Forecasting and analyzing the dynamics of the outbreak in Hubei and Turkey
Yükleniyor...
Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Bilim Akademisi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-ShareAlike 3.0 United States
Attribution-NonCommercial-ShareAlike 3.0 United States
Özet
As the pandemic of Coronavirus Disease 2019 (COVID-19) rages throughout the world, accurate modeling of the
dynamics thereof is essential. However, since the availability and quality of data varies dramatically from region to
region, accurate modeling directly from a global perspective is difficult, if not altogether impossible. Nevertheless, via
local data collected by certain regions, it is possible to develop accurate local prediction tools, which may be coupled
to develop global models.
In this study, we analyze the dynamics of local outbreaks of COVID-19 via a coupled system of ordinary differential
equations (ODEs). Utilizing the large amount of data available from the ebbing outbreak in Hubei, China as a testbed,
we estimate the basic reproductive number, R0 of COVID-19 and predict the total cases, total deaths, and other
features of the Hubei outbreak with a high level of accuracy. Through numerical experiments, we observe the effects
of quarantine, social distancing, and COVID-19 testing on the dynamics of the outbreak. Using knowledge gleaned
from the Hubei outbreak, we apply our model to analyze the dynamics of outbreak in Turkey. We provide forecasts
for the peak of the outbreak and the total number of cases/deaths in Turkey, for varying levels of social distancing,
quarantine, and COVID-19 testing
Açıklama
Anahtar Kelimeler
Quarantine, Social Distancing, COVID-19 Testing, Novel Coronavirus (COVID-19), Reproductive Number, Forecasting, Ordinary Differential Equations
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Aslan, İ. H., Demir, M., Wise, M. M., Lenhart, S. (2020). Forecasting and analyzing the dynamics of the outbreak in Hubei and Turkey. COVİD-19 Modelleme Çalıştayı, 22 Haziran 2020. https://doi.org/10.1101/2020.04.11.20061952
