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Vaccination strategies against COVID-19 and the diffusion of anti-vaccination views (preprint)
arxiv; 2020.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2009.13674v1
ABSTRACT
Miss-information is usually adjusted to fit distinct narratives and can propagate rapidly through communities of interest, which work as echo chambers, cause reinforcement and foster confirmation bias. False beliefs, once adopted, are rarely corrected. Amidst the COVID-19 crisis, pandemic-deniers and people who oppose wearing face masks or quarantines have already been a substantial aspect of the development of the pandemic. With a potential vaccine for COVID-19, different anti-vaccine narratives will be created and, likely, adopted by large population groups, with critical consequences. Here, we analyse epidemic spreading and optimal vaccination strategies, measured with the average years of life lost, in two network topologies (scale-free and small-world) assuming full adherence to vaccine administration. We consider the spread of anti-vaccine views in the network, using a similar diffusion model as the one used in epidemics, which are adopted based on a persuasiveness parameter of anti-vaccine views. Results show that even if an anti-vaccine narrative has a small persuasiveness, a large part of the population will be rapidly exposed to them. Assuming that all individuals are equally likely to adopt anti-vaccine views after being exposed, more central nodes in the network are more exposed and therefore are more likely to adopt them. Comparing years of life lost, anti-vaccine views could have a significant cost not only on those who share them, since the core social benefits of a limited vaccination strategy (reduction of susceptible hosts, network disruptions and slowing the spread of the disease) are substantially shortened.
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Full text: Available Collection: Preprints Database: PREPRINT-ARXIV Main subject: Optic Nerve Diseases / COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-ARXIV Main subject: Optic Nerve Diseases / COVID-19 Language: English Year: 2020 Document Type: Preprint