arXiv subjects

Onder Ergonul

Publications and source records attributed to Onder Ergonul.

3 recordsLinked to original sources

arXiv2021

Molecular Communication Theoretical Modeling and Analysis of SARS-CoV2 Transmission in Human Respiratory System

Severe Acute Respiratory Syndrome-CoronaVirus 2 (SARS-CoV2) caused the ongoing pandemic. This pandemic devastated the world by killing more than a million people, as of October 2020. It is imperative to understand the transmission dynamics of SARS-CoV2 so that novel and interdisciplinary prevention, diagnostic, and therapeutic techniques could be developed. In this work, we model and analyze the transmission of SARS-CoV2 through the human respiratory tract from a molecular communication perspective. We consider that virus diffusion occurs in the mucus layer so that the shape of the tract does not have a significant effect on the transmission. Hence, this model reduces the inherent complexity of the human respiratory system. We further provide the impulse response of SARS-CoV2-ACE2 receptor binding event to determine the proportion of the virus population reaching different regions of the respiratory tract. Our findings confirm the results in the experimental literature on higher mucus flow rate causing virus migration to the lower respiratory tract. These results are especially important to understand the effect of SARS-CoV2 on the different human populations at different ages who have different mucus flow rates and ACE2 receptor concentrations in the different regions of the respiratory tract.

physics.bio-ph↗

arXiv2020

What Can We Estimate from Fatality and Infectious Case Data using the Susceptible-Infected-Removed (SIR) model? A case Study of Covid-19 Pandemic

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 ten countries 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 analysed. 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 realised for all countries except USA, as long as lock-down measures were retained.

q-bio.PE↗

arXiv2012

A Susceptible-Exposed-Infected-Removed (Seir) Model For The 2009-2010 A/H1N1 Epidemic In Istanbul

A/H1N1 epidemic data from Istanbul, Turkey during the period June 2009-February 2010 is analyzed with SEIR (Susceptible-Exposed-Infected-Removed) model. The data consist of the daily adult hospitalization numbers and fatalities recorded in various state hospitals serving an adult population of about 1.5-2 million. June 2009-August 2009 period corresponds to the initial stage of the epidemic where the hospitalization rate is nearly %100 and it is excluded from further consideration. The analysis covers the September 2009-February 2010 period, the total number of hospitalizations and fatalities being respectively 869 and 46. It is shown that the maximum correlation between the number of fatalities and hospitalizations occur with a time shift of 9 days and the proportionality constant is δ=0.0537. The SEIR epidemic model is applied to the data by back-shifting the number of fatalities. The determination of the best fitting model is based on the L2 norms of errors between the model and the data and the errors are around %10 and %2.6 for the number of hospitalizations and fatalities, respectively. The parameters in the model are I0, η, ε and β, where I0 is the percentage of people infected initially, η and ε are related to the inverses of the infection and incubation periods and β/η is the representative of the basic reproduction number. These parameters are determined as η=0.09 (1/η =11.11days), I0=10^-7.4, ε=0.32 (1/ε =3.125 days), β=0.585, β/η=6.5.

q-bio.QM↗