A stochastic inventory model of COVID-19 and robust, real-time identification of carriers at large and infection rate via asymptotic laws.

ABSTRACT: A critical operations management problem in the ongoing COVID-19 pandemic is cognizance of (a) the number of all carriers at large (CaL) conveying the SARS-CoV-2, including asymptomatic ones and (b) the infection rate (IR). Both are random and unobservable, affecting the spread of the disease, patient arrivals to health care units (HCUs) and the number of deaths. A novel, inventory perspective of COVID-19 is proposed, with random inflow, random losses and retrials (recurrent cases) and delayed/distributed exit, with randomly varying fractions of the exit distribution. A minimal construal, it enables representation of COVID-19 evolution with close fit of national incidence profiles, including single and multiple pattern outbreaks, oscillatory, periodic or non-periodic evolution, followed by

SUBMITTER: Tsiligianni C 

PROVIDER: S-EPMC8741332 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature