Treating Epidemics as Feedback Loops

Treating Epidemics as Feedback LoopsA new model of epidemics describes infections as part of a feedback loop-an approach that might one day help optimize interventions such as social distancing and lockdowns.By Andrea Parlangeli D uring the worst days of the COVID-19 pandemic, many of us became accustomed to news reports on the reproduction number R, which is the average number of cases arising from a single infected case.If we were told that R was much greater than 1, that meant the number of infections was growing rapidly, and interventions (such as social distancing and lockdowns) were necessary.But if R was near to 1, then the disease was deemed to be under control and some relaxation of restrictions could be warranted.New mathematical modeling by Kris Parag from Imperial College London shows limitations to using R or a related growth rate