Traveler-based Genomic Surveillance: A Scalable Approach to Early Pathogen Detection and Global Biosecurity

The CDC's Traveler-based Genomic Surveillance (TGS) program, implemented from 2021 to 2024, successfully utilized anonymous nasal samples from international travelers and aviation wastewater to enable early, scalable detection and genomic monitoring of global infectious threats like SARS-CoV-2, influenza, and monkeypox before they spread widely within the U.S.

The Gist

Imagine the United States has a giant, invisible "early warning system" built right at its airport gates. This isn't a system of security guards checking passports, but a scientific team looking for invisible germs before they can spread into the general population. This paper describes how the CDC built and ran this system, called Traveler-based Genomic Surveillance (TGS), between 2021 and 2024.

Here is how it works, broken down into simple concepts:

1. The Two "Sensors": The Nose and the Sink

The system uses two different ways to catch germs, kind of like having two different types of smoke detectors in a house.

• The Nose (Volunteer Swabs): Imagine a friendly volunteer at the airport asking travelers, "Hey, would you mind taking a quick nose swab to help us keep everyone safe?" About 700,000 people said yes. They didn't have to be sick; they just had to be arriving on an international flight.

  • How it works: The lab takes these swabs and mixes them together in groups (like mixing 10 cups of coffee to test the flavor). If the "group cup" tastes bad (tests positive), they test the individual cups to see who has the "bad coffee."
  • The Benefit: This gives them a list of specific people and where they came from, but it relies on people volunteering.

• The Sink (Wastewater): This is the "no-touch" sensor. Every time a plane lands, the crew can collect a sample from the airplane's toilet waste (or from the airport's main waste pipe that collects from many planes).

  • How it works: It's like checking the drain of a busy restaurant kitchen. You don't know exactly who used the sink, but you know what everyone who ate there left behind. If there are germs in the drain, the kitchen is infected.
  • The Benefit: This catches germs from everyone on the plane, even those who didn't want to be swabbed or didn't know they were sick.

2. The "Super-Scanner" (Genomic Sequencing)

Once the system finds a germ (like the virus that causes COVID-19, the flu, or RSV), it doesn't just say, "Oh, there's a virus." It acts like a high-tech fingerprint scanner.

It reads the genetic code of the virus to see exactly which "version" or "variant" it is. Think of it like identifying a specific model of a car. Is it a 2020 Ford? A 2024 Ford with a new engine? This helps scientists know if a new, tricky version of a virus is arriving from another country before it starts spreading locally.

3. What They Found

The paper reports on three years of data:

• It worked fast: They could tell the public about a new virus variant in about 11 days from the time the sample was collected.
• It caught the big waves: They saw the different versions of COVID-19 (like Delta, Omicron, and its many children) arrive in the U.S. just as they were changing around the world.
• It caught other bugs: They didn't just look for COVID. They also found the flu, RSV (a common respiratory virus), and stomach viruses in the wastewater.
• It acted as a radar for trouble:
  • China's Surge (2022): When China suddenly stopped its strict lockdowns and cases spiked, the U.S. didn't have much data from inside China. The TGS system acted as a window, showing the U.S. exactly which virus versions were coming out of China before the rest of the world knew.
  • Monkeypox & Pneumonia: When there were scary reports of new outbreaks in Africa or China, the system quickly switched its "sensors" to look for those specific germs. They found nothing for monkeypox in the wastewater, which was good news.

4. Why This Matters

The paper argues that this system is a blueprint for the future.

• Voluntary is better than forced: They proved you don't need to force people to get tested to get good data. People were happy to help voluntarily.
• Filling the blind spots: Many countries stopped testing for viruses after the pandemic peak. This system acts as a "backup camera" for the world, spotting germs in places where other countries aren't looking anymore.
• Speed: Because they are looking at travelers, they see the germs before they hit the local neighborhoods, giving public health officials a head start.

The Limitations (The Fine Print)

The authors are honest about what the system can't do:

• It's not a census. It doesn't tell them exactly how many people in a whole country are sick, just what's arriving at the airport.
• It can't trace a specific sick person back to their home address (because the nose swabs are anonymous).
• It only works if airlines and airports cooperate to let them take the wastewater samples.

In short: This paper describes a successful experiment where the U.S. built a "germ radar" at its airports using volunteer nose swabs and airplane toilet water. It successfully spotted new virus versions and outbreaks from around the world, proving that this kind of "early warning" system is possible, fast, and effective without needing to force anyone to participate.

Technical Summary

1. Problem Statement

The rapid global spread of infectious diseases via international travel necessitates early detection systems that can identify pathogens before they establish widespread community transmission. Traditional clinical surveillance is often insufficient because it relies on symptomatic individuals seeking care, leading to significant delays and "blind spots," particularly in regions with limited genomic sequencing capacity.

• Context: During the COVID-19 pandemic, global SARS-CoV-2 sequencing and testing declined by approximately 95% after January 2022, creating gaps in global pathogen tracking.
• Challenge: There is a need for a scalable, multi-modal surveillance system that can detect emerging variants and pathogens in near-real-time without relying on mandatory testing or disrupting travel.

2. Methodology

The study describes the Traveler-based Genomic Surveillance (TGS) program, a public-private partnership between the CDC, Ginkgo Biosecurity, and XpresCheck. The program operated from September 2021 to August 2024 across eight U.S. international airports.

A. Data Collection Modalities

1. Voluntary Nasal Swabs:
   • Population: Anonymous, voluntary participation by international travelers (aged ≥18) regardless of symptoms.
   • Process: Participants self-collected anterior nasal swabs and completed a brief questionnaire regarding demographics and travel itinerary.
   • Sampling Strategy: Initially, single swabs were collected. Later, two swabs were collected (one for pooled testing, one held for reflex testing).
   • Testing: Samples were pooled (5–25 swabs) and tested via RT-PCR. If a pool tested positive for SARS-CoV-2, Influenza A/B, or RSV, individual swabs were reflex-tested.
2. Aviation Wastewater Surveillance:
   • Sources: Samples collected from individual airplane lavatory service ports and airport "triturators" (composite samples from multiple flights).
   • Advantage: Does not require individual traveler consent; captures a composite of travelers on a flight.
   • Testing: RT-PCR (early phase) and RT-digital PCR (later phase) for respiratory and gastrointestinal pathogens.

B. Genomic Sequencing & Analysis

• Sequencing: All SARS-CoV-2 positive samples (nasal and wastewater) underwent whole-genome sequencing. Influenza and RSV positive individual nasal samples were also sequenced.
• Lineage Deconvolution: Wastewater samples underwent deconvolution to identify multiple co-circulating lineages.
• Turnaround Time: Defined as days from sample collection to result/sequence submission.
• Scope: The program monitored SARS-CoV-2, Influenza A/B, RSV, Mycoplasma pneumoniae, and other pathogens (e.g., Monkeypox, Norovirus) based on emerging global threats.

3. Key Contributions

• First Large-Scale Implementation: This is the first real-world, anonymized, multi-pathogen surveillance system implemented across multiple U.S. airports, engaging nearly 700,000 travelers.
• Multi-Modal Integration: Successfully integrated nasal swabs (high granularity, traveler metadata) and aviation wastewater (broad coverage, no individual metadata) into a unified platform.
• Scalability and Adaptability: The system demonstrated the ability to rapidly pivot in response to specific global events (e.g., expanding operations during the China COVID surge, adding M. pneumoniae testing, screening for Monkeypox).
• Voluntary Model: Proved that large-scale, effective pathogen surveillance can be achieved through voluntary participation without mandatory testing, maintaining public trust and high engagement.

4. Key Results

• Participation & Volume:
  • Nasal Swabs: 694,798 travelers participated; 67,308 pools were tested.
  • Wastewater: 495 airplane samples and 443 triturator samples were collected.
• SARS-CoV-2 Detection:
  • Nasal: 20.8% (13,990/67,308) of pools were positive.
  • Wastewater: 80.8% of airplane samples and 96.6% of triturator samples were positive.
  • Sequencing: Median turnaround time for GISAID submission was 11 days (IQR 10–13).
  • Variant Tracking: Successfully tracked the evolution from Delta to Omicron sub-lineages (BA.1 through JN.1, KP.2, KP.3).
• Other Pathogens:
  • Respiratory: High positivity for Influenza A/B and RSV in Dec/Jan; H3N2 was the predominant Influenza A subtype in 2024.
  • Gastrointestinal: Norovirus and Adenovirus F were frequently detected in wastewater year-round.
• Response to Specific Events:
  • China Surge (Dec 2022–Jan 2023): TGS detected the rise in cases and identified BA.5.2 and BF.7 variants one week before WHO-reported case counts increased, filling a critical data gap.
  • M. pneumoniae: Detected in travelers from South America but not China; confirmed susceptibility to macrolides.
  • Monkeypox (Clade I): No positive detections in wastewater samples from Central Africa travelers.

5. Significance and Implications

• Early Warning System: The TGS program serves as a critical "sentinel" for global biosecurity, detecting pathogens entering the U.S. before they spread locally. It effectively mitigates blind spots caused by declining global sequencing efforts.
• Public Health Utility: The data generated informed public health responses, such as evaluating the impact of pre-departure testing policies and monitoring the re-emergence of antimicrobial-resistant pathogens.
• Global Replicability: The program offers a viable model for global replication. It demonstrates that integrating voluntary traveler surveillance with wastewater epidemiology can be a core component of pandemic preparedness.
• Limitations: The system is subject to participation bias (voluntary), does not provide nationally representative prevalence estimates, and wastewater data cannot be linked to individual travelers for contact tracing. Geographic coverage is limited by direct flight volumes.

Conclusion: The TGS program successfully transitioned from a pilot to a national surveillance system, proving that a nimble, multi-modal approach combining traveler swabs and aviation wastewater can provide timely, high-quality genomic data essential for global health security.