Tracking Rt of COVID-19 Vaccine Effectiveness Using Kalman Filter and SIRD Model

In this paper, a SIRD model is adapted to study the vaccine's impact on the spread of coronavirus (COVID19) spread in Lebanon. To describe the epidemic development across the country, a Kalman filter is integrated with the SIRD model in order to estimate the time-varying reproduction number R t...

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Bibliographic Details
Published in2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME) pp. 151 - 154
Main Authors Kaddour, Mahmoud, Charafeddine, Jinan, Moubayed, Nazih
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.10.2021
Subjects
Adaptation models
COVID - 19
Data models
Kalman filter
Pandemics
Predictive models
SIRD model
Sociology
Vaccines
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Summary:In this paper, a SIRD model is adapted to study the vaccine's impact on the spread of coronavirus (COVID19) spread in Lebanon. To describe the epidemic development across the country, a Kalman filter is integrated with the SIRD model in order to estimate the time-varying reproduction number R t - is the most important indicator that predicts the severity of an epidemic outbreak. R t denotes the number of healthy persons to whom an infected person can spread the disease. The results show a reduction in the spread of the pandemic after employing the vaccine. All the data and relevant codebase are available at https://www.moph.gov.lb
ISSN:2377-5696
DOI:10.1109/ICABME53305.2021.9604831