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Die Zhang, Yong Ge, Xilin Wu, Haiyan Liu, Wenbin Zhang and Shengjie Lai
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accurac...
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Bolanle Adefowoke Ojokoh, Benjamin Aribisala, Oluwafemi A. Sarumi, Arome Junior Gabriel, Olatunji Omisore, Abiola Ezekiel Taiwo, Tobore Igbe, Uchechukwu Madukaku Chukwuocha, Tunde Yusuf, Abimbola Afolayan, Olusola Babalola, Tolulope Adebayo and Olaitan Afolabi
Coronavirus Disease 2019 (COVID-19) spreads rapidly and is easily contracted by individuals who come near infected persons. With this nature and rapid spread of the contagion, different types of research have been conducted to investigate how non-pharmac...
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Fleurianne Bertrand and Emilie Pirch
This paper investigates numerical properties of a flux-based finite element method for the discretization of a SEIQRD (susceptible-exposed-infected-quarantined-recovered-deceased) model for the spread of COVID-19. The model is largely based on the SEIRD ...
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Andrea Gatto, Gabriele Accarino, Valeria Aloisi, Francesco Immorlano, Francesco Donato and Giovanni Aloisio
Compartmental models have long been used in epidemiological studies for predicting disease spread. However, a major issue when using compartmental mathematical models concerns the time-invariant formulation of hyper-parameters that prevent the model from...
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Jui-Yao Liu, Tzeng-Ji Chen and Shinn-Jang Hwang
In the early stages of the 2019 novel coronavirus disease (COVID-19) pandemic, containment of disease importation from epidemic areas was essential for outbreak control. This study is based on publicly accessible data on confirmed COVID-19 cases in Taiwa...
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