scholarly journals Meta-analysis of several epidemic characteristics of COVID-19

2020 ◽  
Author(s):  
Panpan Zhang ◽  
Tiandong Wang ◽  
Sharon X. Xie
Keyword(s):  
Public Health ◽  
Doubling Time ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Daily Work ◽  
Serial Interval ◽  
Key Characteristics ◽  
Public Health Strategies ◽  
The Basic Reproduction Number ◽  
Work And Life

AbstractAs the COVID-19 pandemic has strongly disrupted people’s daily work and life, a great amount of scientific research has been conducted to understand the key characteristics of this new epidemic. In this manuscript, we focus on four crucial epidemic metrics with regard to the COVID-19, namely the basic reproduction number, the incubation period, the serial interval and the epidemic doubling time. We collect relevant studies based on the COVID-19 data in China and conduct a meta-analysis to obtain pooled estimates on the four metrics. From the summary results, we conclude that the COVID-19 has stronger transmissibility than SARS, implying that stringent public health strategies are necessary.

scholarly journals Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria

2020 ◽  
Vol 17 (9) ◽  
pp. 3054 ◽  
Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan
Keyword(s):  
Doubling Time ◽  
Reproduction Number ◽  
Infected Individual ◽  
Credible Interval ◽  
World Health ◽  
Time Interval ◽  
Serial Interval ◽  
Imported Cases ◽  
Novel Coronavirus ◽  
Health Organization

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

scholarly journals The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Khosravi ◽  
R. Chaman ◽  
M. Rohani-Rasaf ◽  
F. Zare ◽  
S. Mehravaran ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Early Stage ◽  
Screening Tests ◽  
The Novel ◽  
Epidemic Size ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Interval Distribution ◽  
The Basic Reproduction Number

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.

scholarly journals Accounting for super-spreading gives the basic reproduction number R0 of COVID-19 that is higher than initially estimated

2020 ◽  
Author(s):  
Marek Kochańczyk ◽  
Frederic Grabowski ◽  
Tomasz Lipniacki
Keyword(s):  
Basic Reproduction Number ◽  
Doubling Time ◽  
Reproduction Number ◽  
Case Reports ◽  
Individual Case ◽  
Epidemic Spread ◽  
Empirical Estimation ◽  
Seir Model ◽  
Initial Stage ◽  
The Basic Reproduction Number

Transmission of infectious diseases is characterized by the basic reproduction number R0, a metric used to assess the threat posed by an outbreak and inform proportionate preventive decision-making. Based on individual case reports from the initial stage of the coronavirus disease 2019 epidemic, R0 is often estimated to range between 2 and 4. In this report, we show that a SEIR model that properly accounts for the distribution of the incubation period suggests that R0 lie in the range 4.4–11.7. This estimate is based on the doubling time observed in the near-exponential phases of the epidemic spread in China, United States, and six European countries. To support our empirical estimation, we analyze stochastic trajectories of the SEIR model showing that in the presence of super-spreaders the calculations based on individual cases reported during the initial phase of the outbreak systematically overestimate the doubling time and thus underestimate the actual value of R0.

scholarly journals Meta-analysis of the SARS-CoV-2 serial interval and the impact of parameter uncertainty on the COVID-19 reproduction number

2020 ◽  
Author(s):  
Robert Challen ◽  
Ellen Brooks-Pollock ◽  
Krasimira Tsaneva-Atanasova ◽  
Leon Danon
Keyword(s):  
Incubation Period ◽  
Time Delays ◽  
Hospital Admissions ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Model Parameters ◽  
Small Data ◽  
Generation Interval ◽  
Serial Interval ◽  
The Impact

AbstractThe serial interval of an infectious disease, commonly interpreted as the time between onset of symptoms in sequentially infected individuals within a chain of transmission, is a key epidemiological quantity involved in estimating the reproduction number. The serial interval is closely related to other key quantities, including the incubation period, the generation interval (the time between sequential infections) and time delays between infection and the observations associated with monitoring an outbreak such as confirmed cases, hospital admissions and deaths. Estimates of these quantities are often based on small data sets from early contact tracing and are subject to considerable uncertainty, which is especially true for early COVID-19 data. In this paper we estimate these key quantities in the context of COVID-19 for the UK, including a meta-analysis of early estimates of the serial interval. We estimate distributions for the serial interval with a mean 5.6 (95% CrI 5.1–6.2) and SD 4.2 (95% CrI 3.9–4.6) days (empirical distribution), the generation interval with a mean 4.8 (95% CrI 4.3–5.41) and SD 1.7 (95% CrI 1.0–2.6) days (fitted gamma distribution), and the incubation period with a mean 5.5 (95% CrI 5.1–5.8) and SD 4.9 (95% CrI 4.5–5.3) days (fitted log normal distribution). We quantify the impact of the uncertainty surrounding the serial interval, generation interval, incubation period and time delays, on the subsequent estimation of the reproduction number, when pragmatic and more formal approaches are taken. These estimates place empirical bounds on the estimates of most relevant model parameters and are expected to contribute to modelling COVID-19 transmission.

scholarly journals Estimation of the basic reproduction number, average incubation time, asymptomatic infection rate, and case fatality rate for COVID-19: Meta-analysis and sensitivity analysis

2020 ◽  
Author(s):  
Wenqing He ◽  
Grace Y. Yi ◽  
Yayuan Zhu
Keyword(s):  
Confidence Interval ◽  
Basic Reproduction Number ◽  
Incubation Time ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Case Fatality ◽  
Asymptomatic Infection ◽  
Fatality Rate ◽  
The Basic Reproduction Number

AbstractThe coronavirus disease 2019 (COVID-19) has been found to be caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensive knowledge of COVID-19 remains incomplete and many important features are still unknown. This manuscripts conduct a meta-analysis and a sensitivity study to answer the questions: What is the basic reproduction number? How long is the incubation time of the disease on average? What portion of infections are asymptomatic? And ultimately, what is the case fatality rate? Our studies estimate the basic reproduction number to be 3.15 with the 95% interval (2.41, 3.90), the average incubation time to be 5.08 days with the 95% confidence interval (4.77, 5.39) (in day), the asymptomatic infection rate to be 46% with the 95% confidence interval (18.48%, 73.60%), and the case fatality rate to be 2.72% with 95% confidence interval (1.29%, 4.16%) where asymptomatic infections are accounted for.

scholarly journals The long-term dynamics of tuberculosis and other diseases with long serial intervals: implications of and for changing reproduction numbers

1998 ◽  
Vol 121 (2) ◽  
pp. 309-324 ◽  
Author(s):  
E. VYNNYCKY ◽  
P. E. M. FINE
Keyword(s):  
Infectious Disease ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
England And Wales ◽  
Transmission Potential ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Net Reproduction ◽  
Epidemiological Parameters ◽  
The Basic Reproduction Number

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.

scholarly journals Implications of the COVID-19 pandemic on eliminating trachoma as a public health problem

2020 ◽  
Author(s):  
Seth Blumberg ◽  
Anna Borlase ◽  
Joaquin M Prada ◽  
Anthony W Solomon ◽  
Paul Emerson ◽  
...  
Keyword(s):  
Public Health ◽  
Basic Reproduction Number ◽  
Health Problem ◽  
Reproduction Number ◽  
Control Strategies ◽  
Public Health Problem ◽  
New Paradigm ◽  
Specific Implementation ◽  
The Impact ◽  
The Basic Reproduction Number

AbstractBackgroundProgress towards elimination of trachoma as a public health problem has been substantial, but the COVID-19 pandemic has disrupted community-based control efforts.MethodsWe use a susceptible-infected model to estimate the impact of delayed distribution of azithromycin treatment on the prevalence of active trachoma.ResultsWe identify three distinct scenarios for geographic districts depending on whether the basic reproduction number and the treatment-associated reproduction number are above or below a value of one. We find that when the basic reproduction number is below one, no significant delays in disease control will be caused. However, when the basic reproduction number is above one, significant delays can occur. In most districts a year of COVID-related delay can be mitigated by a single extra round of mass drug administration. However, supercritical districts require a new paradigm of infection control because the current strategies will not eliminate disease.ConclusionIf the pandemic can motivate judicious, community-specific implementation of control strategies, global elimination of trachoma as a public health problem could be accelerated.

scholarly journals Effect of quarantine and vaccination in a pandemic situation: a mathematical modelling approach

2021 ◽  
Vol 2 (3) ◽  
pp. 77-87
Author(s):  
D. S. A. Aashiqur Reza ◽  
Md. Noman Billah ◽  
Sharmin Sultana Shanta
Keyword(s):  
Public Health ◽  
Sensitivity Analysis ◽  
Empirical Study ◽  
Mathematical Modelling ◽  
Total Population ◽  
Reproduction Number ◽  
Human Life ◽  
Global Pandemic ◽  
The Basic Reproduction Number ◽  
Modelling Approach

 When a pandemic occurs, it can cost fatal damages to human life. Therefore, it is important to understand the dynamics of a global pandemic in order to find a way of prevention. This paper contains an empirical study regarding the dynamics of the current COVID-19 pandemic. We have formulated a dynamic model of COVID-19 pandemic by subdividing the total population into six different classes namely susceptible, asymptomatic, infected, recovered, quarantined, and vaccinated. The basic reproduction number corresponding to our model has been determined. Moreover, sensitivity analysis has been conducted to find the most important parameters which can be crucial in preventing the outbreak. Numerical simulations have been made to visualize the movement of population in different classes and specifically to see the effect of quarantine and vaccination processes. The findings from our model reveal that both vaccination and quarantine are important to curtail the spread of COVID-19 pandemic. The present study can be effective in public health sectors for minimizing the burden of any pandemic.

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

2021 ◽  
Author(s):  
Dasom Kim ◽  
Jisoo Jo ◽  
Jun-Sik Lim ◽  
Sukhyun Ryu
Keyword(s):  
South Korea ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Credible Interval ◽  
Serial Interval ◽  
Community Transmission ◽  
The Mean ◽  
The Basic Reproduction Number

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.

scholarly journals A deterministic, age-stratified, extended SEIRD model for assessing the effect of non-pharmaceutical interventions on SARS-CoV-2 spread in Belgium

2020 ◽  
Author(s):  
Tijs W. Alleman ◽  
Jenna Vergeynst ◽  
Elena Torfs ◽  
Daniel Illana Gonzalez ◽  
Ingmar Nopens ◽  
...  
Keyword(s):  
Public Health ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Social Contact ◽  
The Elderly ◽  
Public Health Care ◽  
Successful Implementation ◽  
The Public ◽  
Pharmaceutical Interventions ◽  
The Basic Reproduction Number

As a response to the rapidly rising number of SARS-CoV-2 infections, the Belgian governments imposed strict social contact restrictions on March 13th, 2020. After nearly two months, the curve was successfully flattened and social restrictions were gradually relaxed. Unfortunately, pharmaceutical interventions are not yet available so it is expected that preventing COVID-19 outbreaks will depend mostly on the successful implementation of non-pharmaceutical interventions, hence the need for well-informed models. In this study, we built a deterministic, continuous-time, age-stratified-SEIRD model with detailed hospital dynamics. Because the hospitalization data for Belgium are not made publically available by the Belgian Scientific Institute of Public Health (Sciensano), we computed the hospitalization parameters based on data from 370 patients treated in two Ghent (Belgium) hospitals. The basic reproduction number was estimated as R0 = 2.83 in March 2020 and the model fits the hospitalization and ICU admission incidence under lockdown measures well. Despite the relaxation of social restrictions, hospitalizations have been steadily declining. We recomputed the basic reproduction number under lockdown release and found that it had to be as low as R0 = 0.73 to explain the endemic trend. We further found that although the basic reproduction number in the population older than 70 years was smaller than one, this group compromises nearly half of the expected hospitalizations. This indicates that the protection of the elderly may be the most efficient way to reduce strain on the public health care system in case of another SARS-CoV-2 outbreak.

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