Evidence map›Paper›PMID 37982071›Full record

ArticleStochastic analysis and applications2023

REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management.

M Stehlík, J Kisel'ák, A Dinamarca, E Alvarado, F Plaza, F A Medina, S Stehlíková, J Marek, B Venegas, A Gajdoš and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Stochastic analysis and applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. On regime changes of COVID-19 outbreak.Journal of applied statistics · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

M StehlíkLinz Institute of Technology & Department of Applied Statistics, J. Kepler University in Linz, Linz, Austria.ORCID 0000-0003-2749-5990
J Kisel'ákInstitute of Mathematics, Faculty of Science, P.J.Šafárik University, Košice, Slovakia.
A DinamarcaCentro de Micro-Bioinnovación, Escuela de Nutrición y Dietética, Facultad de Farmacia, Universidad de Valparaíso, Valparaíso, Chile.
E AlvaradoInstituto de Estadística, Universidad de Valparaíso, Valparaíso, Chile.
F PlazaInstituto de Estadística, Universidad de Valparaíso, Valparaíso, Chile.
F A MedinaBiostatistics Program, School of Public Health, University of Chile, Santiago, Chile.ORCID 0000-0003-4486-9237
S StehlíkováLinz Institute of Technology & Department of Applied Statistics, J. Kepler University in Linz, Linz, Austria.
J MarekUniversity of Pardubice, Pardubice, Czech Republic.
B VenegasDepartamento de Estomatología, Facultad de Ciencias de la Salud, Universidad de Talca, Chile.
A GajdošFacultad de Ingeniería, Universidad Andrés Bello, Valparaíso, Chile.
Y LiThe University of Iowa, Iowa City, Iowa, USA.
S KatuščákEmeritus Prof.STU, Senior Konzulting, ESK.
A BražinováInstitute of Epidemiology, Faculty of Medicine in Bratislava, Comenius University, Slovak Republic.
E ZeintlLinz Institute of Technology & Department of Applied Statistics, J. Kepler University in Linz, Linz, Austria.
Y LuDepartment of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA.ORCID 0000-0002-7698-8962

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Statistical Methods for Optimizing Personalized Treatment SelectionR01HL089778 · NHLBI · STANFORD UNIVERSITY · PI LU TIAN · 2008 to 2026
$4.8M
NCATS NIH HHS UL1 TR003142NHLBI NIH HHS R01 HL089778
6 · The paper itself

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.

Indexed as

ACSantigen test validationprevalenceREDACSsampling

Identifiers

PMID37982071
PMCPMC10655945

What Socratic holds

Textmetadata
LicenceTDM
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.