Concerning the Recent 2019-Novel Coronavirus Outbreak
Update: Most information presented here is out of date. See the 80,000 hours page for more up-to-date information.
I have been researching the Wuhan Coronavirus for several hours today, and I have come to the tentative conclusion that the situation is worse than I initially thought.
Given my current understanding, it now seems reasonable to assign a non-negligible probability (>2%) to the proposition that the current outbreak will result in a global disaster (>50 million deaths resulting from the pathogen within 1 year). I understand this prediction will sound alarmist, but in this post I will outline some of the reasons why I have come to this conclusion.
I now believe that it is warranted for effective altruists to take particular actions to prepare for a resulting pandemic. The most effective action is likely to research preparation in order to limit exposure to sources of the virus. Sending out evidence-based warning signals to at-risk communities may also be effective at limiting the spread of the pathogen.
Summary of my reasons for believing that this outbreak could result in a global disaster
The current outbreak matches the criteria that scientists have identified as being particularly likely characteristics of a pandemic-induced global disaster. That is, it’s a disease that’s contagious during a long incubation period, has a high infection rate, has no known treatment, few people are immune, and it has a low but significant mortality rate. See this article for a summary of likely characteristics of a pandemic-induced global disaster.
Based on my research, I wasn’t able to identify any historically recent pathogen with these characteristics, giving me reason to believe that using an outside view to argue against alarmism may not be warranted. For reference, the 2003 SARS outbreak, the 2009 Swine Flu, and the several Ebola outbreaks do not match the profiles of a global disaster as completely as the current outbreak.
Estimates of the mortality rate vary, but one media source says, “While the single figures of deaths in early January seemed reassuring, the death toll has now climbed to above 3 percent.” This would put itroughly on par with the mortality rate of the 1918 flu pandemic, and over 10 times more deadly than a normal seasonal flu. It’s worth noting, however, that the 1918 flu pandemic killed mostly young adults, whereas the pattern for this pathogen appears to be the opposite (which is normal for pathogens).
The incubation period (the period during which symptoms are not present but those infected can still infect others) could be as long as 14 days, according to many sources.
An Imperial College London report stated, “Self-sustaining human-to-human transmission of the novel coronavirus (2019-nCov) is the only plausible explanation of the scale of the outbreak in Wuhan. We estimate that, on average, each case infected 2.6 (uncertainty range: 1.5-3.5) other people up to 18th January 2020, based on an analysis combining our past estimates of the size of the outbreak in Wuhan with computational modelling of potential epidemic trajectories. This implies that control measures need to block well over 60% of transmission to be effective in controlling the outbreak.”
Compare the above infection rate to the H1N1 virus, which some estimate to have infected 10-20% of the world population in 2009. The World Health Organization has said, “The pandemic (H1N1) 2009 influenza virus has a R0 of 1.2 to 1.6 (Fraser, 2009) which makes controlling its spread easier than viruses with higher transmissibility.”
A simple regression model indicates that the growth rate of the pathogen is predictable and extremely rapid.
The number of cases as reported by the National Health Commission of China forms the basis of my regression model (you can currently find the number of cases reported in graphical format on the Wikipedia page here). An exponential regression model fit to the data reveals that the equation 38.7 * e^(0.389 * (t+11)) strongly retrodicts the number of cases (where t is the number of days since January 26th). In this model, the growth is very high.
[Update: Growth for January 27th remained roughly in line with the predicted growth from the exponential regression model. The new equation is 35.5*exp(0.401*t) where t is the number of days since January 15th]
A top expert has estimated that approximately 100,000 people have already been infected, which is much more than the confirmed number of 2808 (as of January 26th). If the number were this high, then the pathogen has likely already crossed the quarantine. The infection has also spread to 12 other countries besides China, supporting this point.
The Metaculus community’s estimate for the number of total cases in 2020 is much higher than it was just two or three days ago. Compare this older question here, versus this new question (when it opens).
While several organizations are developing a vaccine, Wikipedia seems to indicate that it will take months before vaccines even enter trials, and we should expect that it will take about a year before a vaccine comes out.
Summary of my recommendations
I think it’s unlikely that EAs are in any special position to help stop the pandemic. However, we can guard ourselves against the pandemic by heeding early warnings, research ways to limit our exposure to the virus, and use our platforms to warn those at-risk.
The CDC has a page for preparing for disaster.
Currently, the pathogen appears to have a significant mortality rate, but kills mainly older people. Therefore, old people are most at-risk of dying.
Even if you contract the disease and don’t die, the symptoms are likely to be severe. One source says,
ARDS (acute respiratory distress syndrome) is a common complication. Between 25 and 32 percent of cases are admitted to the intensive care unit (ICU) for mechanical ventilation and sometimes ECMO (pumping blood through an artificial lung for oxygenation).
Other complications include septic shock, acute kidney injury, and virus-induced cardiac injury. The extensive lung damage also sets the lung up for secondary bacterial pneumonia, which occurs in 10 percent of ICU admissions.
Acknowledgements: Dony Christie and Louis Francini helped gather sources and write this post.