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Who should we fear more: biohackers, disgruntled postdocs, or bad governments? a simple risk chain model of biorisk

Abstract:
The biological risk landscape continues to evolve as developments in synthetic biology and biotechnology offer increasingly powerful tools to a widening pool of actors, including those who may consider carrying out a deliberate biological attack. However, it remains unclear whether it is the relatively large numbers of low-resourced actors or the small handful of high-powered actors who pose a greater biosecurity risk. To answer this question, this paper introduces a simple risk chain model of biorisk, from actor intent to a biological event, where the actor can successfully pass through each of N steps. Assuming that actor success probability at each independent step is sigmoidally distributed and actor power follows a power-law distribution, if a biorisk event were to occur, this model shows that the expected perpetrator would likely be highly powered, despite lower-powered actors being far more numerous. However, as the number of necessary steps leading to a biological release scenario decreases, lower-powered actors can quickly overtake more powerful actors as the likely source of a given event. If steps in the risk chain are of unequal difficulty, this model shows that actors are primarily limited by the most difficult step. These results have implications for biosecurity risk assessment and health security strengthening initiatives and highlight the need to consider actor power and ensure that the steps leading to a biorisk event are sufficiently difficult and not easily bypassed.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1089/hs.2019.0115

Authors

More by this author
Institution:
University of Oxford
Division:
HUMS
Department:
Philosophy Faculty
Oxford college:
Kellogg College
Role:
Author
ORCID:
0000-0001-5636-5402
More by this author
Institution:
University of Oxford
Division:
HUMS
Role:
Author
ORCID:
0000-0003-0934-8313


Publisher:
Mary Ann Liebert
Journal:
Health Security More from this journal
Volume:
18
Issue:
3
Pages:
155-163
Publication date:
2020-06-10
DOI:
EISSN:
2326-5108
ISSN:
2326-5094
Pmid:
32522112


Language:
English
Keywords:
Pubs id:
1113644
Local pid:
pubs:1113644
Deposit date:
2020-06-30
ARK identifier:

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