A Vaccination Simulator for COVID-19: Effective and Sterilizing Immunization Cases

Abstract

Accurate modeling provides a means by which a complex problem can be examined for informed decision-making. We present a particle-based SEIR epidemic simulator as a tool to assess the impact of vaccination strategies on viral propagation and to model both sterilizing and effective immunization outcomes. The simulator includes modules to support contact tracing of the interactions amongst individuals as well as epidemiological testing of the general population. The simulator particles are distinguished by age, thus enabling a more accurate representation of the rates of infection and mortality in accordance with differential demographic susceptibilities and medical outcomes. The simulator can be calibrated by region of interest and variable vaccination strategies (i.e. random or prioritized by age) so as to enable locality-sensitive virus mitigation policy measures and resource allocation. The results described, based on the experience of the province of Lecco, Italy, indicate that the tool can be used to evaluate vaccination strategies in a way that incorporates local circumstances of viral propagation and demographic susceptibilities. Further, the simulator accounts for modeling the distinction between sterilizing immunization, in which immunized people are no longer contagious, and that of effective immunization, in which symptoms and mortality outcomes are diminished but individuals can still transmit the virus.

COVID-19 Vaccination Strategies Considering Hesitancy Using Particle-Based Epidemic Simulation

“…This province was one of the epicenters of the COVID-19 epidemic in Italy. We also used this province in our previous works [7], [8]. The simulations start from the first day of vaccination in the region (December 27, 2020).…”

“…The simulations start from the first day of vaccination in the region (December 27, 2020). In [7], we presented the validation scenario for the province till the start of the vaccination in Italy. Therefore, we used the data from the last day of the validation scenario to initialize our simulations.…”

“…In this work, we use an extension of our previous particle-based simulator with vaccination, contact tracing, and testing modules [7]. Due to the page restrictions, this section only describes the implementation of the vaccine hesitancy in the vaccination module.…”

“…Due to the page restrictions, this section only describes the implementation of the vaccine hesitancy in the vaccination module. For further details on the simulator, the reader is referred to [7].…”

“…In this context, epidemic simulators are essential for finding optimal vaccination strategies considering the above-mentioned constraints and scenarios. In our previous work, we developed a vaccination simulator for COVID-19 based on a particle-based SEIR (susceptible-exposed-infected-recovered) epidemic model [7]. In this work, we extend our previous simulator for the “effective immunization” case after vaccination with the addition of the hesitancy parameter to the particle model.…”