Abstract
A novel statistical model based on a two-layer, contact and information, graph is suggested in order to study the influence of disease prevalence on voluntary general population vaccination during the COVID-19 outbreak. Details about the structure and number of susceptible, infectious, and recovered/vaccinated individuals from the contact layer are simultaneously transferred to the information layer. The ever-growing wealth of information that is becoming available about the COVID virus was modelled at each individual level by a simplified proxy predictor of the amount of disease spread. Each informed individual, a node in a heterogeneous graph, makes a decision about vaccination “motivated” by their benefit. The obtained results showed that disease information type, global or local, has a significant impact on an individual vaccination decision. A number of different scenarios were investigated. The scenarios showed that in the case of the stronger impact of globally broadcasted disease information, individuals tend to vaccinate in larger numbers at the same time when the infection has already spread within the population. If individuals make vaccination decisions based on locally available information, the vaccination rate is uniformly spread during infection outbreak duration. Prioritising elderly population vaccination leads to an increased number of infected cases and a higher reduction in mortality. The developed model accuracy allows the precise targeting of vaccination order depending on the individuals’ number of social contacts. Precisely targeted vaccination, combined with pre-existing immunity, and public health measures can limit the infection to isolated hotspots inside the population, as well as significantly delay and lower the infection peak.
Highlights
The model was not compared with COVID-19 data after the beginning of December because this period corresponds to the return of Belgrade citizens from Serbian ski centres
The novel two-layer graph-based SEIR-V (Susceptible, Infectious, Recovered—Vaccinated) model was applied to determine the influence of disease prevalence during voluntary general population vaccination against SARS-CoV-2
It was found that if global information has a prevailing role during the COVID-19 outbreak, the population tends to decide to vaccinate instantly and in large numbers when the infection has already spread, which may lead to the overstretching of both vaccination and hospital systems
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The novel human coronavirus associated with severe acute respiratory syndrome (SARS-CoV-2) was first identified in December 2019, in Wuhan, China [1]. Infection caused by this new coronavirus (COVID-19) spread globally and the World Health Organization proclaimed it a pandemic on 11 March 2020 [2,3]. More than 106 million cases of COVID-19 including almost 2.5 million deaths were reported as of February 2021 [4]
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