scholarly journals The Acceleration Index as a Test-Controlled Reproduction Number: Application to COVID-19 in France

2020 ◽  
Author(s):  
Christelle Baunez ◽  
Mickael Degoulet ◽  
Stephane Luchini ◽  
Patrick Pintus ◽  
Matteo Louis Pintus ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Controlled Reproduction

scholarly journals Estimation of the Time-Varying Reproduction Number of COVID-19 Outbreak in China

2020 ◽  
Author(s):  
Chong You ◽  
Yuhao Deng ◽  
Wenjie Hu ◽  
Jiarui Sun ◽  
Qiushi Lin ◽  
...  
Keyword(s):  
Standard Deviation ◽  
World Wide ◽  
Reproduction Number ◽  
Infectious Period ◽  
Time Varying ◽  
Exponential Growth Rate ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Controlled Reproduction ◽  
Novel Coronavirus

BackgroundThe 2019-nCoV outbreak in Wuhan, China has attracted world-wide attention. As of February 11, 2020, a total of 44730 cases of novel coronavirus-infected pneumonia associated with COVID-19 were confirmed by the National Health Commission of China.MethodsThree approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers.ResultsA total of 71 chains of transmission together with dates of symptoms onset and 67 dates of infections were identified among 5405 confirmed cases outside Hubei as reported by February 2, 2020. Based on this information, we find the serial interval having an average of 4.41 days with a standard deviation of 3.17 days and the infectious period having an average of 10.91 days with a standard deviation of 3.95 days.ConclusionsThe controlled reproduction number is declining. It is lower than one in most regions of China, but is still larger than one in Hubei Province. Sustained efforts are needed to further reduce the Rc to below one in order to end the current epidemic.

scholarly journals Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study

2020 ◽  
Author(s):  
Jiawen Hou ◽  
Jie Hong ◽  
Boyun Ji ◽  
Bowen Dong ◽  
Yue Chen ◽  
...  
Keyword(s):  
Mathematical Modelling ◽  
Reproduction Number ◽  
Mainland China ◽  
Hubei Province ◽  
Transmission Dynamics ◽  
Population Movement ◽  
Long Distance ◽  
Spring Festival ◽  
Travel Restrictions ◽  
Controlled Reproduction

AbstractBackgroundThe first case of COVID-19 atypical pneumonia was reported in Wuhan, China on December 1, 2019. Since then, at least 33 other countries have been affected and there is a possibility of a global outbreak. A tremendous amount of effort has been made to understand its transmission dynamics; however, the temporal and spatial transmission heterogeneity and changing epidemiology have been mostly ignored. The epidemic mechanism of COVID-19 remains largely unclear.MethodsEpidemiological data on COVID-19 in China and daily population movement data from Wuhan to other cities were obtained and analyzed. To describe the transmission dynamics of COVID-19 at different spatio-temporal scales, we used a three-stage continuous-time Susceptible-Exposed-Infectious-Recovered (SEIR) meta-population model based on the characteristics and transmission dynamics of each stage: 1) local epidemic from December 1, 2019 to January 9, 2020; 2) long-distance spread due to the Spring Festival travel rush from January 10 to 22, 2020; and 3) intra-provincial transmission from January 23, 2020 when travel restrictions were imposed. Together with the basic reproduction number (R0) for mathematical modelling, we also considered the variation in infectivity and introduced the controlled reproduction number (Rc) by assuming that exposed individuals to be infectious; we then simulated the future spread of COVID across Wuhan and all the provinces in mainland China. In addition, we built a novel source tracing algorithm to infer the initial exposed number of individuals in Wuhan on January 10, 2020, to estimate the number of infections early during this epidemic.FindingsThe spatial patterns of disease spread were heterogeneous. The estimated controlled reproduction number (Rc) in the neighboring provinces of Hubei province were relatively large, and the nationwide reproduction number ‐ except for Hubei ‐ ranged from 0.98 to 2.74 with an average of 1.79 (95% CI 1.77‐1.80). Infectivity was significantly greater for exposed than infectious individuals, and exposed individuals were predicted to have become the major source of infection after January 23. For the epidemic process, most provinces reached their epidemic peak before February 10, 2020. It is expected that the maximum number of infections will be approached by the end of March. The final infectious size is estimated to be about 58,000 for Wuhan, 20,800 for the rest of Hubei province, and 17,000 for the other provinces in mainland China. Moreover, the estimated number of the exposed individuals is much greater than the officially reported number of infectious individuals in Wuhan on January 10, 2020.InterpretationThe transmission dynamics of COVID-19 have been changing over time and were heterogeneous across regions. There was a substantial underestimation of the number of exposed individuals in Wuhan early in the epidemic, and the Spring Festival travel rush played an important role in enhancing and accelerating the spread of COVID-19. However, China’s unprecedented large-scale travel restrictions quickly reduced Rc. The next challenge for the control of COVID-19 will be the second great population movement brought by removing these travel restrictions.

scholarly journals The Acceleration Index as a Test-Controlled Reproduction Number: Application to COVID-19 in France*

2020 ◽  
Author(s):  
Christelle Baunez ◽  
Mickael Degoulet ◽  
Stéphane Luchini ◽  
Matteo L. Pintus ◽  
Patrick A. Pintus ◽  
...  
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Jel Classification ◽  
Time Varying ◽  
Infectious Disease Outbreak ◽  
Sufficient Statistic ◽  
Viral Spread ◽  
Acceleration And Deceleration ◽  
Controlled Reproduction ◽  
Accurate Indicator

AbstractWe show that the acceleration index, a novel indicator that measures acceleration and deceleration of viral spread (Baunez et al. 2020a,b), is essentially a test-controlled version of the reproduction number. As such it is a more accurate indicator to track the dynamics of an infectious disease outbreak in real time. We indicate a discrepancy between the acceleration index and the reproduction number, based on the infectivity and test rates and we provide a formal decomposition of this difference. When applied to French data for the ongoing COVID-19 pandemic, our decomposition shows that the reproduction number consistenly underestimates the resurgence of the pandemic since the summer of 2020, compared to the acceleration index which accounts for the time-varying volume of tests. From the comparison that we present here follows that the acceleration index is a sufficient statistic to track the pandemic’s propagation, as it captures in real time the sizeable time variation featured by viral circulation.JEL Classification NumbersI18; H12

NUMERICAL AND STABILITY ANALYSIS OF THE TRANSMISSION DYNAMICS OF SVIR EPIDEMIC MODEL WITH STANDARD INCIDENCE RATE

2019 ◽  
Vol 4 (2) ◽  
pp. 349 ◽  
Author(s):  
Oluwatayo Michael Ogunmiloro ◽  
Fatima Ohunene Abedo ◽  
Hammed Kareem
Keyword(s):  
Reproduction Number ◽  
Disease Spread ◽  
Asymptotically Stable ◽  
Equilibrium Solutions ◽  
Transform Method ◽  
Globally Asymptotically Stable ◽  
Differential Transform ◽  
Mathematical Techniques ◽  
Fourth Order Method ◽  
Theoretical Results

In this article, a Susceptible – Vaccinated – Infected – Recovered (SVIR) model is formulated and analysed using comprehensive mathematical techniques. The vaccination class is primarily considered as means of controlling the disease spread. The basic reproduction number (Ro) of the model is obtained, where it was shown that if Ro<1, at the model equilibrium solutions when infection is present and absent, the infection- free equilibrium is both locally and globally asymptotically stable. Also, if Ro>1, the endemic equilibrium solution is locally asymptotically stable. Furthermore, the analytical solution of the model was carried out using the Differential Transform Method (DTM) and Runge - Kutta fourth-order method. Numerical simulations were carried out to validate the theoretical results. 

Domestizierung im Vergleich

2016 ◽  
Vol 7 (2) ◽  
pp. 93-110 ◽  
Author(s):  
Erhard Schüttpelz
Keyword(s):  
Hunter Gatherers ◽  
Controlled Reproduction

"Domestizierung lässt sich durch einen Nukleus aus drei technischen Tätigkeiten definieren: durch die gesteuerte Reproduktion, die eigens eingerichtete Ernährung und den Schutz von Tieren und Pflanzen vor Schädigungen. Wenn man diese Definition an einen Vergleich von Kulturen und Kollektiven anlegt, stellen sich zwei Überraschungen ein: Außerhalb jeder Domestizierung entwickeln Wildbeuter eine rituelle Domestizierung oder ein mythologisches Verständnis, ihre Welt sei bereits domestiziert. Und in der Moderne tritt an die Seite der technischen Domestizierung ihre mögliche Naturalisierung. Der Aufsatz zieht einige Konsequenzen aus diesem typologischen Vergleich. Domestication can be defined by a nucleus of three technical activities: controlled reproduction and nutrition as well as protection of animals and plants from damage. If one applies this definition to a comparison of cultures and collectives, two surprises arise: Without being in touch of any kind of domestication, hunter-gatherers develop a ritual domestication or a mythological understanding that their world already is domesticated. And in modernity, possible naturalization arises at the side of technical domestication. The paper draws some conclusions from this typological comparison. "

An Updated Review on COVID-19

2020 ◽  
Vol 20 ◽  
Author(s):  
Mahmoud Ahmed Ebada ◽  
Ahmed Wadaa Allah ◽  
Eshak Bahbah ◽  
Ahmed Negida
Keyword(s):  
Screening Tool ◽  
Distress Syndrome ◽  
Reproduction Number ◽  
Case Fatality ◽  
Current Data ◽  
Future Research ◽  
Rt Pcr ◽  
Viral Structure ◽  
Discharge Criteria ◽  
Serology Testing

: Coronavirus Disease (COVID-19) pandemic has affected more than seven million individuals in 213 countries worldwide with a basic reproduction number ranging from 1.5 to 3.5 and an estimated case fatality rate ranging from 2% to 7%. A substantial proportion of COVID-19 patients are asymptomatic; however, symptomatic cases might present with fever, cough, and dyspnoea or severe symptoms up to acute respiratory distress syndrome. Currently, RNA RT-PCR is the screening tool, while bilateral chest CT is the confirmatory clinical diagnostic test. Several drugs have been repurposed to treat COVID-19, including chloroquine or hydroxychloroquine with or without azithromycin, lopinavir/ritonavir combination, remdesivir, favipiravir, tocilizumab, and EIDD-1931. Recently, Remdesivir gained FDA emergency approval based on promising early findings from the interim analysis of 1063 patients. The recently developed serology testing for SARSCoV-2 antibodies opened the door to evaluate the actual burden of the disease and to determine the rate of the population who have been previously infected (or developed immunity). This review article summarizes current data on the COVID-19 pandemic starting from the early outbreak, viral structure and origin, pathogenesis, diagnosis, treatment, discharge criteria, and future research.

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.

Stability Analysis of an SEIR Epidemic Model with Stochastic Perturbation and Numerical Simulation

2013 ◽  
Vol 14 (2) ◽  
Author(s):  
Xiaoming Fan ◽  
Zhigang Wang
Keyword(s):  
Numerical Simulation ◽  
Asymptotic Behavior ◽  
Epidemic Model ◽  
Reproduction Number ◽  
Stochastic Perturbation ◽  
Random Fluctuation ◽  
Deterministic System ◽  
Stochastic Version ◽  
Special Case ◽  
The Basic Reproduction Number

AbstractAn SEIR epidemic model with constant immigration and random fluctuation around the endemic equilibrium is considered. As a special case, a deterministic system discussed by Li et al. will be incorporated into the stochastic version given by us. We carry out a detailed analysis on the asymptotic behavior of the stochastic model, also regarding of the basic reproduction number ℛ

scholarly journals Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Rozhnova ◽  
Christiaan H. van Dorp ◽  
Patricia Bruijning-Verhagen ◽  
Martin C. J. Bootsma ◽  
Janneke H. H. M. van de Wijgert ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Additional Benefit ◽  
Transmission Model ◽  
Time Points ◽  
School Based ◽  
Admission Data ◽  
Age Structured ◽  
The Impact ◽  
Pandemic Wave

AbstractThe role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We use an age-structured transmission model fitted to age-specific seroprevalence and hospital admission data to assess the effects of school-based measures at different time points during the COVID-19 pandemic in the Netherlands. Our analyses suggest that the impact of measures reducing school-based contacts depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce the effective reproduction number (Re) with non-school-based measures are exhausted or undesired and Re is still close to 1, the additional benefit of school-based measures may be considerable, particularly among older school children. As two examples, we demonstrate that keeping schools closed after the summer holidays in 2020, in the absence of other measures, would not have prevented the second pandemic wave in autumn 2020 but closing schools in November 2020 could have reduced Re below 1, with unchanged non-school-based contacts.

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