scholarly journals Estimating the Serial Interval of the Novel Coronavirus Disease (COVID-19): A Statistical Analysis Using the Public Data in Hong Kong From January 16 to February 15, 2020

2020 ◽  
Vol 8 ◽  
Author(s):  
Shi Zhao ◽  
Daozhou Gao ◽  
Zian Zhuang ◽  
Marc K. C. Chong ◽  
Yongli Cai ◽  
...  
Keyword(s):  
Hong Kong ◽  
Statistical Analysis ◽  
The Novel ◽  
The Public ◽  
Serial Interval ◽  
Public Data ◽  
Novel Coronavirus

scholarly journals Dynamics based on analysis of public data for spreading of disease

2021 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Planck Equation ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus ◽  
Official Data

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We perform the numerical analysis using the stochastic differential equation in Itô’s calculus (SDE) for the estimating of novel cases daily as well as analytical calculations solving the correspondent Fokker-Planck equation for the density probability distribution of novel cases, P(N(t); t). Our results display that the model based in the Itô diffusion fits well to the results due to uncertain in the official data and to the number of tests realized in the populations of each country.

scholarly journals Estimating the serial interval of the novel coronavirus disease (COVID-19): A statistical analysis using the public data in Hong Kong from January 16 to February 15, 2020

2020 ◽  
Author(s):  
Shi Zhao ◽  
Daozhou Gao ◽  
Zian Zhuang ◽  
Marc KC Chong ◽  
Yongli Cai ◽  
...  
Keyword(s):  
Hong Kong ◽  
Contact Tracing ◽  
Distributed Model ◽  
Serial Interval ◽  
Public Data ◽  
Interval Censored ◽  
Large Outbreak ◽  
Emerging Virus ◽  
Novel Coronavirus ◽  
Censored Likelihood

AbstractBackgroundsThe emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of novel coronavirus disease (COVID-19) in Wuhan, China since December 2019. Based on the publicly available surveillance data, we identified 21 transmission chains in Hong Kong and estimated the serial interval (SI) of COVID-19.MethodsIndex cases were identified and reported after symptoms onset, and contact tracing was conducted to collect the data of the associated secondary cases. An interval censored likelihood framework is adopted to fit a Gamma distribution function to govern the SI of COVID-19.FindingsAssuming a Gamma distributed model, we estimated the mean of SI at 4.4 days (95%CI: 2.9−6.7) and SD of SI at 3.0 days (95%CI: 1.8−5.8) by using the information of all 21 transmission chains in Hong Kong.ConclusionThe SI of COVID-19 may be shorter than the preliminary estimates in previous works. Given the likelihood that SI could be shorter than the incubation period, pre-symptomatic transmission may occur, and extra efforts on timely contact tracing and quarantine are recommended in combating the COVID-19 outbreak.

scholarly journals Dynamics based on analysis of public data for spreading of disease

2021 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Planck Equation ◽  
Probability Density Distribution ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Itô’s calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker-Planck equation for the probability density distribution of novel cases, P(N(t); t). Our results display that the model based in the Itô’s diffusion fits well to the results due to uncertainty in the official data and to the number of testsrealized in populations of each country.

scholarly journals A Mathematical Model for the COVID-19 Outbreak and Its Applications

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 990
Author(s):  
Roman Cherniha ◽  
Vasyl’ Davydovych
Keyword(s):  
Mathematical Model ◽  
Exact Solutions ◽  
Quantitative Description ◽  
Measured Data ◽  
Nonlinear Ordinary Differential Equations ◽  
The Novel ◽  
The Public ◽  
Public Data ◽  
Novel Coronavirus ◽  
Good Agreement

A mathematical model based on nonlinear ordinary differential equations is proposed for quantitative description of the outbreak of the novel coronavirus pandemic. The model possesses remarkable properties, such as as full integrability. The comparison with the public data shows that exact solutions of the model (with the correctly specified parameters) lead to the results, which are in good agreement with the measured data in China and Austria. Prediction of the total number of the COVID-19 cases is discussed and examples are presented using the measured data in Austria, France, and Poland. Some generalizations of the model are suggested as well.

scholarly journals Dynamics based on analysis of public data for spreading of disease

2020 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Public Health ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus ◽  
Official Data

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We performed the numerical analysis using the stochastic differential equation for estimating of the novel cases diary as well as analytical calculations solving the correspondent partial equation for the distribution of novel cases P. Our results display that the model based in the Itô diffusion fits well to the results diary due to uncertain in the official data and to the number of tests realized in the populations of each country.

scholarly journals Dynamics based on analysis of public data for spreading of disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Planck Equation ◽  
Probability Density Distribution ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus

AbstractThe stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Itô’s calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker–Planck equation for the probability density distribution of novel cases, P(N(t), t). Our results display that the model based in the Itô’s diffusion fits well to the results due to uncertainty in the official data and to the number of tests realized in populations of each country.

Coronavirus: Towards controlling of the pandemic - Indian scenario

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 462-468
Author(s):  
Latika kothari ◽  
Sanskruti Wadatkar ◽  
Roshni Taori ◽  
Pavan Bajaj ◽  
Diksha Agrawal
Keyword(s):  
Control Measures ◽  
The Novel ◽  
Medical Treatments ◽  
Health Crisis ◽  
The Public ◽  
Infection Control Measures ◽  
The Social ◽  
Asking Questions ◽  
The Government ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) is a communicable infection caused by the novel coronavirus resulting in severe acute respiratory syndrome coronavirus 2 (SARS-CoV). It was recognized to be a health crisis for the general population of international concern on 30th January 2020 and conceded as a pandemic on 11th March 2020. India is taking various measures to fight this invisible enemy by adopting different strategies and policies. To stop the COVID-19 from spreading, the Home Affairs Ministry and the health ministry, of India, has issued the nCoV 19 guidelines on travel. Screening for COVID-19 by asking questions about any symptoms, recent travel history, and exposure. India has been trying to get testing kits available. The government of India has enforced various laws like the social distancing, Janata curfew, strict lockdowns, screening door to door to control the spread of novel coronavirus. In this pandemic, innovative medical treatments are being explored, and a proper vaccine is being hunted to deal with the situation. Infection control measures are necessary to prevent the virus from further spreading and to help control the current situation. Thus, this review illustrates and explains the criteria provided by the government of India to the awareness of the public to prevent the spread of COVID-19.

High cytokine levels and cytokine storm in the novel coronavirus infection

2021 ◽  
pp. 38-47
Author(s):  
Maksim Leonidovich Maksimov ◽  
Albina Ayratovna Zvegintseva ◽  
Lyudmila Yurievna Kulagina ◽  
Albina Zainutdinovna Nigmedzyanova ◽  
Elvina Ramisovna Kadyseva
Keyword(s):  
Peripheral Blood ◽  
High Frequency ◽  
The Novel ◽  
Cytokine Storm ◽  
The Public ◽  
Systemic Inflammatory Reaction ◽  
Scientific World ◽  
Cytokine Levels ◽  
Coronavirus Infection ◽  
Novel Coronavirus

A review article is based on current foreign sources. The level of cytokines in the peripheral blood can be increased in many diseases, but in some cases there may be an excess of their normal concentration in tens, hundreds or more times with the development of a peculiar clinical picture, which is based on a systemic inflammatory reaction. In the literature this condition has received the figurative name «cytokine storm», which highlights an extremely violent reaction of the immune system with an unknown (often unfavorable) outcome. Close attention of the scientific world and the public to the problem of extremely high levels of cytokines in the peripheral blood (hypercytokinemia) was drawn due to the high frequency of the cytokine storm in the novel coronavirus infection.

scholarly journals The Impact of Armed Conflict on the Epidemiological Situation of COVID-19 in Libya, Syria and Yemen

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohamed A. Daw
Keyword(s):  
Armed Conflict ◽  
Early Stage ◽  
Armed Conflicts ◽  
Cumulative Number ◽  
The Novel ◽  
Global Pandemic ◽  
Large Numbers ◽  
Public Data ◽  
Novel Coronavirus ◽  
The Impact

Background: Since the Arab uprising in 2011, Libya, Syria and Yemen have gone through major internal armed conflicts. This resulted in large numbers of deaths, injuries, and population displacements, with collapse of the healthcare systems. Furthermore, the situation was complicated by the emergence of COVID-19 as a global pandemic, which made the populations of these countries struggle under unusual conditions to deal with both the pandemic and the ongoing wars. This study aimed to determine the impact of the armed conflicts on the epidemiology of the novel coronavirus (SARS-CoV-2) within these war-torn countries and highlight the strategies needed to combat the spread of the pandemic and its consequences.Methods: Official and public data concerning the dynamics of the armed conflicts and the spread of SARS-COV-2 in Libya, Syria and Yemen were collected from all available sources, starting from the emergence of COVID-19 in each country until the end of December 2020. Datasets were analyzed by a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the conflict and the prevalence of COVID-19.Results: The data indicated that there was an increase in the intensity of the violence at an early stage from March to August 2020, when it approximately doubled in the three countries, particularly in Libya. During that period, few cases of COVID-19 were reported, ranging from 5 to 53 cases/day. From September to December 2020, a significant decline in the intensity of the armed conflicts was accompanied by steep upsurges in the rate of COVID-19 cases, which reached up to 500 cases/day. The accumulative cases vary from one country to another during the armed conflict. The highest cumulative number of cases were reported in Libya, Syria and Yemen.Conclusions: Our analysis demonstrates that the armed conflict provided an opportunity for SARS-CoV-2 to spread. The early weeks of the pandemic coincided with the most intense period of the armed conflicts, and few cases were officially reported. This indicates undercounting and hidden spread during the early stage of the pandemic. The pandemic then spread dramatically as the armed conflict declined, reaching its greatest spread by December 2020. Full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its consequences.

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