scholarly journals Simulation of the Progression of the COVID-19 Disease in Northwest Syria Using Basic and Adjusted SIR Model

2021 ◽  
Author(s):  
Orwa Al Abdulla ◽  
Agneta Kallström ◽  
Jussi Kauhanen ◽  
Camilo Valderrama
Keyword(s):  
Disease Progression ◽  
Armed Conflict ◽  
Reproduction Number ◽  
Preventive Measure ◽  
Sir Model ◽  
Expected Number ◽  
One Year ◽  
The Impact ◽  
Governmental Control ◽  
Initial Prediction

Abstract Background: Syria has been experienced an armed conflict since 2011. At the time of writing, Northwest Syria is outside governmental control and facing the challenges of the COVID-19 pandemic. In this research, we studied the progression of the COVID-19 pandemic in northwest Syria. We studied the impact of wearing facial masks and discussed the results compared to the existing figures and facts. Methods: Based on available data and using the basic and adjusted SIR model, we estimated the value of the basic reproduction number () which gives an initial prediction of the disease progression. We studied the disease progression for one year (from July 2020 to July 2021) and simulated using the basic and adjusted SIR models. Results: We estimated that the for 2019-nCOV was 2.38, and the resulted figures were overestimated compared to the reported numbers and data concerning the COVID-19 pandemic. However, when adjusting the model by a preventive measure (in this case, wearing face masks), the results were significantly less and closer to the actual reported numbers. Conclusions: Hospital utilization throughout 365 days was projected depending on the basic and adjusted SIR model. The pandemic's peak in the studied area was predicted to arise in December 2020. The expected number of cases to be infected and admitted to hospitals and ICU in 365 days was 633636, 1901, and between 1141 and 2090, accordingly.

scholarly journals Analysis and Prediction of COVID-19 Characteristics Using a Birth-and-Death Model

2020 ◽  
Author(s):  
Narayanan C. Viswanath
Keyword(s):  
Mathematical Modeling ◽  
Infectious Diseases ◽  
Explicit Expression ◽  
Basic Reproduction Number ◽  
Stationary Point ◽  
Reproduction Number ◽  
Sir Model ◽  
Expected Number ◽  
Infection Period ◽  
The Basic Reproduction Number

AbstractIts spreading speed together with the risk of fatality might be the main characteristic that separates COVID-19 from other infectious diseases in our recent history. In this scenario, mathematical modeling for predicting the spread of the disease could have great value in containing the disease. Several very recent papers have contributed to this purpose. In this study we propose a birth-and-death model for predicting the number of COVID-19 active cases. It relation to the Susceptible-Infected-Recovered (SIR) model has been discussed. An explicit expression for the expected number of active cases helps us to identify a stationary point on the infection curve, where the infection ceases increasing. Parameters of the model are estimated by fitting the expressions for active and total reported cases simultaneously. We analyzed the movement of the stationary point and the basic reproduction number during the infection period up to the 20th of April 2020. These provide information about the disease progression path and therefore could be really useful in designing containment strategies.

A hypothesis for the 2007 dengue outbreak in Singapore

2009 ◽  
Vol 138 (7) ◽  
pp. 951-957 ◽  
Author(s):  
E. MASSAD ◽  
F. A. B. COUTINHO ◽  
S. MA ◽  
M. N. BURATTINI
Keyword(s):  
Mathematical Model ◽  
Mortality Rate ◽  
Carrying Capacity ◽  
Reproduction Number ◽  
Control Strategies ◽  
Expected Number ◽  
Alternative Control ◽  
Dengue Outbreak ◽  
Mosquito Mortality ◽  
The Impact

SUMMARYA previous mathematical model explaining dengue in Singapore predicted a reasonable outbreak of about 6500 cases for 2006 and a very mild outbreak with about 2000 cases for 2007. However, only 3051 cases were reported in 2006 while more than 7800 were reported in the first 44 weeks of 2007. We hypothesized that the combination of haze with other local sources of particulate matter had a significant impact on mosquito life expectancy, significantly increasing their mortality rate. To test the hypothesis a mathematical model based on the reproduction number of dengue fever and aimed at comparing the impact of several possible alternative control strategies was proposed. This model also aimed at contributing to the understanding of the causes of dengue resurgence in Singapore in the last decade. The model's simulation demonstrated that an increase in mosquito mortality in 2006 and either a reduction in mortality or an increase in the carrying capacity of mosquitoes in 2007 explained the patterned observed in Singapore. Based on the model's simulation we concluded that the fewer than expected number of dengue cases in Singapore in 2006 was caused by an increase in mosquito mortality due to the disproportionate haze affecting the country that year and that particularly favourable environmental conditions in 2007 propitiated mosquitoes with a lower mortality rate, which explains the greater than expected number of dengue cases in 2007. Whether our hypothesis is plausible or not should be debated further.

Study of the impact of cytomegalovirus-encephalopathy on survival of brain cancer patients undergoing treatment with radio(chemo)therapy.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 2036-2036
Author(s):  
Nicole Lydia Goerig ◽  
Benjamin Frey ◽  
Klaus Korn ◽  
Bernhard Fleckenstein ◽  
Klaus M Ueberla ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Disease Progression ◽  
Cancer Patients ◽  
Brain Cancer ◽  
Antiviral Treatment ◽  
High Grade ◽  
Increased Risk ◽  
One Year ◽  
The Impact ◽  
The Brain

2036 Background: As recently demonstrated (Neurooncology, 2016), neurological decline of patients with brain cancer (high grade glioma, brain metastases) during radio(chemo)therapy (RCT) of the brain is oftentimes caused by CMV-encephalopathy but not disease progression or therapeutic complications. We examined the impact of clinical and serological CMV-status on the survival one year after the onset of radio(chemo)therapy of the brain. Methods: 118 patients requiring whole-brain radiotherapy for brain metastases (n = 55) or local RCT of the brain for high-grade gliomas (n = 63) were observed in the prospective GLIO-CMV-01 study. MRIs and blood samples were obtained before, halfway through, and at the end of radiotherapy. MRIs were screened for disease progression or increased intracranial pressure. Blood was tested for anti-CMV immunoglobulin (Ig)M, anti-CMV IgG, and CMV DNA. Results: 68 of 118 (58%) patients were positive for anti-CMV IgG before radio(chemo)therapy. 28 of those 68 (41%) developed CMV-viremia during or up to 28 days after the end of irradiation. 21 of those 28 (75%) required treatment for symptomatic CMV-associated encephalopathy. One year after the start of RCT, survival was 72% (34/47) (no encephalopathy, anti-CMV-IgG+) or 68% (34/50) (no encephalopathy, anti-CMV-IgG-) versus 38% (8/21) (encephalopathy) (p = 0.0034). Conclusions: Symptomatic CMV-encephalopathy all but doubles the mortality of brain cancer patients within one year of RCT, despite antiviral treatment with ganciclovir. These findings heavily underline the importance to identify patients with increased risk profile for developing CMV-encephalopathy before initiating RCT.

scholarly journals How Many Can You Infect? Simple (and Naive) Methods of Estimating the Reproduction Number

2020 ◽  
Vol 3 (1) ◽  
pp. 28-36
Author(s):  
H. Susanto ◽  
V.R. Tjahjono ◽  
A. Hasan ◽  
M.F. Kasim ◽  
N. Nuraini ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Sir Model ◽  
Epidemic Outbreak ◽  
Numerical Approximations ◽  
Expected Number ◽  
Slowing Down ◽  
Policy Responses ◽  
Current State

This is a pedagogical paper on estimating the number of people that can be infected by one infectious person during an epidemic outbreak, known as the reproduction number. Knowing the number is crucial for developing policy responses. There are generally two types of such a number, i.e., basic and effective (or instantaneous). While basic reproduction number is the average expected number of cases directly generated by one case in a population where all individuals are susceptible, effective reproduction number is the number of cases generated in the current state of a population. In this paper, we exploit the deterministic susceptibleinfected-removed (SIR) model to estimate them through three different numerical approximations. We apply the methods to the pandemic COVID-19 in Italy to provide insights into the spread of the disease in the country. We see that the effect of the national lockdown in slowing down the disease exponential growth appearedabout two weeks after the implementation date. We also discuss available improvements to the simple (and naive) methods that have been made by researchers in the field. Authors of this paper are members of the SimcovID (Simulasi dan Pemodelan COVID-19 Indonesia) collaboration.

Emic Perspectives on the Impact of Armed Conflict on Children's Mental Health in Northern Sri Lanka

2012 ◽  
Author(s):  
Wietse Tol ◽  
Fiona Thomas ◽  
Anavarathan Vallipuram ◽  
Sambasivamoorthy Sivayokan ◽  
Mark Jordans ◽  
...  
Keyword(s):  
Mental Health ◽  
Sri Lanka ◽  
Armed Conflict ◽  
Children’S Mental Health ◽  
Children's Mental Health ◽  
The Impact

A Perspective On The Impact of COVID-19 Pandemic in Basic Science Research and its Future implications

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Yam Nath Paudel ◽  
Efthalia Angelopoulou ◽  
Bhupendra Raj Giri ◽  
Christina Piperi ◽  
Iekhsan Othman ◽  
...  
Keyword(s):  
Basic Science ◽  
Large Scale ◽  
Preventive Measure ◽  
Science Research ◽  
Research Institutes ◽  
Basic Science Research ◽  
Long Term Consequences ◽  
Long Term Impact ◽  
The Impact

: COVID-19 has emerged as a devastating pandemic of the century that the current generations have ever experienced. The COVID-19 pandemic has infected more than 12 million people around the globe and 0.5 million people have succumbed to death. Due to the lack of effective vaccines against the COVID-19, several nations throughout the globe has imposed a lock-down as a preventive measure to lower the spread of COVID-19 infection. As a result of lock-down most of the universities and research institutes has witnessed a long pause in basic science research ever. Much has been talked about the long-term impact of COVID-19 in economy, tourism, public health, small and large-scale business of several kind. However, the long-term implication of these research lab shutdown and its impact in the basic science research has not been much focused. Herein, we provide a perspective that portrays a common problem of all the basic science researchers throughout the globe and its long-term consequences.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

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