Article In: orcid, scopus

Decision support tool to define the optimal pool testing strategy for SARS-CoV-2

Decision Support Systems

Barracosa B.; Felício J.; Pinto-Varela T.2023Elsevier

Key information

Authors:

Barracosa B.; Felício J.; Carvalho A.; Moreira L.M. (Leonilde de Fátima Morais Moreira); Mendes F. (Filipa Fernandes Mendes); Verde S.C.; Pinto-Varela T. (Tânia Rute Xavier de Matos Pinto Varela)

Published in

12/01/2023

Abstract

This work proposes a holistic decision support tool to be used by diverse stakeholders and decision-makers, integrating experimental data. Considering the characteristics of each region, the tool aids in defining the most suitable testing strategies per country or region: number of tests, time, cost, type of pool strategy based on prevalence rate interval, and the use of centralization vs. decentralization of testing strategies. The tool contributes to the field of decision support systems theoretically by introducing a novel model for testing decisions in extreme situations within a specific region, and practically, by demonstrating how laboratory data can be applied to real-life decision-making in that same region. This tool has been validated with two real case studies (Portugal and France) and has applied, as input data, real experimental results. The results suggested tree- and matrix-based strategies for low and high prevalence rates. A decentralized testing strategy improves the financial and time gains introduced by pool testing; however, centralizing the decisions shows a more straightforward implementation and resource management of the pool testing system with a low-performance loss. Therefore, there might be a solution to consider overcoming operational restrictions.

Publication details

Authors in the community:

Publisher

Elsevier

Link to the publisher's version

https://doi.org/10.1016/j.dss.2023.114046

Title of the publication container

Decision Support Systems

Volume

175

ISSN

0167-9236

Fields of Science and Technology (FOS)

mathematics - Mathematics

Publication language (ISO code)

eng - English

Rights type:

Only metadata available

Financing entity

European Commission

Identifier for the funding entity: UIDB/00097/2020