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  4. Redacs: Regional Emergency-Driven Adaptive Cluster Sampling For Effective Covid-19 Management
 
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Redacs: Regional Emergency-Driven Adaptive Cluster Sampling For Effective Covid-19 Management

Journal
Stochastic Analysis and Applications
Date Issued
2022-02-25
Author(s)
Stehlik, Milán  
Facultad de Ciencias  
J. Kiseľák
Dinamarca, Alejandro  
Facultad de Farmacia  
E. Alvarado
F. Plaza
F.A. Medina
S. Stehlíková
J. Marek
B. Venegas
A. Gajdoš
Y. Li
S. Katuščák
A. Bražinová
E. Zeintl
Y. Lu
DOI
10.1080/07362994.2022.2033126
WoS ID
WOS:000761711800001
Abstract
As COVID-19 is spreading, national agencies need to monitor and track several metrics. Since we do not have perfect testing programs on the hand, one needs to develop an advanced sampling strategies for prevalence study, control and management. Here we introduce REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management and control and justify its usage for COVID-19. We show its advantages over classical massive individual testing sampling plans. We also point out how regional and spatial heterogeneity underlines proper sampling. Fundamental importance of adaptive control parameters from emergency health stations and medical frontline is outlined. Since the Northern hemisphere entered Autumn and Winter season (this paper was originally submitted in November 2020), practical illustration from spatial heterogeneity of Chile (Southern hemisphere, which already experienced COVID-19 winter outbreak peak) is underlying the importance of proper regional heterogeneity of sampling plan. We explain the regional heterogeneity by microbiological backgrounds and link it to behavior of Lyapunov exponents. We also discuss screening by antigen tests from the perspective of "on the fly" biomarker validation, i.e., during the screening.
Subjects

Applied Mathematics

Mathematics, Applied

Statistics And Probab...

Statistics, Probabili...

OCDE Subjects

Natural Sciences::Phy...

Quartile (Date Issued)
Q4
License
acceso abierto

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