Browsing by Author "Ahmetolan, Semra"

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Citation Count: 0
2009 A (H1N1) ve COVID-19 Pandemilerinde Nüfus Yoğunluğunun ve Temas Oranının Rolü
(2024) Bilge, Ayşe Hümeyra; Ahmetolan, Semra; Bilge, Ayşe Hümeyra; Demirci, Ali; Kaya, Burak Erkan
Sağlıklı-Virus bulaşmış-Bulaşıcılığı olmayan (SIR) salgın modelinin başlıca özellikleri, temel üreme sayısı olarak bilinen 𝑅0 parametresi tarafından belirlenir. Bu çalışmada, çeşitli Avrupa ülkeleri ve İstanbul'daki 2009 A(H1N1) pandemisi ile Almanya'nın federal eyaletlerindeki Covid-19 pandemisi olmak üzere iki farklı salgın için, 𝑅0'ın temas oranlarına olan bağımlılığı araştırılmıştır. 2009 A(H1N1) pandemisine ait veriler, Hollanda da dahil olmak üzere yedi Avrupa ülkesi ve İstanbul için ele alınmış olup, bu ülkeler için temel üreme sayısının nüfus yoğunluğuna orantılı olduğu gösterilmiştir. Yüksek nüfus yoğunluklarına sahip olmaları nedeniyle Hollanda ve İstanbul’a ait 𝑅0 değerlerinin, literatürde kabul edilen aralıkların oldukça dışında kaldığı gözlemlenmiştir. Covid-19 pandemisi için 2020 yılının Şubat ve Haziran ayları arasındaki döneme ait Almanya federal eyaletlerinin verileri kullanılarak, toplumdaki heterojenliklerin nüfus yoğunluğunun etkilerini domine ettiği gösterilmiştir. Bu durum, sokağa çıkma yasağı ve seyahat kısıtlamaları gibi uygulamaların ev içi dinamiklerinin rolünü arttırması olasılığı ile açıklanmıştır.
Citation Count: 1
On the Time Shift Phenomena in Epidemic Models
(Frontiers Media Sa, 2020) Bilge, Ayşe Hümeyra; Demirci, Ali; Bilge, Ayşe Hümeyra; Ahmetolan, Semra
In the standard Susceptible-Infected-Removed (SIR) and Susceptible-Exposed-Infected-Removed (SEIR) models, the peak of infected individuals coincides with the inflection point of removed individuals. Nevertheless, a survey based on the data of the 2009 H1N1 epidemic in Istanbul, Turkey displayed a time shift between the hospital referrals and fatalities. An analysis of recent COVID-19 data and the records for Spanish flu (1918-1919) and SARS (2002-2004) epidemics confirm this observation. We use multistage SIR and SEIR models to provide an explanation for this time shift. Numerical solutions of these models present strong evidence that the delay between the peak of R' (t) and the peak of J(t) = Sigma I-i(i)(t) is approximately half of the infectious period of the epidemic disease. In addition, we use a quadratic approximation to show that the distance between successive peaks of I-i is 1/gamma(i) , where 1/gamma(i) is the infectious period of the ith infectious stage, and we present numerical calculations that confirm this approximation.
Citation Count: 1
A Susceptible-Infectious (SI) model with two infective stages and an endemic equilibrium
(Elsevier, 2022) Bilge, Ayşe Hümeyra; Demirci, Ali; Bilge, Ayse Humeyra; Dobie, Ayse Peker
The focus of this article is on the dynamics of a susceptible-infected model which consists of a susceptible group (S) and two different infectious groups (I-1 and I-2). Once infected, an individual becomes a member of one of these infectious groups which have different clinical forms of infection. In addition, during the progress of the illness, an infected individual in group I-1 may pass to the infectious group I-2 which has a higher mortality rate. The infection is deadly and it has no cure. In this study, positiveness of the solutions for the model is proved. Stability analysis of species extinction, I-1-free equilibrium and endemic equilibrium as well as disease-free equilibrium is studied, and it is shown that the disease-free equilibrium is stable whereas all other equilibrium points are asymptotically stable for parameter ranges determined by certain inequalities. In addition, relations between the basic reproduction number of the disease and the basic reproduction number of each infectious stage are examined. Furthermore, the case where all newborns from infected mothers are also infected is analysed. For this type of vertical transmission, endemic equilibrium is asymptotically stable for certain parameter ranges. Finally, a special case which refers to the disease without vital dynamics is investigated and its exact solution is obtained. (c) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
Citation Count: 13
What Can We Estimate From Fatality and Infectious Case Data Using the Susceptible-Infected-Removed (SIR) Model? A Case Study of Covid-19 Pandemic
(Frontıers Medıa Sa, 2020) Bilge, Ayşe Hümeyra; Bilge, Ayşe Hümeyra; Demirci, Ali; Peker-Dobie, Ayşe; Ergönül, Önder
The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its spread. Since the earliest stages of this major pandemic, academics have done a huge amount of research in order to understand the disease, develop medication, vaccines and tests, and model its spread. Among these studies, a great deal of effort has been invested in the estimation of epidemic parameters in the early stage, for the countries affected by Covid-19, hence to predict the course of the epidemic but the variability of the controls over the course of the epidemic complicated the modeling processes. In this article, the determination of the basic reproduction number, the mean duration of the infectious period, the estimation of the timing of the peak of the epidemic wave is discussed using early phase data. Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020-April 18, 2020 are evaluated using the Susceptible-Infected-Removed (SIR) model. For each country, the SIR models fitting cumulative infective case data within 5% error are analyzed. It is observed that the basic reproduction number and the mean duration of the infectious period can be estimated only in cases where the spread of the epidemic is over (for China and South Korea in the present case). Nevertheless, it is shown that the timing of the maximum and timings of the inflection points of the proportion of infected individuals can be robustly estimated from the normalized data. The validation of the estimates by comparing the predictions with actual data has shown that the predictions were realized for all countries except USA, as long as lock-down measures were retained.