Evidence map›Paper›PMID 41986360›Full record

ArticleNature communications2026

Investigating antibody cross-reactivity and transmission dynamics of alphaviruses and flaviviruses using a multiplex serological assay.

Victor Yman, Jason Rosado, Noé Ochida, Laura Garcia, Marie-Fabrice Gasasira, Gaëlle Baudemont, Estee Cramer, Myrielle Dupont-Rouzeyrol, Karl Huet, Maylis Douine and 14 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

24 authors.

Victor Yman *Infectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France.ORCID 0000-0001-7267-0749
Jason Rosado *Infectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France.
Noé OchidaMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, INSERM U1332, CNRS UMR2000, Paris, France.ORCID 0000-0003-2347-6426
Laura GarciaInfectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France.ORCID 0000-0001-8044-5365
Marie-Fabrice GasasiraInfectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France.
Gaëlle BaudemontInfectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France.ORCID 0009-0006-0345-7489
Estee CramerInfectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France.
Myrielle Dupont-RouzeyrolURE Dengue and Arboviruses, Institut Pasteur de Nouvelle-Calédonie, Noumea, New Caledonia.
Karl HuetURE Dengue and Arboviruses, Institut Pasteur de Nouvelle-Calédonie, Noumea, New Caledonia.
Maylis DouineCentre d'Investigation Clinique Guyane, Inserm 1424, Centre Hospitalier Universitaire de Guyane, UA17 Santé des Populations en Amazonie, Cayenne, French Guiana, France.
Alice SannaCentre d'Investigation Clinique Guyane, Inserm 1424, Centre Hospitalier Universitaire de Guyane, UA17 Santé des Populations en Amazonie, Cayenne, French Guiana, France.
Yann LambertCentre d'Investigation Clinique Guyane, Inserm 1424, Centre Hospitalier Universitaire de Guyane, UA17 Santé des Populations en Amazonie, Cayenne, French Guiana, France.ORCID 0000-0001-9020-3263
Gabriel Carrasco-EscobarInstituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.ORCID 0000-0002-6945-0419
Oscar NolascoInstituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.ORCID 0000-0002-5672-5516
Dionicia GamboaInstituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.
Gamou FallVirology Department, Institut Pasteur de Dakar, Dakar, Sénégal.ORCID 0000-0001-5035-1325
Oumar NdiayeVirology Department, Institut Pasteur de Dakar, Dakar, Sénégal.
Oumar FayeVirology Department, Institut Pasteur de Dakar, Dakar, Sénégal.
Cheikh LoucoubarEpidemiology, Clinical Research and Data sciences Department, Institut Pasteur de Dakar, Dakar, Sénégal.
Aissatou Toure-BaldeImmunophysiopathology and Infectious Diseases Department, Institut Pasteur de Dakar, Dakar, Sénégal.
Makhtar NiangImmunophysiopathology and Infectious Diseases Department, Institut Pasteur de Dakar, Dakar, Sénégal.ORCID 0000-0003-0810-4595
Ines Vigan-WomasImmunophysiopathology and Infectious Diseases Department, Institut Pasteur de Dakar, Dakar, Sénégal.
Simon CauchemezMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, INSERM U1332, CNRS UMR2000, Paris, France.ORCID 0000-0001-9186-4549
Michael T WhiteInfectious Disease Epidemiology & Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris Cité, INSERM U1347, Paris, France. michael.white@pasteur.fr.ORCID 0000-0002-7472-4138

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate serological tools are essential for monitoring the transmission of arboviruses with pandemic potential, yet cross-reactivity between closely related viruses hampers diagnostics and surveillance. Here, we develop a high-throughput multiplex serological assay to quantify antibody responses to 28 antigens from nine arboviruses (dengue, Zika, yellow fever, West Nile, Usutu, Japanese encephalitis, chikungunya (CHIKV), Mayaro (MAYV), and O'nyong-nyong virus) and apply it to over 4000 samples from epidemiologically distinct sites on four continents. We implement a flexible analytical method based on Bayesian finite mixture models and Receiver Operating Characteristic analysis to evaluate assay performance and define seropositivity thresholds. As a case study, we resolve cross-reactive and virus-specific responses for CHIKV and the emerging MAYV by combining competitive immunoassays with mathematical modelling of multiplex serological and epidemiological data. This approach yields cross-reactivity-adjusted estimates of local transmission dynamics, in agreement with existing epidemiological evidence, and reveals that CHIKV is more prone to induce cross-reactive antibody responses than MAYV. Our results demonstrate the power of combining multiplex serology with experimental validation and modelling to disentangle exposure histories in the face of serological cross-reactivity. This integrative approach holds promise for improving arbovirus surveillance, particularly in settings with overlapping transmission of multiple viruses and limited diagnostic capacity.

Indexed as

AlphavirusAlphavirus InfectionsAntibodies, ViralFlavivirusFlavivirus InfectionsAnimalsAntigens, ViralBayes TheoremChikungunya virusCross ReactionsEncephalitis Virus, JapaneseHumansImmunoassaySerologic TestsWest Nile FeverWest Nile virusAntibodies, ViralAntigens, Viral

Identifiers

PMID41986360
PMCPMC13083944

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LicenceCC BY-NC-ND
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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.