Lennart Justen

Biosafety level (BSL) classifications of biological agents have succeeded at minimizing occupational risk inside laboratories, but largely neglect the potential for onward transmission. As a result, many non- transmissible pathogens that could kill at most one individual per person exposed require greater containment than 1918 influenza, a virus that killed 50-100 million and might cause a new pandemic today. Laboratory workers are consenting professionals; the public is not. We recommend complementing BSLs with explicit thresholds for expected societal harm. Here we formalize Societal Safety Levels (SSLs) based on expected public fatalities per year, which we quantify from (i) estimated probability of laboratory release, (ii) likelihood of societal transmission, and (iii) consequence. SSLs would apply specifically to laboratory research with replication-competent potential pandemic pathogens, and would not restrict field surveillance, sequencing, or countermeasure development using non-replicating systems or pandemic-incapable agents. We find that applying the 0.1 expected deaths per facility-year standard common across multiple major-hazard industries to potential pandemic pathogen research would require marked safety improvements. Complementing BSLs with SSLs would establish enforceable accident- safety thresholds for pandemic-capable pathogens, bringing high-risk biological research into alignment with the quantitative safety standards that help other hazardous industries operate with public acceptance.

Wastewater metagenomic sequencing (WW-MGS) enables simultaneous detection of hundreds of pathogens, but its use for quantitative pathogen tracking has not been robustly validated. Like wastewater PCR (WW-PCR), WW-MGS is affected by biases from variable fecal dilution and sample processing, but must additionally contend with the compositional structure of sequencing data, where a taxon’s apparent abundance depends on the abundance of every other taxon in the sample. Simple summaries such as a pathogen’s fraction of total reads may therefore be poorly suited to quantitative use. We retrospectively evaluated seven normalization approaches that attempt to control for these sources of bias against a baseline of total read relative abundance, using 1,425 samples from the CASPER consortium spanning 25 U.S. sites. Each approach was compared against WW-PCR and clinical data across eight total pathogens. Among the normalization strategies we evaluated, tobamovirus markers, diet-derived plant viruses abundant in human stool, performed best. Normalizing WW-MGS data by tobamovirus-genus counts improved median site concordance for 18 of 19 pathogen and comparison-source combinations. Gains were largest for year-round-circulating SARS-CoV-2 and norovirus and smaller for sharply seasonal pathogens such as influenza and respiratory syncytial virus, where baseline concordance was already high. Tobamovirus normalization rarely degraded concordance, with median gains roughly five times larger than median losses. Tobamovirus-normalized WW-MGS reached clinical concordance comparable to targeted WW-PCR, supporting its use as a quantitative trend-monitoring tool alongside pathogen-agnostic detection.

Wastewater monitoring enables non-invasive, population-scale tracking of community infections independent of healthcare-seeking behavior and clinical diagnosis. Metagenomic sequencing extends this capability by enabling broad, pathogen-agnostic detection of hundreds of viral taxa, including emerging threats. Here, we present data from CASPER (the Coalition for Agnostic Sequencing of Pathogens from Environmental Reservoirs), a U.S.-based wastewater metagenomic sequencing network designed for deep, untargeted pathogen monitoring at national scale. This release includes 1,206 samples collected between December 2023 and December 2025 from 27 sites across nine states, covering 13 million people. Deep sequencing (∼1 billion read pairs per sample) generated 1.2 trillion read pairs (358 terabases), capturing diverse human, animal, and plant viruses including rare taxa. CASPER data tracks wastewater digital PCR and clinical abundance trends for SARS-CoV-2, influenza A, and respiratory syncytial virus, and recovers national-scale variant dynamics for SARS-CoV-2 and norovirus. As the largest publicly available untargeted wastewater sequencing dataset to date, CASPER provides a shared and growing resource for pathogen surveillance and microbial ecology.

Emerging infectious diseases often circulate undetected until they cause clinical illness, leaving surveillance systems reactive rather than anticipatory. The U.S. blood supply, with millions of whole-blood and plasma donations annually, offers an underutilized national resource for proactive pathogen surveillance. We propose integrating metagenomic sequencing (MGS) into existing blood collection and testing workflows to detect known and novel viruses in residual samples within days of collection. Unlike current blood screening, which targets a limited set of predefined pathogens, MGS captures a broad range of viral threats, including blood- and vector-borne agents that produce asymptomatic viremia and may be missed by syndromic surveillance. Modeling suggests that an annual investment of $5.5 million could detect a novel HIV-like pathogen before it infects 0.01% of the U.S. population. Building on established donor monitoring, testing, and privacy infrastructure, blood supply sequencing represents a deployment-ready opportunity to strengthen national and global biosecurity.

This article examines air sampling as an environmental surveillance strategy for early pathogen detection and offers a preliminary comparison of air and wastewater surveillance. Air sampling involves collecting bioaerosols to analyze the microbial composition of the air, utilizing techniques like PCR and metagenomic sequencing. Air sampling appears especially promising for detecting respiratory pathogens and highly transmissible pandemic agents, as these spread primarily via aerosols and droplets. The article details various air sampling techniques, their efficiency, and practical considerations, categorizing them into filtration, impaction, impingement, electrostatic precipitation, and condensation methods. It also explores the composition of airborne microbes, emphasizing the low concentration of viral nucleic acids and the challenges this poses for metagenomic sequencing. The selection of sampling locations, including indoor environments and airplanes, is discussed as critical for effective pathogen detection. Finally, the article contrasts air and wastewater sampling, concluding that while both methods should ideally be explored as layered defenses, air sampling does not collectively appear more promising than wastewater sampling.