2021/11/11 by Braden Scherting, Alison J. Peel, Scherting, Braden +5
Agricultural and Biological Sciences · Medicine · #Animal Disease Management and Epidemiology #Applications (stat.AP) #FOS: Computer and information sciences #Viral gastroenteritis research and epidemiology #Zoonotic diseases and public health
paper · pdf · doi:10.48550/arxiv.2111.06249
openalex publication_date 2021/11/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Estimating the prevalence of a disease is necessary for evaluating and mitigating risks of its transmission within or between populations. Estimates that consider how prevalence changes with time provide more information about these risks but are difficult to obtain due to the necessary sampling intensity and commensurate testing costs. We propose pooling and jointly testing multiple samples to reduce testing costs and use a novel nonparametric, hierarchical Bayesian model to infer population prevalence from the pooled test results. This approach is shown to reduce uncertainty compared to individual testing at the same budget and to produce similar estimates compared to individual testing at a much higher budget through two synthetic studies and two case studies of natural infection data.