Modelling serological multiplex bead assays responses: A case study from Malaysia.

Background: Multiplex bead assays (MBAs) provide quantitative measurements of many analytes from small sample volumes, reducing cost and processing time compared with traditional immunoassays. These advantages have made MBAs valuable for studying diverse diseases, particularly in low-resource settings. However, most analytical approaches focus on individual diseases, while integrated surveillance platforms would benefit from methods that jointly analyse the full range of pathogens included in multiplex assays. Methods: We applied factor analysis combined with a Dirichlet process mixture model to identify sub-populations based on MBA responses and assess whether these groups show spatial patterns or share socioeconomic characteristics and disease exposures. Data were drawn from four districts in northern Sabah, Malaysia, and included antibody responses for several neglected tropical diseases (NTDs): strongyloidiasis, lymphatic filariasis, giardiasis, toxoplasmosis, trachoma, and yaws. Results: The model identified four distinct sub-populations. Three of these were spatially distributed and included people with similar socioeconomic profiles. These shared characteristics may help explain the antibody patterns observed within each group, offering a comprehensive characterization of each sub-population. Conclusion: The presented analytical workflow, combining factor analysis, Dirichlet process mixture modelling, and spatial analysis, offers a replicable approach for identifying multi-disease exposure clusters that could inform integrated, targeted interventions.