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@proceedings{1821361,
author = {Eclerová, Veronika and Přibylová, Lenka},
booktitle = {Epidemics8 - 8th International Conference on Infectious Disease Dynamics},
keywords = {ascertainment rate; epidemic monitoring; COVID-19; SARS-CoV-2},
language = {eng},
title = {Ascertainment rate estimate from hospital data used in modelling COVID-19 epidemics},
url = {https://www.elsevier.com/events/conferences/international-conference-on-infectious-disease-dynamics},
year = {2021}
}
TY - CONF
ID - 1821361
AU - Eclerová, Veronika - Přibylová, Lenka
PY - 2021
TI - Ascertainment rate estimate from hospital data used in modelling COVID-19 epidemics
KW - ascertainment rate
KW - epidemic monitoring
KW - COVID-19
KW - SARS-CoV-2
UR - https://www.elsevier.com/events/conferences/international-conference-on-infectious-disease-dynamics
N2 - We based our approach on a mechanistic compartmental SEIR model with additional undetected cohort A (stands for absent infected). To estimate the size of compartment A, we use a novel concept, a moving ascertainment rate estimate computed from data of hospitalized subjects. We estimate the probability of detection from the proportion of cases not detected before hospital admission using a conditional probability. We have developed an extended ZSEIAR model that also includes unknown dynamics in the affected clusters. We optimize the size of affected clusters in the model since the effects as seasonality or government measures cannot be easily distinguished. We submit our predictions to European Covid-19 Forecast Hub https://covid19forecasthub.eu/ and the web Czech Monitoring, Analysis and Management of Epidemic Situations https://webstudio.shinyapps.io/MAMES/.
ER -
ECLEROVÁ, Veronika and Lenka PŘIBYLOVÁ. Ascertainment rate estimate from hospital data used in modelling COVID-19 epidemics. In \textit{Epidemics8 - 8th International Conference on Infectious Disease Dynamics}. 2021.
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