Mask, Vaccine, and Misinformation in Covid-19 Pandemic*

Abstract: The COVID-19 pandemic, caused by SARS-CoV-2, presents an unprecedented challenge to human health, the economy, and nearly all aspects of our society. Like many of our colleagues, we jumped into Covid-19 modeling, hoping to improve our understanding of the disease spread and mitigation strategies. In 2020 before vaccines were available, masks and social distancing were the main tools we had to impede the spread of virus. Using a stratified SEIAR model, we performed the virtual experiments of putting masks on the passengers onboard of the cruise ship Diamond Princess. The results show quantitatively how timing of masking policy, types of masks used, and public compliance could affect the epidemic outcome, thus suggesting optimal masking policy strategies for high risk environments. Since late 2020, as we recognize vaccination is the only sustainable mitigation to prevent widespread morbidity and mortality from the infection, vaccine hesitancy, resulting mostly from misinformation, threatens the possibility of ending the COVID-19 pandemic through mass vaccination. To address vaccine hesitancy in driving epidemic spread, we use an evolutionary game theoretical framework to characterize the individual decision in vaccine adoption, and an SIS model for the co-evolution of epidemic spread and information spread. Our preliminary results show rich dynamical behavior of this co-evolution, suggesting misinformation fuels epidemic spread such that without the management of misinformation, the epidemic will never end even with high vaccine efficacy. Education increases vaccination and reduces infection, suggesting an 'educate to vaccinate' approach to eventually bring the pandemic to endemic. While all models are wrong, we hope our models are somewhat useful in combating Covid-19 and possible future epidemics.

Back to Search Research Symposium Abstracts