# Why should we model infectious diseases with fractional differential equations?

With COVID19 becoming a pandemic I saw some researchers trying to model it with fractional differential equations (FDE) instead of ordinary differential equations (ODE). From a technical standpoint I wondered what's the reason in doing so. I don't see how FDEs appear "naturally" when modelling diseases. For example lets look at a simple SIR-model

$$\frac{dS}{dt} = -\beta IS$$ $$\frac{dI}{dt}=\beta IS - \gamma I$$ $$\frac{dR}{dt} = \gamma I$$ With $$S$$ being the amount of susceptible persons, $$I$$ being the amount of infectious persons and $$R$$ being the amount of recovered persons. $$\beta > 0$$ the average number of contacts per person and $$\gamma>0$$ being the transition rate.

What would be the benefit of looking at it as a fractional differential equation with parameter $$\alpha \in (0,1)$$? (Let's say e.g. with a Caputo-Derivative)

I know, that a major difference between ODE and FDE is, that the solution of the FDE is not "local" in a sense that the solution in a point $$t_1$$ depends on the values of the solution on the whole intervall $$[0,t_1]$$. Whereas in ODE this is not really the case, we don't necessarily need the information about the values of the solution on the whole interval $$[0,t_1]$$. Often this is interpreted as the solution having a "memory" but why is it good for modelling epidemics, that the solution, i.e. the amount of susceptible, infectious and recovered people has a "memory"?

Apart from that, are there any technical advantages from using FDE instead of ODE? I know, that we have slightly different results regarding the stability of equilibrium points. (if we look at $$u'=f(u)$$, with equilibrium point $$u_*$$, then by the principle of linearized stability, we know that $$u_*$$ is asymptotically stable if the Eigenvalues $$\lambda$$ of $$f'(u_*)$$ have negative real part. Whereas for FDE of order $$\alpha$$ we have asymptotic stability if $$|arg(\lambda)|>\frac{\alpha \pi}{2}$$). (see this paper for a proof of this statement). However I don't see how this would "help" us in the model given above.

Question Why should we use FDEs instead of ODEs, when it comes to modelling infectious diseases? What are FDEs able to do, that ODEs are not? Is there a way to show that FDEs appear "naturally" in modelling diseases? (Literature hints are always appreciated!) Thanks in advance!

P.S. I already asked this question on Math stackexchange two weeks ago, however I thought mathoverflow may be better suited for this question. If its not I apologize in advance!

• A corresponding post on Mathematics: Why model infectious diseases with fractional differential equation Dec 23, 2021 at 11:22
• @MartinSleziak Yes, this is also my post, but I thought mathoverflow may be better suited for this question. If its not I'd like to apologize! Dec 23, 2021 at 11:23
• I have linked to the posts on the other site mainly because it is recommended to link cross-posts to each other. See also: Cross posts to Math SE and Can I ask a question on MathOverflow and also on another site? Dec 23, 2021 at 11:30
• I have no expertise in this field and have no opinion about this particular approach. Generally speaking, however, I would imagine that since covid, researchers in mathematical epidemiology might try to see if their favourite approach/method/subtopic/... has anything to contribute. Such papers would probably look good on applications for research funding. They will surely be able to give some motivation/justification for their approach. Some might truly be able to contribute. And even if not to covid, they may be of intrinsic value to maths or modelling. Dec 25, 2021 at 22:46