Logo image
Back
Leveraging network structure to improve pooled testing efficiency
Journal article   Open access   Peer reviewed

Leveraging network structure to improve pooled testing efficiency

Daniel K. Sewell
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, Vol.71(5), pp.1648-1662
09/16/2022
DOI: 10.1111/rssc.12594
PMCID: PMC9826453
PMID: 36632279
Appears in  UI Libraries Support Open Access
url
https://doi.org/10.1111/rssc.12594View
Published (Version of record)CC BY-NC V4.0,  Open Access

Abstract

Screening is a powerful tool for infection control, allowing for infectious individuals, whether they be symptomatic or asymptomatic, to be identified and isolated. The resource burden of regular and comprehensive screening can often be prohibitive, however. One such measure to address this is pooled testing, whereby groups of individuals are each given a composite test; should a group receive a positive diagnostic test result, those comprising the group are then tested individually. Infectious disease is spread through a transmission network, and this paper shows how assigning individuals to pools based on this underlying network can improve the efficiency of the pooled testing strategy, thereby reducing the resource burden. We designed a simulated annealing algorithm to improve the pooled testing efficiency as measured by the ratio of the expected number of correct classifications to the expected number of tests performed. We then evaluated our approach using an agent-based model designed to simulate the spread of SARS-CoV-2 in a school setting. Our results suggest that our approach can decrease the number of tests required to regularly screen the student body, and that these reductions are quite robust to assigning pools based on partially observed or noisy versions of the network.
 Mathematics Physical Sciences Science & Technology Statistics & Probability UIOWA OA Agreement

Details

Metrics

3 Record Views
1 Times Cited - Web of Science
Logo image