2020/11/11 by Li‐Chun Zhang, Zhang, Li-Chun
Mathematics · Medicine · #Applications (stat.AP) #FOS: Biological sciences #FOS: Computer and information sciences #HIV, Drug Use, Sexual Risk #Methodology (stat.ME) #Populations and Evolution (q-bio.PE) #Statistical Methods and Bayesian Inference #Survey Sampling and Estimation Techniques
paper · pdf · doi:10.48550/arxiv.2011.08669
openalex publication_date 2020/11/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Intuitively, sampling is likely to be more efficient for prevalence estimation, if the cases (or positives) have a relatively higher representation in the sample than in the population. In case the virus is transmitted via personal contacts, contact tracing of the observed cases (but not noncases), to be referred to as adaptive network tracing, can generate a higher yield of cases than random sampling from the population. The efficacy of relevant designs for cross-sectional and change estimation is investigated. The availability of these designs allows one unite tracing for combating the epidemic and sampling for estimating the prevalence in a single endeavour.