Infection Units: A Novel Approach for Modeling COVID-19 Spread

Abstract

A novel mechanistic model of COVID-19 spread is presented. The pool of infected individuals is not homogeneously mixed but is viewed as a passage into which individuals enter upon the contagion, through which they pass (in the manner of “plug flow”) and exit at their recovery points within a fixed time. Our novel concept of infection unit is defined. The model separately considers various population pools: two of symptomatic and asymptomatic infected patients; three different pools of recovered individuals; of assisted hospitalized patients; of the quarantined; and of those who die from COVID-19. Transmission of this disease is described by an infection rate function, modulated by an encounter frequency function. This definition makes redundant the addition of a separate pool for the exposed, as done in several other models. Simulations are presented. The effects of social restrictions and of quarantine policies on pandemic spread are demonstrated. The model differs conceptually from others of the kind in the description of the transmission dynamics of the disease. A set of experimental data is used to calibrate our model, which predicts the dynamic behavior of each of the defined pools during pandemic spread.