Michael Levitt is an “American-British-Israeli” chemist who won the Nobel Prize for chemistry in 2013. He spends a lot of time in China and has followed the coronavirus epidemic from the beginning. The Jerusalem Post highlights Levitt’s optimistic view of the epidemic, in part because the contagion is waning in China:
“The rate of infection of the virus in the Hubei province increased by 30% each day — that is a scary statistic. I am not an influenza expert but I can analyze numbers and that is exponential growth.”
Had the growth continued at that rate, the whole world would have become infected within 90 days. But as Levitt continued to process the numbers, the pattern changed. On February 1, when he first looked at the statistics, Hubei Province had 1,800 new cases a day. By February 6, that number had reached 4,700 new cases a day.
But on February 7, something changed. “The number of new infections started to drop linearly and did not stop,” Levitt said. “A week later, the same happened with the number of the deaths. This dramatic change in the curve marked the median point and enabled better prediction of when the pandemic will end. Based on that, I concluded that the situation in all of China will improve within two weeks. And, indeed, now there are very few new infection cases.”
By plotting the data forward, Levitt has predicted that the virus will likely disappear from China by the end of March.
Levitt explains one of the reasons why the spread of the disease slows:
The reason for the slowdown is due to the fact that exponential models assume that people with the virus will continue to infect others at a steady rate. In the early phase of COVID-19, that rate was 2.2 people a day on average.
“In exponential growth models, you assume that new people can be infected every day, because you keep meeting new people,” Levitt said. “But, if you consider your own social circle, you basically meet the same people every day. You can meet new people on public transportation, for example; but even on the bus, after some time most passengers will either be infected or immune.”
Levitt also concludes that most people are naturally immune to COVID-19:
In Wuhan, where the virus first emerged, the whole population theoretically was at risk of becoming infected, but only 3% were.
The Diamond Princess cruise ship represented the worst-case scenario in terms of disease spread, as the close confines of the ship offered optimal conditions for the virus to be passed among those aboard. The population density aboard the ship was the equivalent of trying to cram the whole Israeli population into an area 30 kilometers square. In addition, the ship had a central air conditioning and heating system, and communal dining rooms.
“Those are extremely comfortable conditions for the virus and still, only 20% were infected. It is a lot, but pretty similar to the infection rate of the common flu,” Levitt said. Based on those figures, his conclusion was that most people are simply naturally immune.
Let’s hope that proves to be true. The cruise ship experience seems to be powerful evidence that it is.
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