J 2023

Using real-time ascertainment rate estimate from infection and hospitalization dataset for modeling the spread of infectious disease: COVID-19 case study in the Czech Republic

PŘIBYLOVÁ, Lenka, Veronika ECLEROVÁ, Ondřej MÁJEK, Jiří JARKOVSKÝ, Tomáš PAVLÍK et. al.

Basic information

Original name

Using real-time ascertainment rate estimate from infection and hospitalization dataset for modeling the spread of infectious disease: COVID-19 case study in the Czech Republic

Authors

PŘIBYLOVÁ, Lenka (203 Czech Republic, guarantor, belonging to the institution), Veronika ECLEROVÁ (203 Czech Republic, belonging to the institution), Ondřej MÁJEK (203 Czech Republic, belonging to the institution), Jiří JARKOVSKÝ (203 Czech Republic, belonging to the institution), Tomáš PAVLÍK (203 Czech Republic, belonging to the institution) and Ladislav DUŠEK (203 Czech Republic, belonging to the institution)

Edition

PLoS ONE, Public Library of Science, 2023, 1932-6203

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10100 1.1 Mathematics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 3.700 in 2022

RIV identification code

RIV/00216224:14310/23:00131249

Organization unit

Faculty of Science

UT WoS

001030033800054

Keywords in English

COVID 19; Virus testing; Hospitals; Czech Republic; Hospitalizations; Infectious diseases; Respiratory infections; SARS CoV 2

Tags

International impact, Reviewed
Změněno: 9/3/2024 12:50, Mgr. Michaela Hylsová, Ph.D.

Abstract

V originále

We present a novel approach to estimate the time-varying ascertainment rate in almost real-time, based on the surveillance of positively tested infectious and hospital admission data. We also address the age dependence of the estimate. The ascertainment rate estimation is based on the Bayes theorem. It can be easily calculated and used (i) as part of a mechanistic model of the disease spread or (ii) to estimate the unreported infections or changes in their proportion in almost real-time as one of the early-warning signals in case of undetected outbreak emergence. The paper also contains a case study of the COVID-19 epidemic in the Czech Republic. The case study demonstrates the usage of the ascertainment rate estimate in retrospective analysis, epidemic monitoring, explanations of differences between waves, usage in the national Anti-epidemic system, and monitoring of the effectiveness of non-pharmaceutical interventions on Czech nationwide surveillance datasets. The Czech data reveal that the probability of hospitalization due to SARS-CoV-2 infection for the senior population was 12 times higher than for the non-senior population in the monitored period from the beginning of March 2020 to the end of May 2021. In a mechanistic model of COVID-19 spread in the Czech Republic, the ascertainment rate enables us to explain the links between all basic compartments, including new cases, hospitalizations, and deaths.

Links

EF16_013/0001761, research and development project
Name: RECETOX RI
EF17_043/0009632, research and development project
Name: CETOCOEN Excellence
MUNI/A/1132/2022, interní kód MU
Name: Matematické a statistické modelování 7
Investor: Masaryk University
MUNI/A/1342/2021, interní kód MU
Name: Matematické a statistické modelování 6 (Acronym: MaStaMo6)
Investor: Masaryk University
MUNI/A/1615/2020, interní kód MU
Name: Matematické a statistické modelování 5 (Acronym: MaStaMo5)
Investor: Masaryk University
MUNI/11/02202001/2020, interní kód MU
Name: Online platforma pro monitoring, analýzu a management epidemických situací v reálném čase
Investor: Masaryk University
857560, interní kód MU
(CEP code: EF17_043/0009632)
Name: CETOCOEN Excellence (Acronym: CETOCOEN Excellence)
Investor: European Union, Spreading excellence and widening participation
90121, large research infrastructures
Name: RECETOX RI

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