10.7910/DVN/3YZ8IE Kutima, Bernadette Bernadette Kutima KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Orindi, Benedict Benedict Orindi https://orcid.org/0000-0002-4601-7890 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Masinde, Augustine Augustine Masinde KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Gitonga, John John Gitonga KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Omuoyo, Donwilliams Donwilliams Omuoyo https://orcid.org/0000-0003-3900-5354 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Mugo, daisy daisy Mugo KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Muchiri, Samuel K. Samuel K. Muchiri KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Ochola-Oyier, Lynette Lynette Ochola-Oyier https://orcid.org/0000-0003-4393-0470 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Bejon, Philip Philip Bejon https://orcid.org/0000-0002-2135-7549 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Agweyu, Ambrose Ambrose Agweyu https://orcid.org/0000-0001-8760-1279 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Scott, J. Anthony G. J. Anthony G. Scott KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Uyoga, Sophie Sophie Uyoga https://orcid.org/0000-0003-1746-7873 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Snow, Robert Robert Snow https://orcid.org/0000-0003-3725-6088 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Kagucia, Eunice Wangeci Eunice Wangeci Kagucia https://orcid.org/0000-0002-4481-8889 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Warimwe, George George Warimwe https://orcid.org/0000-0002-4911-6333 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Nyagwange, James James Nyagwange https://orcid.org/0000-0001-5430-6011 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Harvard Dataverse 2026 Medicine, Health and Life Sciences Arboviruses Seroprevalence Multiplex Immunoassay Public Heath Surveillance Nyagwange, James James Nyagwange KEMRI-Wellcome Trust Research Programme, Center for Geographic Medicine Research, Kilifi, Kenya The Data Governance Committee KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya 2026-04-01 2026-04-01 2026-04-01 Open Access 1979 10763 12196 1455 1600 13752 2056 text/comma-separated-values text/plain text/comma-separated-values text/comma-separated-values text/x-stata-syntax type/x-r-syntax text/x-stata-syntax 2.0 Creative Commons Attribution 4.0 International License. <p>This is a replication dataset for the manuscript titled: "<strong><i>Seroprevalence of Dengue, Chikungunya and Rift Valley fever virus IgG antibodies in Kenyan blood donors</i></strong>."</p> <p>Aedes-borne arboviruses such as dengue (DENV), chikungunya (CHIKV), and Rift Valley fever virus (RVFV) are increasing globally due to climate change, urbanization, and increased human mobility, and continue to cause recurrent outbreaks in Kenya. However, national data on population exposure remain limited, with most studies being outdated or region-specific. Surveillance is further complicated by overlapping clinical symptoms, while molecular methods detect only short-term infections and serological approaches capture longer-term exposure. Conventional assays such as ELISAs and neutralization tests are often costly, time-consuming, or unsuitable for large-scale studies. To address this, we developed and validated a multiplex bead-based immunoassay (arbo-plex MIA) on the Luminex® platform for the simultaneous detection of IgG antibodies to DENV, CHIKV, and RVFV. Using the Foci Reduction Neutralization Test (FRNT) as the gold standard, we estimated the sensitivity and specificity of the assay, achieving a high proportion of correctly classified samples, and further compared its performance with commercial ELISAs to assess agreement. Assay optimization was conducted using multiple cohorts, including adult samples from coastal Kenya (n=147) for CHIKV and RVFV, and the KIPMAT (n=76) and CPGH (n=57) cohorts for DENV. Additional samples from Kilifi (n=795) and Nairobi (n=843) Health and Demographic Surveillance Systems (HDSS) were used for comparison with ELISAs, alongside a panel of pooled convalescent sera (n=10) from Kenya and Tunisia. The validated assay was then applied to a large national dataset of blood donor samples (n=11,420) to estimate seroprevalence. We used a Bayesian multilevel logistic regression framework to generate pathogen-specific estimates, accounting for age and sex differences in sampling. Assay performance was incorporated into the model through sensitivity and specificity parameters informed by validation data, with uncertainty propagated into the final estimates. Population-representative seroprevalence was obtained by post-stratifying model outputs using age and sex distributions from the 2019 Kenya Population and Housing Census.</p>