Preventing Covid-19 From Outrunning Humanity

Yossi Sheffi
MITSupplyChain
Published in
5 min readJan 22, 2021

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Photo by Marc Rafanell López on Unsplash

As delays in Covid-19 vaccinations inflict an increasing toll of deaths and economic ruin upon the US, the newly inaugurated Biden administration is releasing all doses of approved vaccines in federal storage to the states. The aim is to speed up the rate of inoculations.

Several healthcare experts have warned against this action due to the risk of not having enough vaccines for a second jab. These critics are wrong because failing to increase the pace of vaccinations poses graver risks.

Mutants multiply the chances of infection

The main long-term risk to the vaccines’ effectiveness is that Covid-19 might mutate to evade the immune systems of the vaccinated. The virus converts an infected person’s cells into “bio factories” that churn out billions of copies of the virus and infect more cells, potentially exposing more victims to the virus droplets and aerosol leaving the infected person’s body. However, sometimes the hijacked cellular machinery makes mistakes in copying Covid-19’s genetic code, creating a mutation that is passed on to the virus’s offspring.

The vast majority of mutations have little impact and do not change the behavior of the virus. However, once in a while, a mutation can increase the virus’s potency, making it deadlier or more transmissible. Two recent mutations, the UK’s 202012/01 and the South African 501.V2, are more transmissible than the original virus by an estimated 50%. Luckily, the current mRNA vaccines (Pfizer’s and Moderna’s) seem to be effective against both mutants, especially in the short term.

The more people that get infected and the longer the virus replicates in its hosts, the greater the chance of dangerous mutations. Therefore, the sooner people worldwide get vaccinated, the lower the chance that new, even more dangerous mutants will develop.

Transmission and mortality

Covid-19 transmissibility is more of a problem than mortality. To understand why, consider two important statistics: mortality infection rate (MIR) and the disease replication rate, R0. MIR is the percentage of people infected who are likely to die. The R0 rate is the number of people that a person carrying the disease will infect on average from the time they catch the virus until they show symptoms (and presumably are then isolated, or hospitalized). This lag time is known as the incubation period, and it ranges from 2 to 14 days with an average of about five days.

Current infection mortality rate is about 1.5% in high-income nations such as the US. As of December 2020, the reproduction number in the UK was about 1.15, and by January 2021 it varied in America from 0.94 in South Dakota to 1.32 in Georgia. For exposition purposes, assume a rate of 1.1 per infection cycle. This means that, on average, each infected person will, over the course of their infection, infect another 1.1 susceptible individuals.

Assume that on day 0, there are 200,000 new cases of Covid-19 in a large susceptible population. With a 1.5% case fatality rate, the virus kills about 3,000 per day. With a reproduction rate of 1.1, the daily case counts and deaths will grow slowly but inexorably. After a week, about 3,400 new deaths per day will take place, and after a month, about 5,300 further deaths will happen each day. To appreciate how much worse the increase in transmissibility is compared to the mortality rate, assume that a mutation boosts the mortality rate by 50%, to reach a fatality rate of 2.25%. With the same 1.1 replication rate of spread, there will be 5,100 deaths per day after a week and almost 8,000 deaths per day after a month. However, if, as has already happened, the transmissibility rate of a new dominant mutant rises by 50% the reproduction rate will be 1.65 instead of 1.1. Even if the mortality rate stays at 1.5%, daily deaths will surge to 6,000 after one week and 60,000 deaths per day after 30 days.

The graph demonstrates the daily death rate differences between mutations with increased mortality and increased transmissibility. While daily deaths from increased mortality (with the same transmissibility) increase very slowly, daily deaths from the mutant that has boosted transmissibility have a “hockey stick” exponential growth. This accelerated exponential (1.1 vs. 1.65) is responsible for the huge difference between the two mutations.

Covid-19 is in the lead

We are in a race against time, which the virus is currently winning. As it spreads faster, infects more and more people, and mutates billions of times in its victims, the chances of ever more potent mutations grow. The rate of vaccinations must increase substantially to reduce the size of the susceptible population and slow the spread.

The above analysis leads to four major conclusions.

  1. The mutation issue accentuates the point that vaccination a global challenge, in addition to equity concerns.
  2. Vaccination speed may be more important than an orderly preference system if such a system slows down the rate of immunization.
  3. The US should underwrite the cost of vaccine administration (in addition to the cost of the vaccine itself which is already free) in order to reduce bureaucratic and financial hurdles.
  4. Initial data from vaccination programs in Israel show that even one vaccine dose confers significant immunity. Consequently, it is important to administer as many initial vaccine jabs as fast as possible.

When the reproduction rate drops below 1, the number of new infections will subside, and as we achieve herd immunity the chance of additional potent mutations will decline too.

Thus, the challenge is to vaccinate the entire world as fast as possible, especially when many citizens in developed economies hesitate or avoid getting the vaccine. The goal should be to decrease the likelihood of deadly mutations that can create new pandemics: Covid-21, Covid-22, etc. Such new mutations could have higher transmissibility rates, higher mortality, or not respond to the current vaccines.

The race is on.

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Yossi Sheffi
MITSupplyChain

Dr. Yossi Sheffi is a professor at the Massachusetts Institute of Technology, where he serves as Director of the Center for Transportation & Logistics.