scholarly journals Spatial variability in reproduction number and doubling time across two waves of the COVID-19 pandemic in South Korea, February to July 2020

2020 ◽  
Author(s):  
Eunha Shim ◽  
Amna Tariq ◽  
Gerardo Chowell
Keyword(s):  
South Korea ◽  
Doubling Time ◽  
Reproduction Number ◽  
Control Measures ◽  
List Type ◽  
Transmission Potential ◽  
Reproduction Numbers ◽  
Gyeonggi Province ◽  
The Government ◽  
Second Wave

AbstractObjectivesIn South Korea, 13,745 cases of coronavirus disease (COVID-19) have been reported as of 19 July, 2020. To examine the spatiotemporal changes in the transmission potential, we present regional estimates of the doubling time and reproduction number (Rt) of COVID-19 in the country.MethodsDaily series of confirmed COVID-19 cases in the most affected regions were extracted from publicly available sources. We employed established mathematical and statistical methods to investigate the time-varying reproduction numbers of the COVID-19 in Korea and its doubling time, respectively.ResultsAt the regional level, Seoul and Gyeonggi Province have experienced the first peak of COVID-19 in early March, followed by the second wave in early June, with Rt exceeding 3.0 and mean doubling time ranging from 3.6 to 10.1 days. As of 19 July, 2020, Gyeongbuk Province and Daegu are yet to experience a second wave of the disease, where the mean Rt reached 3.5-4.4 and doubling time ranging from 2.8 to 4.6 days during the first wave.ConclusionsOur findings support the effectiveness of control measures against COVID-19 in Korea. However, the easing of the restrictions imposed by the government in May 2020 facilitated a second wave in the greater Seoul area.HighlightsSouth Korea has experienced two spatially heterogenous waves of COVID-19.Seoul and Gyeonggi Province experienced two waves of COVID-19 in March and June.In the densely populated Seoul and nearby areas, reproduction numbers exceeded 3.0.The easing of the social distancing measures resulted in the second wave.

scholarly journals Estimation of the Time-dependent Reproduction Number of Influenza A(H1N1)pdm2009 in South Korea

2020 ◽  
Author(s):  
Yunjeong Lee ◽  
Dong Han Lee ◽  
Hee-Dae Kwon ◽  
Changsoo Kim ◽  
Jeehyun Lee
Keyword(s):  
South Korea ◽  
Influenza A ◽  
Reproduction Number ◽  
Time Estimation ◽  
Time Dependent ◽  
Estimation Of Parameters ◽  
Transmission Potential ◽  
Reproduction Numbers ◽  
Influenza A H1n1 ◽  
Feasible Range

Abstract Background: The reproduction number is one of the most crucial parameters in determining disease dynamics, providing a summary measure of the transmission potential. However, estimating this value is particularly challenging owing to the characteristics of epidemic data, including non-reproducibility and incompleteness.Methods: In this study, we propose mathematical models with different population structures; each of these models can produce data on the number of cases of the influenza A(H1N1)pdm09 epidemic in South Korea. These structured models incorporating the heterogeneity of age and region are used to estimate the time-dependent effective reproduction numbers. Subsequently, the age- and region-specific reproduction numbers are also computed to analyze the differences illustrated in the incidence data.Results: The basic SIR fails to provide a reasonable estimation of the reproduction numbers. The estimated values demonstrate a large variation and remains outside of the feasible range for the influenza, regardless of the time period for data. Real-time estimation using age- and region-structured models demonstrated that the effective reproduction number rose sharply during mid-October when the ㅜumber of patients increased dramatically. The reproduction number fell below unity at the end of October and stayed lower than unity indicating that the epidemic starts decreasing, which is consistent with the incidence data.Conclusions: Numerical results reveal that the introduction of heterogeneity into the population to represent the general characteristics of dynamics is essential for the robust estimation of parameters.

scholarly journals Estimation of the Reproduction Number of Influenza A(H1N1)pdm2009 in South Korea Using Heterogeneous Models

2020 ◽  
Author(s):  
Yunjeong Lee ◽  
Dong Han Lee ◽  
Hee-Dae Kwon ◽  
Changsoo Kim ◽  
jeehyun lee
Keyword(s):  
South Korea ◽  
Influenza A ◽  
Reproduction Number ◽  
Time Estimation ◽  
Estimation Of Parameters ◽  
Transmission Potential ◽  
Incidence Data ◽  
Reproduction Numbers ◽  
Number Of Patients ◽  
Influenza A H1n1

Abstract Background: The reproduction number is one of the most crucial parameters in determining disease dynamics, providing a summary measure of the transmission potential. However, estimating this value is particularly challenging owing to the characteristics of epidemic data, including non-reproducibility and incompleteness.Methods: In this study, we propose mathematical models with different population structures; each of these models can produce data on the number of cases of the influenza A(H1N1)pdm09 epidemic in South Korea. These structured models incorporating the heterogeneity of age and region are used to estimate the reproduction numbers at various terminal times. Subsequently, the age- and region-specific reproduction numbers are also computed to analyze the differences illustrated in the incidence data. Results: The basic SIR fails to provide a reasonable estimation of the reproduction numbers. The estimated values demonstrate a large variation and remains outside of the feasible range for the influenza, regardless of the time period for data. Real-time estimation using age- and region-structured models demonstrated that the effective reproduction number rose sharply during mid-October when the number of patients increased dramatically. The reproduction number fell below unity at the end of October and stayed lower than unity indicating that the epidemic starts decreasing, which is consistent with the incidence data. Conclusions: Numerical results reveal that the introduction of heterogeneity into the population to represent the general characteristics of dynamics is essential for the robust estimation of parameters.

scholarly journals Estimation of the reproduction number of influenza A(H1N1)pdm09 in South Korea using heterogeneous models

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yunjeong Lee ◽  
Dong Han Lee ◽  
Hee-Dae Kwon ◽  
Changsoo Kim ◽  
Jeehyun Lee
Keyword(s):  
South Korea ◽  
Robust Estimation ◽  
Influenza A ◽  
Reproduction Number ◽  
Infectious Period ◽  
Estimation Of Parameters ◽  
Structured Model ◽  
Transmission Potential ◽  
Reproduction Numbers ◽  
Influenza A H1n1

Abstract Background The reproduction number is one of the most crucial parameters in determining disease dynamics, providing a summary measure of the transmission potential. However, estimating this value is particularly challenging owing to the characteristics of epidemic data, including non-reproducibility and incompleteness. Methods In this study, we propose mathematical models with different population structures; each of these models can produce data on the number of cases of the influenza A(H1N1)pdm09 epidemic in South Korea. These structured models incorporating the heterogeneity of age and region are used to estimate the reproduction numbers at various terminal times. Subsequently, the age- and region-specific reproduction numbers are also computed to analyze the differences illustrated in the incidence data. Results Incorporation of the age-structure or region-structure allows for robust estimation of parameters, while the basic SIR model provides estimated values beyond the reasonable range with severe fluctuation. The estimated duration of infectious period using age-structured model is around 3.8 and the reproduction number was estimated to be 1.6. The estimated duration of infectious period using region-structured model is around 2.1 and the reproduction number was estimated to be 1.4. The estimated age- and region-specific reproduction numbers are consistent with cumulative incidence for corresponding groups. Conclusions Numerical results reveal that the introduction of heterogeneity into the population to represent the general characteristics of dynamics is essential for the robust estimation of parameters.

scholarly journals Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zuiyuan Guo ◽  
Dan Xiao
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Cumulative Number ◽  
Individual Based Model ◽  
Whole Process ◽  
Coordinate Descent Algorithm ◽  
Initial Stage ◽  
The Government ◽  
Prevention And Control Measures ◽  
And Control

AbstractWe established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82–5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982–2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

scholarly journals Transmission potential of COVID-19 in South Korea

2020 ◽  
Author(s):  
Eunha Shim ◽  
Amna Tariq ◽  
Wongyeong Choi ◽  
Yiseul Lee ◽  
Gerardo Chowell
Keyword(s):  
South Korea ◽  
Reproduction Number ◽  
Social Distancing ◽  
Transmission Potential ◽  
Incidence Data ◽  
Novel Coronavirus

AbstractSince the first identified individual of 2019 novel coronavirus (COVID-19) infection on Jan 20, 2020 in South Korea, the number of confirmed cases rapidly increased. As of Feb 26, 2020, 1,261 cases of COVID-19 including 12 deaths were confirmed in South Korea. Using the incidence data of COVID-19, we estimate the reproduction number at 1.5 (95% CI: 1.4-1.6), which indicates sustained transmission and support the implementation of social distancing measures to rapidly control the outbreak.

scholarly journals Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia

2020 ◽  
Vol 17 (15) ◽  
pp. 5509 ◽  
Author(s):  
Balvinder Singh Gill ◽  
Vivek Jason Jayaraj ◽  
Sarbhan Singh ◽  
Sumarni Mohd Ghazali ◽  
Yoon Ling Cheong ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Model Calibration ◽  
Reproduction Number ◽  
Close Contact ◽  
Movement Control ◽  
Control Measures ◽  
Seir Model ◽  
Epidemic Curve ◽  
Reproduction Numbers ◽  
Control Order

Malaysia is currently facing an outbreak of COVID-19. We aim to present the first study in Malaysia to report the reproduction numbers and develop a mathematical model forecasting COVID-19 transmission by including isolation, quarantine, and movement control measures. We utilized a susceptible, exposed, infectious, and recovered (SEIR) model by incorporating isolation, quarantine, and movement control order (MCO) taken in Malaysia. The simulations were fitted into the Malaysian COVID-19 active case numbers, allowing approximation of parameters consisting of probability of transmission per contact (β), average number of contacts per day per case (ζ), and proportion of close-contact traced per day (q). The effective reproduction number (Rt) was also determined through this model. Our model calibration estimated that (β), (ζ), and (q) were 0.052, 25 persons, and 0.23, respectively. The (Rt) was estimated to be 1.68. MCO measures reduce the peak number of active COVID-19 cases by 99.1% and reduce (ζ) from 25 (pre-MCO) to 7 (during MCO). The flattening of the epidemic curve was also observed with the implementation of these control measures. We conclude that isolation, quarantine, and MCO measures are essential to break the transmission of COVID-19 in Malaysia.

scholarly journals Transmission potential of COVID-19 in Iran

2020 ◽  
Author(s):  
Kamalich Muniz-Rodriguez ◽  
Isaac Chun-Hai Fung ◽  
Shayesteh R. Ferdosi ◽  
Sylvia K. Ofori ◽  
Yiseul Lee ◽  
...  
Keyword(s):  
Growth Model ◽  
Doubling Time ◽  
Reproduction Number ◽  
Transmission Potential

AbstractWe estimated the reproduction number of 2020 Iranian COVID-19 epidemic using two different methods: R0 was estimated at 4.4 (95% CI, 3.9, 4.9) (generalized growth model) and 3.50 (1.28, 8.14) (epidemic doubling time) (February 19 - March 1) while the effective R was estimated at 1.55 (1.06, 2.57) (March 6-19).

scholarly journals Assessing the lockdown effect from excess mortalities

2021 ◽  
Author(s):  
Alexej Weber
Keyword(s):  
Growth Rate ◽  
South Korea ◽  
Growth Rates ◽  
Excess Mortality ◽  
Reproduction Number ◽  
Average Growth Rate ◽  
Average Growth ◽  
Reproduction Numbers ◽  
The Difference ◽  
Pharmaceutical Interventions

AbstractBackground and AimsThe reported case numbers of COVID-19 are often used to estimate the reproduction number or the growth rate. We use the excess mortality instead, showing the difference between most restrictive non-pharmaceutical interventions (mrNPIs) and less restrictive NPIs (lrNPIs) with respect to the growth rate and death counts.MethodsWe estimate the COVID-19 growth rate for Sweden, South Korea, Italy and Germany from the excess mortality. We use the average growth rate obtained for Sweden and South Korea, two countries with lrNPIs, to estimate additional death numbers in Germany and Italy (two countries with mrNPIs) in a hypothetic lrNPIs scenario.ResultsThe growth rate estimated from excess mortality decreased faster for Germany and Italy than for Sweden and South Korea, suggesting that the mrNPIs have a non-negligible effect. This is not visible when the growth rate is calculated using the reported case numbers of COVID-19. This results in approximately 4 500 and 12 000 more death numbers for Germany and Italy, respectively.ConclusionThe reproduction numbers or growth rates obtained from reported COVID-19 cases are most likely biased. Expanding testing capacity led to an overestimation of the growth rate across all countries analyzed, masking the true decrease already visible in the excess mortality. Using our method, a more realistic estimate of the growth rate is obtained. Conclusions made for the reproduction number derived from the reported case numbers like the insignificance of most restrictive non-pharmaceutical interventions (lockdowns) might be wrong and have to be reevaluated using the growth rates obtained with our method.

scholarly journals China’s effective control and other countries’ uncharted challenge against COVID-19: an epidemiological and modelling study

2020 ◽  
Author(s):  
Lingling Zheng ◽  
Qin Kang ◽  
Weiyao Liao ◽  
Xiujuan Chen ◽  
Shuai Huang ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Case Reports ◽  
Epidemiological Data ◽  
Control Measures ◽  
Time Dependent ◽  
Effective Control ◽  
List Type ◽  
Global Epidemic ◽  
Serial Interval

AbstractBackgroundOn the present trajectory, COVID is inevitably becoming a global epidemic, leading to concerns regarding the pandemic potential in China and other countries.ObjectiveIn this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries.MethodsWe used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide.ResultsBased on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18 (IQR 1.92 – 6.65) days. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb (Rt were 0.99±0.02, 0.99±0.02 and 0.96±0.02), respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore (Rt was 0.92±0.17).ConclusionsThe epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.What is already known on this subject?The basic reproduction number (R0) and the-time-dependent reproduction number (Rt) are two important indicators of infectious disease transmission. In addition, Rt as a derivative of R0 could be used to assess the epidemiological development of the disease and effectiveness of control measures. Most current researches used data from earlier periods in Wuhan and refer to the epidemiological features of SARS, which are possibly biased. Meanwhile, there are fewer studies discussed the Rt of COVID-19. Current clinical and epidemiological data are insufficient to help us understand the full view of the potential transmission of this disease.What this study adds?We use up-to-data observation of the serial interval and cases arising from local transmission to calculate the Rt in different outbreak level area and every province in China as well as five-top sever outbreak countries and other overseas. By comparing the Rt, we discussed the situation of outbreak around the world.

scholarly journals Real-time Nowcasting and Forecasting of COVID-19 Dynamics in England: the first wave?

2020 ◽  
Author(s):  
Paul J Birrell ◽  
Joshua Blake ◽  
Edwin van Leeuwen ◽  
Nick Gent ◽  
Daniela De Angelis ◽  
...  
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
The Real ◽  
South West ◽  
Effective Contact ◽  
Ongoing Work ◽  
Reproduction Numbers ◽  
Second Wave

England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lock-down' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management. Estimates on the 10th May showed lock-down had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally-varying impact was largest in London of 81% (95% CrI: 77%-84%). Reproduction numbers have since slowly increased, and on 19th June the probability that the epidemic is growing was greater than 50% in two regions, South West and London. An estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9%-1.4%) overall but 17% (14%-22%) among the over-75s. This ongoing work will be key to quantifying any widespread resurgence should accrued immunity and effective contact tracing be insufficient to preclude a second wave.

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