scholarly journals Serial interval and basic reproduction number of SARS-CoV-2 Omicron variant in South Korea

Author(s):  
Dasom Kim ◽  
Jisoo Jo ◽  
Jun-Sik Lim ◽  
Sukhyun Ryu

South Korea is experiencing the community transmission of the SARS-CoV-2 Omicron variant (B.1.1.529). We estimated that the mean of the serial interval was 2.22 days, and the basic reproduction number was 1.90 (95% Credible Interval, 1.50-2.43) for the Omicron variant outbreak in South Korea.

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Khosravi ◽  
R. Chaman ◽  
M. Rohani-Rasaf ◽  
F. Zare ◽  
S. Mehravaran ◽  
...  

Abstract The aim of this study was to estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The 30-day probable incidence and cumulative incidence were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using ‘earlyR’ and ‘projections’ packages in R software. The maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1−3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI 1.03–1.25) by the end of day 42. The expected average number of new cases in Shahroud was 9.0 ± 3.8 cases/day, which means an estimated total of 271 (95% CI: 178–383) new cases for the period between 02 April to 03 May 2020. By day 67 (27 April), the effective reproduction number (Rt), which had a descending trend and was around 1, reduced to 0.70. Based on the Rt for the last 21 days (days 46–67 of the epidemic), the prediction for 27 April to 26 May is a mean daily cases of 2.9 ± 2.0 with 87 (48–136) new cases. In order to maintain R below 1, we strongly recommend enforcing and continuing the current preventive measures, restricting travel and providing screening tests for a larger proportion of the population.


2020 ◽  
Author(s):  
Hyojung Lee ◽  
Yeahwon Kim ◽  
Eunsu Kim ◽  
Sunmi ‍Lee

BACKGROUND The emergence of COVID-19 has posed a serious threat to humans all around the world despite recent achievements of vaccines, antiviral drugs, and medical infrastructure. Our modern society has evolved too complex and most of the countries are tightly connected on a global scale. This makes it nearly impossible to implement perfect and prompt mitigation strategies for the COVID-19 outbreaks. Especially, due to the explosive growth of international travels, the diverse network and complexity of human mobility become an essential factor that gives rise to the spread of COVID-19 globally within a very short time. OBJECTIVE South Korea is one of the countries that have experienced the early stage of the COVID-19 pandemic. In the absence of vaccines and treatments, South Korea has implemented and maintained stringent interventions such as large-scale epidemiological investigation, rapid diagnosis, social distancing, and prompt clinical classification of severe patients with appropriate medical measures. In particular, South Korea has been implementing effective screening and quarantine at the airport. In this work, we aim to investigate the impacts of such effective interventions on international travels which can prevent local transmission of COVID-19. METHODS The relation between the number of passengers and the number of imported cases were analyzed. Based on the relation, we have assessed the country-specific risk as the spread of COVID-19 gets expanded from January to October 2020. Moreover, a renewal mathematical modeling has been employed incorporating the risk assessment to capture both imported and local cases of COVID-19 in South Korea. We have estimated the basic reproduction number and the effective reproduction number accounting for both imported and local cases. RESULTS The basic reproduction number (R_0) was estimated at 1.87 (95% CI : 1.47, 2.35) with the rate (α =0.07)of the secondary transmission caused by the imported cases. The time-varying basic reproduction number (effective reproduction number, R_t) was estimated. Our results indicate that the prompt implementation of case-isolation and quarantine were effective to reduce the. secondary cases from imported cases in spite of constant inflows from high-risk countries of COVID-19 all throughout the year 2020. Moreover, various mitigation interventions including social distancing and movement restriction have been maintained effectively to reduce the spread of local cases in South Korea. CONCLUSIONS We have investigated the relative risk of importation of COVID-19, using the country-specific epidemiological data, and passenger volume. By combining the social distancing, screening, and self-quarantine for all travelers entering Korea, the mitigation of COVID-19 transmission caused by imported cases in Korea was highly successful. Those efforts, accompanied by identification of the source of infection, the strengthened quarantine measures for travelers from overseas countries, should be continued. However, the recent new coronavirus variant originated from South Africa has been threatening to get back to the strict border control and lockdown of all around the world again. Therefore, it is urgent to assess the importation risk and maintain an effective surveillance system of COVID-19 in South Korea.


1998 ◽  
Vol 121 (2) ◽  
pp. 309-324 ◽  
Author(s):  
E. VYNNYCKY ◽  
P. E. M. FINE

The net and basic reproduction numbers are among the most widely-applied concepts in infectious disease epidemiology. A net reproduction number (the average number of secondary infectious cases resulting from each case in a given population) of above 1 is conventionally associated with an increase in incidence; the basic reproduction number (defined analogously for a ‘totally susceptible’ population) provides a standard measure of the ‘transmission potential’ of an infection. Using a model of the epidemiology of tuberculosis in England and Wales since 1900, we demonstrate that these measures are difficult to apply if disease can follow reinfection, and that they lose their conventional interpretations if important epidemiological parameters, such as the rate of contact between individuals, change over the time interval between successive cases in a chain of transmission (the serial interval).The net reproduction number for tuberculosis in England and Wales appears to have been approximately 1 from 1900 until 1950, despite concurrent declines in morbidity and mortality rates, and it declined rapidly in the second half of this century. The basic reproduction number declined from about 3 in 1900, reached 2 by 1950, and first fell below 1 in about 1960. Reductions in effective contact between individuals over this period, measured in terms of the average number of individuals to whom each case could transmit the infection, meant that the conventional basic reproduction number measure (which does not consider subsequent changes in epidemiological parameters) for a given year failed to reflect the ‘actual transmission potential’ of the infection. This latter property is better described by a variant of the conventional measure which takes secular trends in contact into account. These results are relevant for the interpretation of trends in any infectious disease for which epidemiological parameters change over time periods comparable to the infectious period, incubation period or serial interval.


Author(s):  
Shi Zhao ◽  
Qianyin Lin ◽  
Jinjun Ran ◽  
Salihu S Musa ◽  
Guangpu Yang ◽  
...  

AbstractBackgroundsAn ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city of China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.MethodsAccounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.FindingsThe early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.ConclusionThe mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.


2020 ◽  
Author(s):  
James Yeongjun Park

AbstractBackgroundCoronavirus disease 2019 (COVID-19) has been rapidly spreading throughout China and other countries including South Korea. As of March 12, 2020, a total number of 7,869 cases and 66 deaths had been documented in South Korea. Although the first confirmed case in South Korea was identified on January 20, 2020, the number of confirmed cases showed a rapid growth on February 19, 2020 with a total number of 1,261 cases with 12 deaths based on the Korea Centers for Disease Control and Prevention (KCDC).MethodUsing the data of confirmed cases of COVID-19 in South Korea that are publicly available from the KCDC, this paper aims to create spatial visualizations of COVID-19 transmission between January 20, 2020 and February 19, 2020.ResultsUsing spatial visualization, this paper identified two early transmission clusters in South Korea (Daegu cluster and capital area cluster). Using a degree-weighted centrality measure, this paper proposes potential super-spreaders of the virus in the visualized clusters.ConclusionCompared to various epidemiological measures such as the basic reproduction number, spatial visualizations of the cluster-specific transmission networks and the proposed centrality measure may be more useful to characterize super-spreaders and the spread of the virus especially in the early epidemic phase.


Author(s):  
Lauren C. Tindale ◽  
Michelle Coombe ◽  
Jessica E. Stockdale ◽  
Emma S. Garlock ◽  
Wing Yin Venus Lau ◽  
...  

AbstractBackgroundAs the COVID-19 epidemic is spreading, incoming data allows us to quantify values of key variables that determine the transmission and the effort required to control the epidemic. We determine the incubation period and serial interval distribution for transmission clusters in Singapore and in Tianjin. We infer the basic reproduction number and identify the extent of pre-symptomatic transmission.MethodsWe collected outbreak information from Singapore and Tianjin, China, reported from Jan.19-Feb.26 and Jan.21-Feb.27, respectively. We estimated incubation periods and serial intervals in both populations.ResultsThe mean incubation period was 7.1 (6.13, 8.25) days for Singapore and 9 (7.92, 10.2) days for Tianjin. Both datasets had shorter incubation periods for earlier-occurring cases. The mean serial interval was 4.56 (2.69, 6.42) days for Singapore and 4.22 (3.43, 5.01) for Tianjin. We inferred that early in the outbreaks, infection was transmitted on average 2.55 and 2.89 days before symptom onset (Singapore, Tianjin). The estimated basic reproduction number for Singapore was 1.97 (1.45, 2.48) secondary cases per infective; for Tianjin it was 1.87 (1.65, 2.09) secondary cases per infective.ConclusionsEstimated serial intervals are shorter than incubation periods in both Singapore and Tianjin, suggesting that pre-symptomatic transmission is occurring. Shorter serial intervals lead to lower estimates of R0, which suggest that half of all secondary infections should be prevented to control spread.


Author(s):  
Ann Barber ◽  
John M Griffin ◽  
Miriam Casey ◽  
Aine Collins ◽  
Elizabeth A Lane ◽  
...  

Background: The transmissibility of SARS-CoV-2 determines both the ability of the virus to invade a population and the strength of intervention that would be required to contain or eliminate the spread of infection. The basic reproduction number, R0, provides a quantitative measure of the transmission potential of a pathogen. Objective: Conduct a scoping review of the available literature providing estimates of R0 for SARS-CoV-2, provide an overview of the drivers of variation in R0 estimates and the considerations taken in the calculation of the parameter. Design: Scoping review of available literature between the 01 December 2019 and 07 May 2020. Data sources: Both peer-reviewed and pre-print articles were searched for on PubMed, Google Scholar, MedRxiv and BioRxiv. Selection criteria: Studies were selected for review if (i) the estimation of R0 represented either the initial stages of the outbreak or the initial stages of the outbreak prior to the onset of widespread population restriction (lockdown), (ii) the exact dates of the study period were provided and (iii) the study provided primary estimates of R0. Results: A total of 20 R0 estimates were extracted from 15 studies. There was substantial variation in the estimates reported. Estimates derived from mathematical models fell within a wider range of 1.94-6.94 than statistical models which fell between the range of 2.2 to 4.4. Several studies made assumptions about the length of the infectious period which ranged from 5.8-20 days and the serial interval which ranged from 4.41-14 days. For a given set of parameters a longer duration of infectiousness or a longer serial interval equates to a higher R0. Several studies took measures to minimise bias in early case reporting, to account for the potential occurrence of super-spreading events, and to account for early sub-exponential epidemic growth. Conclusions: The variation in reported estimates of R0 reflects the complex nature of the parameter itself, including the context (i.e. social/spatial structure), the methodology used to estimate the parameter, and model assumptions. R0 is a fundamental parameter in the study of infectious disease dynamics however it provides limited practical applicability outside of the context in which it was estimated, and should be calculated and interpreted with this in mind.


2020 ◽  
Author(s):  
Ahmad Khosravi ◽  
Reza Chaman ◽  
Marzieh Rohani-Rasaf ◽  
Fariba Zare ◽  
Shiva Mehravaran ◽  
...  

AbstractObjectivesTo estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud, Northeast of Iran.MethodsThe R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The serial interval was fit with a gamma distribution. The probable incidence and cumulative incidence in the next 30 days were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using “earlyR” and “projections” packages in R software.ResultsThe maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1 to 3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI: 1.03 to 1.25) by the end of the day 41. The expected average number of new cases in Shahroud is 9.0±3.8 case/day, which means an estimated total of 271 (95% CI: 178-383) new cases in the next 30 days.ConclusionsIt is essential to reduce the R0 to values below one. Therefore, we strongly recommend enforcing and continuing the current preventive measures, restricting travel, and providing screening tests for a larger proportion of the population.


2003 ◽  
Vol 131 (2) ◽  
pp. 1015-1022 ◽  
Author(s):  
T. J. HAGENAARS ◽  
C. A. DONNELLY ◽  
N. M. FERGUSON ◽  
R. M. ANDERSON

Knowledge of epidemiological mechanisms and parameters underlying scrapie transmission in sheep flocks remains very limited at present. Here we introduce a method for fitting stochastic transmission models to outbreak data to estimate bounds on key transmission parameters. We apply this method to data describing an outbreak of scrapie in a closed flock of Romanov sheep. The main findings are that the relative infectiousness of infected animals in this outbreak becomes appreciable early into disease incubation and that the mean incubation period is less than 1·5 years. We also find that the data are consistent with a broad range of values for the basic reproduction number R0 and describe how the boundaries of this range depend on assumptions about the mean incubation period and the contribution to transmission of a long-lived environmental reservoir of infectivity.


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