Evidence map›Paper›PMID 39132478›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Optimization and performance analytics of 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 readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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 02115, USA.ORCID 0000-0001-5415-3748
Jessica T DavisLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0003-0726-1855
Laurent Hébert-DufresneVermont Complex Systems Center, University of Vermont, Burlington, VT 05401, USA.ORCID 0000-0002-0008-3673
Antoine AllardVermont Complex Systems Center, University of Vermont, Burlington, VT 05401, USA.ORCID 0000-0002-8208-9920
Alessandra UrbinatiLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0002-9031-1763
Samuel V ScarpinoInstitute for Experiential AI, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0001-5716-2770
Matteo ChinazziLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0002-5955-1929
Alessandro VespignaniLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA 02115, USA.ORCID 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
NIGMS NIH HHS P20 GM125498
6 · The paper itself

Abstract

Aircraft wastewater surveillance has been proposed as a novel approach to monitor the global spread of pathogens. Here we develop a computational framework to provide actionable information for designing and estimating the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potentials and find that networks of 10 to 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 WWSNs effectiveness while minimizing resource use. Our findings highlight that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSNs capabilities, stressing the importance of resource optimization. We show through retrospective analyses that WWSNs can significantly shorten the detection time for emerging pathogens. The presented approach offers a realistic analytic framework for the analysis of WWSNs at airports.

Identifiers

PMID39132478
PMCPMC11312644

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.