IntroductionThe COVID-19 pandemic powerfully demonstrates the consequences of biothreats. Countries will want to know how to better prepare for future events. The Global Health Security Index (GHSI) is a broad, independent assessment of 195 countries’ preparedness for biothreats that may aid this endeavour. However, to be useful, the GHSI’s external validity must be demonstrated. We aimed to validate the GHSI against a range of external metrics to assess how it could be utilised by countries.MethodsGlobal aggregate communicable disease outcomes were correlated with GHSI scores and linear regression models were examined to determine associations while controlling for a number of global macroindices. GHSI scores for countries previously exposed to severe acute respiratory syndrome (SARS), Middle East respiratory syndrome and Ebola and recipients of US Global Health Security Agenda (GHSA) investment were compared with matched control countries. Possible content omissions in light of the progressing COVID-19 pandemic were assessed.ResultsGHSI scores for countries had strong criterion validity against the Joint External Evaluation ReadyScore (rho=0.82, p<0.0001), and moderate external validity against deaths from communicable diseases (−0.56, p<0.0001). GHSI scores were associated with reduced deaths from communicable diseases (F(3, 172)=22.75, p<0.0001). The proportion of deaths from communicable diseases decreased 4.8% per 10-point rise in GHSI. Recipient countries of the GHSA (n=31) and SARS-affected countries (n=26), had GHSI scores 6.0 (p=0.0011) and 8.2 (p=0.0010) points higher than matched controls, respectively. Biosecurity and biosafety appear weak globally including in high-income countries, and health systems, particularly in Africa, are not prepared. Notably, the GHSI does not account for all factors important for health security.ConclusionThe GHSI shows promise as a valid tool to guide action on biosafety, biosecurity and systems preparedness. However, countries need to look beyond existing metrics to other factors moderating the impact of future pandemics and other biothreats. Consideration of anthropogenic and large catastrophic scenarios is also needed.

Horizon scanning is intended to identify the opportunities and threats associated with technological, regulatory and social change. In 2017 some of the present authors conducted a horizon scan for bioengineering (Wintle et al., 2017). Here we report the results of a new horizon scan that is based on inputs from a larger and more international group of 38 participants. The final list of 20 issues includes topics spanning from the political (the regulation of genomic data, increased philanthropic funding and malicious uses of neurochemicals) to the environmental (crops for changing climates and agricultural gene drives). The early identification of such issues is relevant to researchers, policy-makers and the wider public.

Biology can be misused, and the risk of this causing widespread harm increases in step with the rapid march of technological progress. A key security challenge involves attribution: determining, in the wake of a human-caused biological event, who was responsible. Recent scientific developments have demonstrated a capability for detecting whether an organism involved in such an event has been genetically modified and, if modified, to infer from its genetic sequence its likely lab of origin. We believe this technique could be developed into powerful forensic tools to aid the attribution of outbreaks caused by genetically engineered pathogens, and thus protect against the potential misuse of synthetic biology.

Smallpox was declared eradicated in 1980, with known seed stock retained in two high security Biosafety Level 4 laboratories in the United States and Russia. Experts agree the likelihood of theft from these laboratories is low, and that synthetic creation of smallpox is a theoretical possibility. Until 2017 it was believed that synthetic smallpox was technically too complex a task to be a serious threat. However, in 2017, Canadian scientists synthesised a closely related orthopoxvirus, horsepox, using mail order DNA and $100,000. Simultaneously, terrorist groups have declared intent to conduct biological attacks. In this context an exercise was held on August 16th 2018, with international and cross-sectoral stakeholders to review preparedness for a bioterrorism attack in the Asia-Pacific region and globally. The exercise was conducted by The National Health and Medical Research Council (NHMRC) Centre for Research Excellence, Integrated Systems for Epidemic Response, with contextual input from the Ministry of Health and Medical Services Fiji. The scenario involved a deliberate release in Fiji, followed by a larger release in a more populous Asian country. Mathematical modelling was used to underpin epidemic projections under different conditions. The exercise alternated between clinical, public health, emergency and societal responses, with participants making real-time decisions on cross-sectoral response across the region and the world. Key weak points which are influential in determining the final size and impact of the epidemic were identified (based on mathematical modelling of transmission in Fiji and globally). We identified potential gaps in preparedness for smallpox and factors which influence the severity of a smallpox epidemic. This included identifying which determinants of epidemic size are potentially within our control, and which are not. Influential factors within our control include: preventing an attack through intelligence, law enforcement and legislation; speed of diagnosis; speed and completeness of case finding and case isolation; speed and security of vaccination response, including stockpiling; speed and completeness of contact tracing; protecting critical infrastructure and business continuity; non-pharmaceutical interventions (social distancing, PPE, border control); protecting first responders; operational support and logistics; social mobilisation and risk communication. Based on discussion at the workshop between diverse stakeholders, recommendations were made to guide improved prevention, mitigation and rapid response, thus providing a holistic, cross-sectoral framework for prevention of a worst-case scenario smallpox pandemic.

Rapid developments are currently taking place in the fields of artificial intelligence (AI) and biotechnology, and applications arising from the convergence of these 2 fields are likely to offer immense opportunities that could greatly benefit human health and biosecurity. The combination of AI and biotechnology could potentially lead to breakthroughs in precision medicine, improved biosurveillance, and discovery of novel medical countermeasures as well as facilitate a more effective public health emergency response. However, as is the case with many preceding transformative technologies, new opportunities often present new risks in parallel. Understanding the current and emerging risks at the intersection of AI and biotechnology is crucial for health security specialists and unlikely to be achieved by examining either field in isolation. Uncertainties multiply as technologies merge, showcasing the need to identify robust assessment frameworks that could adequately analyze the risk landscape emerging at the convergence of these 2 domains. This paper explores the criteria needed to assess risks associated with AI and biotechnology and evaluates 3 previously published risk assessment frameworks. After highlighting their strengths and limitations and applying to relevant AI and biotechnology examples, the authors suggest a hybrid framework with recommendations for future approaches to risk assessment for convergent technologies.

Objectives The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies. Metagenomic Next-Generation Sequencing (mNGS) may allow for the detection of pathogens that can be missed in targeted assays. The goal of this study was to assess the performance of nanopore-based Sequence-Independent Single Primer Amplification (SISPA) for the detection and characterization of SARS-CoV-2. Methods We performed mNGS on clinical samples and designed a diagnostic classifier that corrects for barcode crosstalk between specimens. Phylogenetic analysis was performed on genome assemblies. Results Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-PCR cycle threshold value less than 30. We assembled 10 complete, and one near-complete genomes from 20 specimens that were classified as positive by mNGS. Phylogenetic analysis revealed that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. We found 100% concordance between phylogenetic lineage assignment and Variant of Concern (VOC) PCR results. Our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with the current standard VOC PCR being used in British Columbia. Conclusions This study supports future work examining the broader feasibility of nanopore mNGS as a diagnostic strategy for the detection and characterization of viral pathogens.

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 highpowered 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 lowerpowered 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.

A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplit’s taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplit’s taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic.