Pathogen Early Warning: New Technologies and Approaches

The document outlines a 'layered detection' strategy for early warning of infectious disease outbreaks, focusing on the integration of metagenomic sequencing, multiplexed detection, environmental surveillance, serological testing, non-invasive wearables, point-of-person tests, and digital detection. It provides specific research and development recommendations for U.S. government agencies and other stakeholders to move these technologies from early-stage research to large-scale procurement and deployment.

• Metagenomic sequencing is presented as a cornerstone technology for early warning because it can identify any pathogen—virus, bacterium, fungus, or parasite—by analyzing DNA or RNA, allowing for the detection of novel threats that current diagnostics cannot identify.
• Massively multiplexed detection, including CRISPR-based and microarray-based approaches, allows for a 'pan-pathogen panel' that can test for all known pathogens using a single sample, though it is less capable than metagenomic sequencing at detecting entirely novel pathogens.
• Environmental detection, specifically wastewater sequencing, provides a more accurate means of tracking community infection dynamics than clinical testing alone because it captures asymptomatic and presymptomatic cases.
• Serological detection, which identifies antibodies, is essential for understanding pathogen transmissibility and monitoring sentinel populations for asymptomatic infections, though it is less effective in the very early stages of an individual's infection.
• Non-invasive detection via wearables (such as Oura Rings) can detect physiological changes, like skin temperature fluctuations, to identify infections before symptoms appear, though high false-positive rates remain a primary challenge.
• Point-of-person tests, particularly emerging CRISPR-based diagnostics, aim to combine the accuracy of PCR tests with the speed and low cost of rapid tests, enabling rapid reconfiguration for new pathogens.
• Digital detection tools, such as those used by BlueDot and ProMED, leverage AI, machine learning, and the analysis of official and unofficial datasets to provide early international alerts and predict the spread of outbreaks.

APA

Beaver, B., Sharma, S., Swett, J., Teran, N., Bajema, N., & Lim, Y.-B. (2021). Pathogen Early Warning: New Technologies and Approaches. The Council on Strategic Risks. https://councilonstrategicrisks.org/wp-content/uploads/2021/08/Pathogen-Early-Warning_New-Technologies-and-Approaches_BRIEFER-23_2021_08_16.pdf

Chicago

Beaver, Bill, Sid Sharma, Jacob Swett, Nikki Teran, Natasha Bajema, and Yong-Bee Lim. Pathogen Early Warning: New Technologies and Approaches. The Council on Strategic Risks, 2021. https://councilonstrategicrisks.org/wp-content/uploads/2021/08/Pathogen-Early-Warning_New-Technologies-and-Approaches_BRIEFER-23_2021_08_16.pdf.

Wikipedia

{{cite report |last1=Beaver |first1=Bill |last2=Sharma |first2=Sid |last3=Swett |first3=Jacob |last4=Teran |first4=Nikki |last5=Bajema |first5=Natasha |last6=Lim |first6=Yong-Bee |title=Pathogen Early Warning: New Technologies and Approaches |publisher=The Council on Strategic Risks |date=16 August 2021 |url=https://councilonstrategicrisks.org/wp-content/uploads/2021/08/Pathogen-Early-Warning_New-Technologies-and-Approaches_BRIEFER-23_2021_08_16.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{beaver2021pathogen, author = {Beaver, Bill and Sharma, Sid and Swett, Jacob and Teran, Nikki and Bajema, Natasha and Lim, Yong-Bee}, title = {{Pathogen Early Warning: New Technologies and Approaches}}, institution = {The Council on Strategic Risks}, year = {2021}, month = aug, url = {https://councilonstrategicrisks.org/wp-content/uploads/2021/08/Pathogen-Early-Warning_New-Technologies-and-Approaches_BRIEFER-23_2021_08_16.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }