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. 2021 Oct 19;12(5):e01864-21. doi: 10.1128/mBio.01864-21

TABLE 2.

Pandemic response and preparedness research related to SARS-CoV-2 associated with dual-use potential

Work Proposed benefits Potential risks Reference(s)
Identification of mutations that make SARS-CoV-2 more transmissible, virulent, and immune evasive Informing genomic surveillance and countermeasure design such as vaccines or monoclonal antibodies May enable engineering of more concerning variants of SARS-CoV-2 or other viruses Starr et al. (2021) (16)
Publication of detailed SARS-CoV-2 engineering protocols Increased access to recombinant SARS-CoV-2 for response research May inform malicious or careless actors on how to create SARS-CoV-2 variants Xie et al. (2021) (20)
Engineering immune evasion for viral vectors Improve effectiveness and reusability of viral vector vaccines Can create transferable insights on engineering immune evasion for pathogens Sandbrink and Koblentz (2021) (23), Roberts et al. (2006) (25)
Creation of transmissible vaccines Use for vaccination of animal reservoirs for eradication of zoonotic viruses at risk of spillover Safety risks; ethical and ecological concerns; may create insights on engineering transmissibility, genetic stability, and immune evasion Nuismer et al. (2018) (31), Nuismer and Bull (2020) (30), Sandbrink et al. (2021) (32)
Increased gain-of-function work on future potential pandemic pathogens, not limited to coronaviruses Prediction of zoonotic epidemics, possibility to inform biosurveillance targeting, and design of countermeasures Risk of accidental exposure and lab release of engineered pathogens; risk of informing the creation of pathogens with enhanced lethality and transmissibility Herfst et al. (2012) (34), Imai et al. (2012) (35), Casadevall and Imperiale (2014) (74)
Large-scale viral collection and characterization Prediction of zoonotic epidemics, possibility to inform biosurveillance targeting, and design of countermeasures Risk of accidental exposure and release; risk of informing viral engineering by creating large-scale data sets connecting sequence and function Carroll et al. (2018) (40), Monrad and Katz (2020) (41), Carlson et al. (2021) (42)