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Considering the global pandemic of coronavirus disease 2019 (COVID-19),around the world several vaccines are being developed. Till now, these vaccinesare the most effective way to reduce the high burden on the global healthinfrastructure. However, the public acceptance towards vaccination is a crucialand pressing problem for health authorities. This study has been designed todetermine the parameters affecting the decisions of common individuals towardsCOVID-19 vaccine. In our study, using the platforms of compartmental model andnetwork simulation, we categorize people and observe their motivation towardsvaccination in a mathematical social contagion process. In our model, weconsider peer influence as an important factor in this dynamics, and study howindividuals are influencing each other for vaccination. The efficiency of thevaccination process is estimated by the period of time required to vaccinate asubstantial fraction of total population. We discovered the major barriers anddrivers of this dynamics, and concluded that it is required to formulatespecific strategies by the healthcare workers which could be more effective forthe undecided and vaccine hesitant group of people.

Hesitancy, Awareness and Vaccination: A Computational Analysis on Complex Networks