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Transl. Med."],"published-print":{"date-parts":[[2025,11,26]]},"abstract":"<jats:p>\n                    Multiplex immunoassays can facilitate the parallel measurement of antibody responses against multiple antigenically related pathogens, generating a wealth of high-dimensional data that depict complex antibody-antigen relationships. In this study, we developed a generalizable analytical framework to maximize inferences from multipathogen serological studies. We fit the model to measurements of immunoglobulin antibody binding against 10 arboviral pathogens from a cross-sectional study in northwest Bangladesh with 1453 participants. We used our framework to jointly infer the prevalence of each pathogen by location and age as well as between-pathogen antibody cross-reactivity. Reconstructing immunological profiles, we found evidence of endemic transmission of Japanese encephalitis virus and recent outbreaks of dengue and chikungunya viruses in this district. Our estimates of antibody cross-reactivity were highly correlated with phylogenetic distances inferred from genetic data [correlation coefficient (\n                    <jats:italic toggle=\"yes\">r<\/jats:italic>\n                    )\u00a0=\u00a00.94], demonstrating how antigenic landscapes can be inferred from population-level serological studies. Furthermore, we showed how our framework could be used to identify the presence of antigenically related pathogens that were not directly tested for, representing a potential opportunity for the detection of emerging pathogens. The presented analytical framework offers a tool that can be applied to a growing number of multipathogen studies and will help support the integration of serological testing into disease surveillance platforms.\n                  <\/jats:p>","DOI":"10.1126\/scitranslmed.ads8680","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T18:58:16Z","timestamp":1764183496000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":7,"title":["Epidemiological and antigenic inferences from serological cross-reactivity among arboviruses"],"prefix":"10.1126","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7972-5703","authenticated-orcid":true,"given":"Megan","family":"O\u2019Driscoll","sequence":"first","affiliation":[{"name":"Department of Genetics, University of Cambridge, Cambridge CB23EH, UK."},{"name":"Institute of Global Health, University of Geneva, 1211 Geneva, 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Santos","sequence":"additional","affiliation":[{"name":"Department of Genetics, University of Cambridge, Cambridge CB23EH, UK."},{"name":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1453-4132","authenticated-orcid":true,"given":"Damien","family":"Hoinard","sequence":"additional","affiliation":[{"name":"Environment and Infectious Risks Unit, Institut Pasteur, 75015 Paris, France."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4103-4835","authenticated-orcid":true,"given":"Mohammed Ziaur","family":"Rahman","sequence":"additional","affiliation":[{"name":"International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka 1213, 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