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Comment
. 2022 Feb;18(2):69-70.
doi: 10.1038/s41582-021-00606-5.

Risk-benefit analysis of COVID-19 vaccines - a neurological perspective

Colleen L Lau  1 , Ian Galea  2
Affiliations
Comment

Risk-benefit analysis of COVID-19 vaccines - a neurological perspective

Colleen L Lau et al. Nat Rev Neurol. 2022 Feb.

Abstract

Rare neurological complications can occur after COVID-19 vaccination, but recent studies show that such complications are much more common after SARS-CoV-2 infection. Novel approaches to risk–benefit analysis such as Bayesian network models can integrate the latest global evidence with local factors to inform decision-making and support the global vaccination effort.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Bayesian network to assess risks versus benefits of COVID-19 vaccines under different scenarios.
Bayesian networks consist of nodes (boxes) and links (arrows) that define probabilistic relationships between parent and child nodes. For example, ‘vaccine effectiveness against death’ has ‘SARS-CoV-2 variant’ as a parent node and ‘death from COVID-19’ as a child node. Conditional probability tables (not shown) define quantitative relationships between parent and child nodes. A priori probabilities are assigned to parentless nodes (for example, ‘sex’). The Bayesian network can be used for risk–benefit analysis under different scenarios, for example, based on the number of vaccine doses, age, sex, SARS-CoV-2 variant and level of community transmission.
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