Evidence map›Paper›PMID 39939526›Full record

ArticleNature medicine2025

Pandemic monitoring with global aircraft-based wastewater surveillance networks.

Guillaume St-Onge, Jessica T Davis, Laurent Hébert-Dufresne, Antoine Allard, Alessandra Urbinati, Samuel V Scarpino, Matteo Chinazzi, Alessandro Vespignani

Abstract read
In one paragraph

Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
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  5. Article
  6. Understanding patterns of variant emergence and spread in an ongoing epidemic.medRxiv : the preprint server for health sciences · 2026
    Article
  7. Article
  8. Article
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  10. Reconstructing the early spatial spread of pandemic respiratory viruses in the United States.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  11. Review
  12. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Guillaume St-OngeLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA. g.st-onge@northeastern.edu.ORCID http://orcid.org/0000-0001-5415-3748
Jessica T DavisLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
Laurent Hébert-DufresneVermont Complex Systems Institute, University of Vermont, Burlington, VT, USA.ORCID http://orcid.org/0000-0002-0008-3673
Antoine AllardVermont Complex Systems Institute, University of Vermont, Burlington, VT, USA.
Alessandra UrbinatiLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
Samuel V ScarpinoThe Roux Institute, Northeastern University, Portland, ME, USA.ORCID http://orcid.org/0000-0001-5716-2770
Matteo ChinazziLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
Alessandro VespignaniLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA. a.vespignani@northeastern.edu.ORCID http://orcid.org/0000-0003-3419-4205

Funding

Using Dengue Controlled Human Infection Model to Identify Adaptive Immune Correlates of ProtectionP20GM125498 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Kristen Pierce · 2018 to 2026
$24.9M
Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation) INV-058220Fonds de Recherche du Québec - Nature et Technologies (Quebec Fund for Research in Nature and Technology) 313475Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada 2019-05183Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada 2024-05626NIGMS NIH HHS P20 GM125498U.S. Department of Health & Human Services | Centers for Disease Control and Prevention (CDC) CDC-75D301Cl4810U.S. Department of Health & Human Services | Centers for Disease Control and Prevention (CDC) CDC-RFA-FT-23-0069U.S. Department of Health & Human Services | National Institutes of Health (NIH) 2P20GM125498-06
6 · The paper itself

Abstract

Aircraft wastewater surveillance has been proposed as a new approach to monitor the global spread of pathogens. Here we develop a computational framework providing actionable information for the design and estimation of the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potential and find that networks of 10-20 strategically placed wastewater sentinel sites can provide timely situational awareness and function effectively as an early warning system. The model identifies potential blind spots and suggests optimization strategies to increase WWSN effectiveness while minimizing resource use. Our findings indicate that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSN capabilities, emphasizing the importance of resource optimization. We show, through retrospective analyses, that WWSNs can notably shorten detection time for emerging pathogens. The approach presented offers a realistic analytic framework for the analysis of WWSNs at airports.

Indexed as

AircraftPandemicsWastewaterHumansWastewater

Identifiers

PMID39939526
PMCPMC11922747

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.