scholarly journals Epidemic potential of COVID-19 in Omsk region and assessment of the anti-epidemic measures

2020 ◽  
Vol 5 (3) ◽  
pp. 8-17
Author(s):  
A. I. Blokh ◽  
N. A. Penievskaya ◽  
N. V. Rudakov ◽  
I. I. Lazarev
Keyword(s):  
Growth Rate ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Case Fatality ◽  
Community Acquired Pneumonia ◽  
Exponential Growth Rate ◽  
Epidemic Size ◽  
Restrictive Measures ◽  
Observation Period

Aim. To study the spread of COVID-19 among the population of the Omsk region during the first 115 days of the epidemic. Materials and Methods. We carried out a descriptive epidemiological study using the data from the Center for Hygiene and Epidemiology in the Omsk Region on the officially registered cases of COVID-19 in the Omsk Region from March 27 to July 19, 2020. The following indicators were calculated: exponential growth rate (r), basic reproduction number (R0), effective reproduction number (Rt), expected natural epidemic size and herd immunity threshold. Results. During the indicated period, there were 5,503 cases of COVID-19 in the Omsk Region. The incidence rate was 285.60/ 0000 (95% CI 278.1 – 293.2), the case fatality rate was 1.5% for completed cases and 0.9^ for all cases. The most active spread of COVID-19 was noted in Omsk and in 5 out of 32 districts of the region (Kalachinskiy, Novovarshavskiy, Russko-Polyanskiy, Moskalenskiy, and Azov German National District). Individuals < 30 years of age were among the least involved in the epidemic process. Among the most affected groups were 55-69 years-old males and 50-64-years-old females. During the observation period, the proportion of asymptomatic forms gradually reduced along with the increase in the proportion of pneumonia cases. A manifold increase in the incidence of community-acquired pneumonia was registered in June and July 2020 compared to the average values in 2017-2019. The exponential growth rate was 6.6% per day, R0 was 1.4-1.5, Rt was 1.18, and herd immunity threshold was 28.6%. The expected size of the epidemic at sustained anti-epidemic measures was 58.0% of the population. Conclusion. The spread of COVID-19 in the Omsk region is not sufficiently suppressed. Reduced number of asymptomatic cases and incomplete detection of COVID-19 among the patients with community-acquired pneumonia may contribute to the latent spread of the infection and complicated epidemic situation. Maintenance of the restrictive measures and acquirement of the herd immunity (over 28.6% population) may significantly reduce the spread of COVID-19 in the Omsk Region.

scholarly journals Epidemic Potential of COVID-19 in Omsk Region during Anti-Epidemic Measures

2020 ◽  
pp. 36-42
Author(s):  
A. I. Blokh ◽  
N. A. Pen’evskaya ◽  
N. V. Rudakov ◽  
I. I. Lazarev ◽  
O. A. Mikhailova ◽  
...  
Keyword(s):  
Growth Rate ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Case Fatality ◽  
Community Acquired Pneumonia ◽  
Cumulative Number ◽  
Exponential Growth Rate ◽  
Epidemic Size ◽  
Threshold Data

Aim. To study the spread of COVID-19 among the population of the Omsk Region during 24 weeks of the epidemic on the background of anti-epidemic measures.Materials and methods. A descriptive epidemiological study was carried out based on publically available data и data from the Center for Hygiene and Epidemiology in the Omsk Region on the official registration and epidemiological investigation of detected COVID-19 cases in the Omsk Region for the period from March 27 to September 10, 2020. To assess the potential of COVID-19 to spread, the following indicators were calculated: exponential growth rate (r), basic reproduction number (R0), effective reproduction number (Rt), expected natural epidemic size and herd immunity threshold. Data processing was performed using MS Excel 2010. The cartogram was built using the QGIS 3.12-Bukuresti application in the EPSG: 3576 coordinate system.Results and discussion. For the period from March 27 to September 10, 2020, a total of 9779 cases of COVID-19 were registered in the Omsk Region, the cumulative incidence was 507,6 per 100000 (95 % CI 497,5÷517,6), the case-fatality rate for completed cases was 2.9 %, for identified cases – 2.4 %. The most active spread of COVID-19 was noted in Omsk and 4 out of 32 districts of the region (Moskalensky, Azov German National, Mariyanovsky, Novovarshavsky). During the ongoing anti-epidemic measures, the exponential growth rate of the cumulative number of COVID-19 cases was 4.5 % per day, R0 – 1.4–1.5, Rt – 1.10, herd immunity threshold – 28.6 %. The expected size of the epidemic in case of sustained anti-epidemic measures can reach 58.0 % of the recovered population. A decrease in the number of detected virus carriers, incomplete detection of COVID-19 among patients with community-acquired pneumonia introduced additional risks for the latent spread of infection and complications of the epidemic situation. Maintaining restrictive  measures and increasing the proportion of the immune population (over 28.6 %) may significantly reduce the risks of increasing the spread of COVID-19 in the Omsk Region. 

scholarly journals Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19) in Africa

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Salihu S. Musa ◽  
Shi Zhao ◽  
Maggie H. Wang ◽  
Abdurrazaq G. Habib ◽  
Umar T. Mustapha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Exponential Growth Rate

scholarly journals Estimation of the basic reproduction number (R0) for the novel coronavirus disease in Sri Lanka

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Samath Dharmaratne ◽  
Supun Sudaraka ◽  
Ishanya Abeyagunawardena ◽  
Kasun Manchanayake ◽  
Mahen Kothalawala ◽  
...  
Keyword(s):  
Growth Rate ◽  
Maximum Likelihood ◽  
Sri Lanka ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Likelihood Method ◽  
Exponential Growth Rate ◽  
Rate Method ◽  
The Basic Reproduction Number

Abstract Background The basic reproduction number (R0) is the number of cases directly caused by an infected individual throughout his infectious period. R0 is used to determine the ability of a disease to spread within a given population. The reproduction number (R) represents the transmissibility of a disease. Objectives We aimed to calculate the R0 of Coronavirus disease-2019 (COVID-19) in Sri Lanka and to describe the variation of R, with its implications to the prevention and control of the disease. Methods Data was obtained from daily situation reports of the Epidemiology Unit, Sri Lanka and a compartmental model was used to calculate the R0 using estimated model parameters. This value was corroborated by using two more methods, the exponential growth rate method and maximum likelihood method to obtain a better estimate for R0. The variation of R was illustrated using a Bayesian statistical inference-based method. Results The R0 calculated by the first model was 1.02 [confidence interval (CI) of 0.75–1.29] with a root mean squared error of 7.72. The exponential growth rate method and the maximum likelihood estimation method yielded an R0 of 0.93 (CI of 0.77–1.10) and a R0 of 1.23 (CI of 0.94–1.57) respectively. The variation of R ranged from 0.69 to 2.20. Conclusion The estimated R0 for COVID-19 in Sri Lanka, calculated by three different methods, falls between 0.93 and 1.23, and the transmissibility R has reduced, indicating that measures implemented have achieved a good control of disease.

scholarly journals Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19) in Africa

2020 ◽  
Author(s):  
Salihu S Musa ◽  
Shi Zhao ◽  
Maggie H Wang ◽  
Abdurrazaq G Habib ◽  
Umar T Mustapha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Initial Phase ◽  
Reproduction Number ◽  
Exponential Growth Rate ◽  
Preparedness Planning ◽  
First Case ◽  
Exponential Growth Model ◽  
The Basic Reproduction Number

Abstract Since the first case of coronavirus disease 2019 (COVID-19) was detected on February 14, 2020, the cumulative confirmations reached 834 including 17 deaths by March 19, 2020. We analyzed the initial phase of the epidemic of COVID-19 in Africa between 1 March and 19 March 2020, by using the simple exponential growth model. We estimated the exponential growth rate as 0.22 per day (95%CI: 0.20 – 0.24), and the basic reproduction number to be 2.37 (95%CI: 2.22-2.51) based on the assumption that the exponential growth starting from 1 March, 2020. Our estimates should be useful in preparedness planning.

scholarly journals Estimating the basic reproduction number for COVID-19 in Western Europe

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248731
Author(s):  
Isabella Locatelli ◽  
Bastien Trächsel ◽  
Valentin Rousson
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Cumulative Incidence ◽  
Western Europe ◽  
Reproduction Number ◽  
European Population ◽  
Exponential Growth Rate ◽  
Official Statistics ◽  
The Basic Reproduction Number

Objective To estimate the basic reproduction number (R0) for COVID-19 in Western Europe. Methods Data (official statistics) on the cumulative incidence of COVID-19 at the start of the outbreak (before any confinement rules were declared) were retrieved in the 15 largest countries in Western Europe, allowing us to estimate the exponential growth rate of the disease. The rate was then combined with estimates of the distribution of the generation interval as reconstructed from the literature. Results Despite the possible unreliability of some official statistics about COVID-19, the spread of the disease appears to be remarkably similar in most European countries, allowing us to estimate an average R0 in Western Europe of 2.2 (95% CI: 1.9–2.6). Conclusions The value of R0 for COVID-19 in Western Europe appears to be significantly lower than that in China. The proportion of immune persons in the European population required to stop the outbreak could thus be closer to 50% than to 70%.

scholarly journals Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19) in Africa

2020 ◽  
Author(s):  
Salihu S Musa ◽  
Shi Zhao ◽  
Maggie H Wang ◽  
Abdurrazaq G Habib ◽  
Umar T Mustapha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Initial Phase ◽  
Reproduction Number ◽  
Initial Growth ◽  
Exponential Growth Rate ◽  
Preparedness Planning ◽  
First Case ◽  
Exponential Growth Model

Abstract Background Since the first case of coronavirus disease 2019 (COVID-19) was detected on February 14, 2020, the cumulative confirmations reached 15207 including 831 deaths by April 13, 2020. Methods We analyzed the initial phase of the epidemic of COVID-19 in Africa between 1 March and 13 April 2020, by using the simple exponential growth model.Results We estimated the exponential growth rate as 0.22 per day (95%CI: 0.20 – 0.24), and the basic reproduction number, R0, to be 2.37 (95%CI: 2.22-2.51) based on the assumption that the exponential growth starting from 1 March 2020.Conclusion The initial growth of COVID-19 cases in Africa was rapid and showed large variations across countries. Our estimates should be useful in preparedness planning. Trial registration: NA

scholarly journals Optimal Strategies for Prudent Investors

1998 ◽  
Vol 01 (04) ◽  
pp. 473-486 ◽  
Author(s):  
Roberto Baviera ◽  
Michele Pasquini ◽  
Maurizio Serva ◽  
Angelo Vulpiani
Keyword(s):  
Growth Rate ◽  
Random Walk ◽  
Exponential Growth ◽  
Optimal Strategies ◽  
Maximum Amount ◽  
Exponential Growth Rate ◽  
One Dimensional ◽  
Economic Level ◽  
Random Walk With Drift ◽  
Analytical Expressions

We consider a stochastic model of investment on an asset in a stock market for a prudent investor. she decides to buy permanent goods with a fraction α of the maximum amount of money owned in her life in order that her economic level never decreases. The optimal strategy is obtained by maximizing the exponential growth rate for a fixed α. We derive analytical expressions for the typical exponential growth rate of the capital and its fluctuations by solving an one-dimensional random walk with drift.

LANGUAGES WITH A FINITE ANTIDICTIONARY: SOME GROWTH QUESTIONS

2014 ◽  
Vol 25 (08) ◽  
pp. 937-953
Author(s):  
ARSENY M. SHUR
Keyword(s):  
Growth Rate ◽  
Structural Properties ◽  
Exponential Growth ◽  
Regular Languages ◽  
The Other ◽  
Exponential Growth Rate ◽  
Strong Component ◽  
Order Of Growth ◽  
Finite Sets ◽  
Complex Order

We study FAD-languages, which are regular languages defined by finite sets of forbidden factors, together with their “canonical” recognizing automata. We are mainly interested in the possible asymptotic orders of growth for such languages. We analyze certain simplifications of sets of forbidden factors and show that they “almost” preserve the canonical automata. Using this result and structural properties of canonical automata, we describe an algorithm that effectively lists all canonical automata having a sink strong component isomorphic to a given digraph, or reports that no such automata exist. This algorithm can be used, in particular, to prove the existence of a FAD-language over a given alphabet with a given exponential growth rate. On the other hand, we give an example showing that the algorithm cannot prove non-existence of a FAD-language having a given growth rate. Finally, we provide some examples of canonical automata with a nontrivial condensation graph and of FAD-languages with a “complex” order of growth.

Validation and Analysis of Modeled Predictions of Growth of Bacillus cereus Spores in Boiled Rice

2000 ◽  
Vol 63 (2) ◽  
pp. 268-272 ◽  
Author(s):  
DANA M. McELROY ◽  
LEE-ANN JAYKUS ◽  
PEGGY M. FOEGEDING
Keyword(s):  
Growth Rate ◽  
Bacillus Cereus ◽  
Exponential Growth ◽  
Generation Time ◽  
Time Lag ◽  
Lag Phase ◽  
Exponential Growth Rate ◽  
Phase Duration ◽  
Margin Of Safety ◽  
Fail Safe

The growth of psychrotrophic Bacillus cereus 404 from spores in boiled rice was examined experimentally at 15, 20, and 30°C. Using the Gompertz function, observed growth was modeled, and these kinetic values were compared with kinetic values for the growth of mesophilic vegetative cells as predicted by the U.S. Department of Agriculture's Pathogen Modeling Program, version 5.1. An analysis of variance indicated no statistically significant difference between observed and predicted values. A graphical comparison of kinetic values demonstrated that modeled predictions were “fail safe” for generation time and exponential growth rate at all temperatures. The model also was fail safe for lag-phase duration at 20 and 30°C but not at l5°C. Bias factors of 0.55, 0.82, and 1.82 for generation time, lag-phase duration, and exponential growth rate, respectively, indicated that the model generally was fail safe and hence provided a margin of safety in its growth predictions. Accuracy factors of 1.82, 1.60, and 1.82 for generation time, lag-phase duration, and exponential growth rate, respectively, quantitatively demonstrated the degree of difference between predicted and observed values. Although the Pathogen Modeling Program produced reasonably accurate predictions of the growth of psychrotrophic B. cereus from spores in boiled rice, the margin of safety provided by the model may be more conservative than desired for some applications. It is recommended that if microbial growth modeling is to be applied to any food safety or processing situation, it is best to validate the model before use. Once experimental data are gathered, graphical and quantitative methods of analysis can be useful tools for evaluating specific trends in model prediction and identifying important deviations between predicted and observed data.

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