Estimating Viral Prevalence with Data Integration for Adaptive Two-Phase
Pooled Sampling
- Andrew Hoegh,
- Alison Peel,
- Wyatt Madden,
- Manuel Ruiz-Aravena,
- Aaron Morris,
- Alex Washburne,
- Raina Plowright
Abstract
1. The COVID-19 pandemic has highlighted the importance of efficient
sampling strategies and statistical methods for monitoring infection
prevalence, both in humans and reservoir hosts. Pooled testing can be an
efficient tool for learning pathogen prevalence in a population.
Typically pooled testing requires a second phase follow up procedure to
identify infected individuals, but when the goal is solely to learn
prevalence in a population, such as a reservoir host, there are more
efficient methods for allocating the second phase samples. 2. To
estimate pathogen prevalence in a population, this manuscript presents
an approach for data integration with two-phased testing of pooled
samples that allows more efficient estimation of prevalence with less
samples than traditional methods. The first phase uses pooled samples to
estimate the population prevalence and inform efficient strategies for
the second phase. To combine information from both phases, we introduce
a Bayesian data integration procedure that combines pooled samples with
individual samples for joint inferences about the population prevalence.
3. Data integration procedures result in more efficient estimation of
prevalence than traditional procedures that only use individual samples
or a single phase of pooled sampling. 4. The manuscript presents
guidance on implementing the first phase and second phase sampling plans
using data integration. Such methods can be used to assess the risk of
pathogen spillover from reservoir hosts to humans, or to track pathogens
such as SARS-CoV-2 in populations.18 Mar 2021Submitted to Ecology and Evolution 19 Mar 2021Submission Checks Completed
19 Mar 2021Assigned to Editor
25 Mar 2021Reviewer(s) Assigned
13 Apr 2021Review(s) Completed, Editorial Evaluation Pending
23 Apr 2021Editorial Decision: Revise Minor
10 Jun 20211st Revision Received
10 Jun 2021Submission Checks Completed
10 Jun 2021Assigned to Editor
10 Jun 2021Review(s) Completed, Editorial Evaluation Pending
10 Jun 2021Reviewer(s) Assigned
18 Jun 2021Editorial Decision: Accept