and anxiety. The human brain is wired to feel uncomfortable with uncertainty. The best response to this is a rational challenge of prevailing beliefs ideally using an established anchor for risk.
I see a spectrum of potential scenarios for the evolution of this epidemic. For simplicity I will describe the range as below:
Whilst accepting the inevitable uncertainties involved in this evolving process the current data is suggestive of an outcome which is more likely to be closer to the best case than the worst case scenario. Ultimately this question will be determined by the effectiveness of containment strategies and the evolution of the epidemic.
We can all reduce the likelihood of suffering from this illness by following the public health advice of hand washing and social distancing in addition to focusing on health and well-being. We have produced some resources here.
It is important to rationally assess both the cost benefit of interventions and the lessons which can be learned, both from the past, and from current experience in this epidemic. The containment methods have been extraordinary. International teams are working on developing testing capacity, vaccine development and clinical trials to determine the best treatment regimes.
Finally, a totally counterintuitive analysis. Mortality in USA from Influenza since 1 October 2019 is 24,000-62,000. This is equivalent to 120-300 deaths per day. This winter influenza epidemic has been trending in severity above normal years in the USA, Canada and Europe. The numbers may reasonably be expected to be equivalent to 500-1,200 per day in China based upon a similar incidence and allowing for population difference. The current COVID-19 mortality is equivalent to 3-7 days of influenza mortality in China. In Hong Kong this year the CHP declared the end of the influenza outbreak after only 5 weeks3. This compares to last year in which the epidemic lasted for 14 weeks and resulted in 357 deaths including one child4.
It would be reasonable to assume that the reason for the shortened influenza epidemic is the recent public health measures including immunisation. The reduction of the epidemic by 9 weeks could reasonably be expected to reduce fatalities from influenza. Mathematical modelling for influenza incidence and mortality is not linear as incidence increases at the peak. Assuming a conservative reduction of 20% in fatalities by shortening of the length of the influenza season by 64% would be expected to reduce fatalities by 71 deaths compared to the 4 deaths so far from COVID-19 in Hong Kong. If the same were to play out in China, which also reports a significant reduction in influenza since week 2 in January, the equivalent numbers would be a reduction of 12,500 deaths in comparison to 3,000 from COVID-19.
I am not trying to downplay the importance of this evolving condition. As discussed, with reference to masks, public heath interventions have the potential to produce unpredictable costs and unpredictable benefits. It will only be possible to assess the relative impact of the COVID-19 and influenza epidemics in retrospect, but it is possible that the evolution of COVID-19 will reduce population mortality in 2020 in China and Hong Kong as a result of the net benefit of public health measures on the influenza epidemic.
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1. Poverty and social determinants. (2020, March 5). Retrieved March 5, 2020, from http://www.euro.who.int/en/health-topics/environment-and-health/urban-health/activities/poverty-and-social-determinants
2. Department for International Development. (n.d.). BUILDING JOBS AND PROSPERITY IN DEVELOPING COUNTRIES. Retrieved March 5, 2020, from https://www.oecd.org/derec/unitedkingdom/40700982.pdf
3. Centre for Health Protection. (2020, February 13). End of 2019/20 Winter Influenza Season and Updated Situation of COVID-19. Retrieved March 5, 2020, from https://www.chp.gov.hk/files/pdf/letters_to_doctors_20200213.pdf
4. End of winter influenza season 2019. (n.d.). Retrieved March 5, 2020, from https://www.info.gov.hk/gia/general/201904/10/P2019041000667.htm