TY - JOUR
T1 - Investigating antibody cross-reactivity and transmission dynamics of alphaviruses and flaviviruses using a multiplex serological assay
AU - Yman, Victor
AU - Rosado, Jason
AU - Ochida, Noé
AU - Garcia, Laura
AU - Gasasira, Marie Fabrice
AU - Baudemont, Gaëlle
AU - Cramer, Estee
AU - Dupont-Rouzeyrol, Myrielle
AU - Huet, Karl
AU - Douine, Maylis
AU - Sanna, Alice
AU - Lambert, Yann
AU - Carrasco-Escobar, Gabriel
AU - Nolasco, Oscar
AU - Gamboa, Dionicia
AU - Fall, Gamou
AU - Ndiaye, Oumar
AU - Faye, Oumar
AU - Loucoubar, Cheikh
AU - Toure-Balde, Aissatou
AU - Niang, Makhtar
AU - Vigan-Womas, Ines
AU - Cauchemez, Simon
AU - White, Michael T.
N1 - Publisher Copyright:
© The Author(s) 2026.
PY - 2026/12
Y1 - 2026/12
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105035819829
U2 - 10.1038/s41467-026-71451-7
DO - 10.1038/s41467-026-71451-7
M3 - Artículo
C2 - 41986360
AN - SCOPUS:105035819829
SN - 2041-1723
VL - 17
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 3491
ER -