Using simulations to provide justification for forced vaccinations AND prolonged lockdowns AND continued mass-scale testing of people with no symptoms.
The authors make some honest statements about the shortcomings of their method, but the "Ethics" section is surprisingly silent on whether such recommendations should be made purely on simulation runs, especially without code.
> We implemented a modification of a SIR model
Where is the code?
> The simplest model for the spread of an infection is the SIR model1,2, which tracks the fraction of a population in each of three groups: susceptible, infectious and recovered (Fig. 1a). The sizes of these groups are functions of time t — we will write them as S, I and R, with dependence on t implied. During a virgin epidemic, we often assume that spread is so rapid that we can ignore any change in the population due to births and deaths — this is a so-called ‘closed epidemic’ with a fixed population size S + I + R = N. The SIR model has no probabilistic component, except for the assumption that the population can mix at random and is large enough that predictions based on average rates can be used.
> ... The model is initialized with the entire population being in the susceptible group except for a single infectious individual: I(0) = 1, S(0) = N – 1, R(0) = 0. At each time unit (for example, day), any infected individual can come into contact with k other individuals in the population. On average, per unit time they will come into contact with kS/N susceptible individuals and infect kπS/N of them, if π is the probability of infection on contact. Conventionally, k and π are combined into a transmission rate, β = πk, which is the average rate at which an infected individual can infect a susceptible. [1]
Discuss the path-dependence of simulated evolutions on choice of initial values.
The authors make some honest statements about the shortcomings of their method, but the "Ethics" section is surprisingly silent on whether such recommendations should be made purely on simulation runs, especially without code.
> We implemented a modification of a SIR model
Where is the code?
> The simplest model for the spread of an infection is the SIR model1,2, which tracks the fraction of a population in each of three groups: susceptible, infectious and recovered (Fig. 1a). The sizes of these groups are functions of time t — we will write them as S, I and R, with dependence on t implied. During a virgin epidemic, we often assume that spread is so rapid that we can ignore any change in the population due to births and deaths — this is a so-called ‘closed epidemic’ with a fixed population size S + I + R = N. The SIR model has no probabilistic component, except for the assumption that the population can mix at random and is large enough that predictions based on average rates can be used.
> ... The model is initialized with the entire population being in the susceptible group except for a single infectious individual: I(0) = 1, S(0) = N – 1, R(0) = 0. At each time unit (for example, day), any infected individual can come into contact with k other individuals in the population. On average, per unit time they will come into contact with kS/N susceptible individuals and infect kπS/N of them, if π is the probability of infection on contact. Conventionally, k and π are combined into a transmission rate, β = πk, which is the average rate at which an infected individual can infect a susceptible. [1]
Discuss the path-dependence of simulated evolutions on choice of initial values.
[1]: https://www.nature.com/articles/s41592-020-0822-z