How did Israel reach its decisions to impose measures to slow the spread of the coronavirus? One of the key documents that has influenced policymakers is a mathematical model that tries to predict the impact of the virus’ spread, how much time it will continue and how it will behave – assuming that the government doesn’t take steps to stop it.
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The model provides four rough scenarios for what could happen based on the rate the infection spreads before serious steps are taken. The figures range from a relatively low rate of contagion, under which each coronavirus sufferer infects 1.2 people on average, to a relatively high average of two people.
In each scenario, the model estimates the cost in terms of human life – the overall number of sick, the number of severe or critical cases, the number of deaths and the level of hospital facilities that will be needed in response.
Broadly speaking, it shows that the most important variable in controlling the epidemic is the rate of infection, and explains why the Health Ministry has been pressing for measures to enforce social distancing. The goal is to reduce the contagion rate to less than one, as China succeeded in doing. If Israel can do the same, the model’s worrying predictions can be avoided.
The model was developed by Dr. Amit Huppert, head of biostatistics and biomathematics of the Gertner Institute for Epidemiology and Health Policy Research at Sheba Medical Center, Tel Hashomer; his colleague at Gertner, Dr. Rami Yaari; and Prof. Haggai Katriel of the ORT Braude College of Engineering’s mathematics department.
It should be stressed that this is only a mathematical model, not based on real life statistics. The rate of contagion and death has varied between countries, which means that predicting the trajectory of the epidemic isn’t easy. Not only have some countries succeeded better than others at controlling the spread of the virus, but local climate may play a role as well.
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Moreover, the model is being constantly updated based on developments from around the world. The estimates seen by TheMarker were based on data as of March 5.
The model shows that with a relatively low average contagion rate of 1.2 people, 22,000 Israelis will suffer a critical case of the coronavirus and 8,600 will die before the epidemic runs its course. By comparison, if on average two people are infected for each sufferer, the number of critical cases will jump to 54,000 and deaths to 21,600. The model deals with two intermediate scenarios as well.
Under the low-contagion scenario, at the peak of the epidemic the number of people in Israeli hospitals in critical condition will average 130 a day. That rises to 1,450 in the high-contagion scenario, a number that the healthcare system would not be able to cope with. In the intermediate scenarios, the number varies between 340 and 580 per day, according to the model.
The high rate of contagion will increase demand for hospital beds to 42,500 at the epidemic’s peak, including 14,000 in intensive care units. Israeli hospitals right now have only 16,000 beds and just a few hundred in ICUs. Even in the low-contagion scenario, coronavirus sufferers will require 4,000 beds at the peak of the epidemic and another 1,300 ICU beds.
According to this model, a high contagion rate will mean that the epidemic peaks after 130 days, or about four months, and 250 days, or eight months, before it comes to an end. This model forecasts that the epidemic would spread rapidly and result in large numbers of sick and dead and lead to a collapse of the healthcare system.
At the lower-contagion scenario, the model holds that the coronavirus epidemic will last longer – more than 440 days till it reaches its peak – and will only fade away after 880 days, or two-and-a-half years.
The model also tries to predict the mortality rates for different ages. It shows that the rate will be low for sufferers up to age 50 and then rises rapidly to 7.9 percent for ages 50-59, 24.1 percent for ages 60-69 and 30.3 percent for those 70-79. However, the mortality rate falls if the rate of infection is slow.