Terminating pandemics with smartwatches.

Märt Vesinurm, Martial Ndeffo-Mbah, Dan Yamin, Margaret L Brandeau

Abstract read

In one paragraph

Article in PNAS nexus, 2025. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Märt VesinurmDepartment of Industrial Engineering and Management, Aalto University School of Science, Maarintie 8, 02150 Espoo, Finland.ORCID https://orcid.org/0000-0001-7351-7834

Martial Ndeffo-MbahDepartment of Veterinary Integrative Biosciences, Texas A&M University, 664 Raymond Stotzer Pkwy, College Station, TX 77843, USA.ORCID https://orcid.org/0000-0003-4158-7613

Dan YaminDepartment of Management Science & Engineering, Stanford University, Huang Engineering Center, 475 Via Ortega, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0002-1131-5572

Margaret L BrandeauDepartment of Management Science & Engineering, Stanford University, Huang Engineering Center, 475 Via Ortega, Stanford, CA 94305, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have demonstrated that wearable devices, such as smartwatches, can accurately detect infections in presymptomatic and asymptomatic individuals. Yet, the extent to which smartwatches can contribute to prevention and control of infectious diseases through a subsequent reduction in social contacts is not fully understood. We developed a multiscale modeling framework that integrates within-host viral dynamics and between-host interactions to estimate the risk of viral disease outbreaks within a given population. We used the model to evaluate the population-level effectiveness of smartwatch detection in reducing the transmission of three COVID-19 variants and seasonal and pandemic influenza. With a 66% reduction in contacts after smartwatch-based disease detection, we estimate that the reproduction number

Indexed as

controlepidemicpandemicsmartwatcheswearables

Identifiers

PMID40045996

DOI10.1093/pnasnexus/pgaf044

PMCPMC11879515

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC

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Registered trials

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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.