Collection
Application of advanced statistical methods in infectious diseases
BMC Infectious Diseases is calling for submissions to our Collection on application of advanced statistical methods in infectious diseases. We aim to highlight the innovative use of statistical methods beyond traditional approaches, thereby advancing our understanding of infectious diseases and improving public health interventions. The journal welcomes research and review submissions addressing but not limited to: advanced statistical methods in infectious diseases, including bioinformatics analysis, machine learning, Bayesian methods, network analysis, choice and interpretation of advanced statistical analyses, spatial and spatio-temporal methods, longitudinal data analysis, multivariate techniques, data integration, meta-analysis, and statistical modeling of vaccine efficacy and emerging infectious diseases.
Articles (2 in this collection)
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Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model
Authors (first, second and last of 9)
