Detailed Information on Publication Record
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 |
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| EF17_043/0009632, research and development project |
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| MUNI/A/1132/2022, interní kód MU |
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| MUNI/A/1342/2021, interní kód MU |
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| MUNI/A/1615/2020, interní kód MU |
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| MUNI/11/02202001/2020, interní kód MU |
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| 857560, interní kód MU (CEP code: EF17_043/0009632) |
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| 90121, large research infrastructures |
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