ABSTRACT
Facing the more contagious COVID-19 variant, Omicron, nonpharmaceutical interventions (NPIs) were still in place and booster doses were proposed to mitigate the epidemic. However, the uncertainty and stochasticity in individuals' behaviours toward the NPIs and booster dose increase, and how this randomness affects the transmission remains poorly understood. We present a model framework to incorporate demographic stochasticity and two kinds of environmental stochasticity (notably variations in adherence to NPIs and booster dose acceptance) to analyze the effects of different forms of stochasticity on transmission. The model is calibrated using the data from December 31, 2021, to March 8, 2022, on daily reported cases and hospitalizations, cumulative cases, deaths and vaccinations for booster doses in Toronto, Canada. An approximate Bayesian computational (ABC) method is used for calibration. We observe that demographic stochasticity could dramatically worsen the outbreak with more incidence compared with the results of the corresponding deterministic model. We found that large variations in adherence to NPIs increase infections. The randomness in booster dose acceptance will not affect the number of reported cases significantly and it is acceptable in the mitigation of COVID-19. The stochasticity in adherence to NPIs needs more attention compared to booster dose hesitancy. © 2023 American Institute of Mathematical Sciences. All rights reserved.
ABSTRACT
In this work, a stochastic differential equation model about the novel Coronavirus 2019 (COVID-19) is introduced to describe the transmission dynamics of that disease among the susceptible person. By taking the social distance, musk wearing, and other human behavior as a control strategy and introducing an objective function which both considers the limitation of social distance and minimizes the infection population, an optimal control strategy is given numerically. This result gives a new numerical method to simulate the epidemic model and make a new insight into the control strategy choice of the pandemic control under the environments and conditions of different countries. © 2021 IEEE.