scholarly journals Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak

2020 ◽  
Author(s):  
Sang Woo Park ◽  
Benjamin M. Bolker ◽  
David Champredon ◽  
David J. D. Earn ◽  
Michael Li ◽  
...  
Keyword(s):  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Similar Data ◽  
Primary Case ◽  
Susceptible Population ◽  
Generation Interval ◽  
Statistical Framework ◽  
Wide Range ◽  
Novel Coronavirus ◽  
Global Threat

AbstractA novel coronavirus (SARS-CoV-2) has recently emerged as a global threat. As the epidemic progresses, many disease modelers have focused on estimating the basic reproductive number ℛ0– the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modeling approaches and resulting estimates of ℛ0 vary widely, despite relying on similar data sources. Here, we present a novel statistical framework for comparing and combining different estimates of ℛ0 across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate r, the mean generation interval , and the generation-interval dispersion κ. We then apply our framework to early estimates of ℛ0 for the SARS-CoV-2 outbreak. We show that many early ℛ0 estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of ℛ0, including the shape of the generation-interval distribution, in efforts to estimate ℛ0 at the outset of an epidemic.

scholarly journals Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak

2020 ◽  
Vol 17 (168) ◽  
pp. 20200144 ◽  
Author(s):  
Sang Woo Park ◽  
Benjamin M. Bolker ◽  
David Champredon ◽  
David J. D. Earn ◽  
Michael Li ◽  
...  
Keyword(s):  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Similar Data ◽  
Primary Case ◽  
Susceptible Population ◽  
Generation Interval ◽  
Statistical Framework ◽  
Wide Range ◽  
Novel Coronavirus ◽  
Global Threat

A novel coronavirus (SARS-CoV-2) emerged as a global threat in December 2019. As the epidemic progresses, disease modellers continue to focus on estimating the basic reproductive number R 0 —the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modelling approaches and resulting estimates of R 0 during the beginning of the outbreak vary widely, despite relying on similar data sources. Here, we present a statistical framework for comparing and combining different estimates of R 0 across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate, the mean generation interval and the generation-interval dispersion. We apply our framework to early estimates of R 0 for the SARS-CoV-2 outbreak, showing that many R 0 estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of R 0 , including the shape of the generation-interval distribution, in efforts to estimate R 0 at the outset of an epidemic.

Modeling and stability analysis of the spread of novel coronavirus disease COVID-19

2021 ◽  
pp. 2150035
Author(s):  
A. George Maria Selvam ◽  
Jehad Alzabut ◽  
D. Abraham Vianny ◽  
Mary Jacintha ◽  
Fatma Bozkurt Yousef
Keyword(s):  
Fractional Order ◽  
Disease Transmission ◽  
Equilibrium Points ◽  
Sufficient Conditions ◽  
Basic Reproductive Number ◽  
Phase Portraits ◽  
Transmission Model ◽  
Reproductive Number ◽  
Discrete Version ◽  
Novel Coronavirus

Towards the end of 2019, the world witnessed the outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (COVID-19), a new strain of coronavirus that was unidentified in humans previously. In this paper, a new fractional-order Susceptible–Exposed–Infected–Hospitalized–Recovered (SEIHR) model is formulated for COVID-19, where the population is infected due to human transmission. The fractional-order discrete version of the model is obtained by the process of discretization and the basic reproductive number is calculated with the next-generation matrix approach. All equilibrium points related to the disease transmission model are then computed. Further, sufficient conditions to investigate all possible equilibria of the model are established in terms of the basic reproduction number (local stability) and are supported with time series, phase portraits and bifurcation diagrams. Finally, numerical simulations are provided to demonstrate the theoretical findings.

scholarly journals A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model

2020 ◽  
Vol 9 (4) ◽  
pp. 944 ◽  
Author(s):  
Kentaro Iwata ◽  
Chisato Miyakoshi
Keyword(s):  
Healthcare Professionals ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Asian Countries ◽  
Hospital Visit ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Novel Coronavirus ◽  
The Impact ◽  
Multiple Scenarios

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. Even though it began to spread to many other parts of the world, such as other Asian countries, the Americas, Europe, and the Middle East, the impact of secondary outbreaks caused by exported cases outside China remains unclear. We conducted simulations to estimate the impact of potential secondary outbreaks in a community outside China. Simulations using stochastic SEIR model were conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in the total number of persons recovered or removed to be 997 (95% CrI 990–1000) at day 100 and a maximum number of symptomatic infectious patients per day of 335 (95% CrI 232–478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6–7.2). However, better case scenarios with different parameters led to no secondary cases. Altering parameters, especially time to hospital visit. could change the impact of a secondary outbreak. With these multiple scenarios with different parameters, healthcare professionals might be able to better prepare for this viral infection.

scholarly journals The effects of the clinical symptoms pneumonia-confirmation strategy of the COVID-19 epidemic in Wuhan, China

2020 ◽  
Author(s):  
Yanjin Wang ◽  
Pei Wang ◽  
Shudao Zhang ◽  
Hao Pan
Keyword(s):  
Turning Point ◽  
Clinical Symptoms ◽  
Transmission Rate ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Wuhan City ◽  
Start Date ◽  
Rapid Spread ◽  
Novel Coronavirus

Abstract Motivated by the quick control in Wuhan, China, and the rapid spread in other countries of COVID-19, we investigate the questions that what is the turning point in Wuhan by quantifying the variety of basic reproductive number after the lockdown city. The answer may help the world to control the COVID-19 epidemic. A modified SEIR model is used to study the COVID-19 epidemic in Wuhan city. Our model is calibrated by the hospitalized cases. The modeling result gives out that the means of basic reproductive numbers are 1.5517 (95% CI 1.1716-4.4283) for the period from Jan 25 to Feb 11, 2020, and 0.4738(95% CI 0.0997-0.8370) for the period from Feb 12 to Mar 10. The transmission rate fell after Feb 12, 2020 as a result of China’s COVID-19 strategy of keeping society distance and the medical support from all China, but principally because of the clinical symptoms to be used for the novel coronavirus pneumonia (NCP) confirmation in Wuhan since Feb 12, 2020. Clinical diagnosis can quicken up NCP-confirmation such that the COVID-19 patients can be isolated without delay. So the clinical symptoms pneumonia-confirmation is the turning point of the COVID-19 battle of Wuhan. The measure of clinical symptoms pneumonia-confirmation in Wuhan has delayed the growth and reduced size of the COVID-19 epidemic, decreased the peak number of the hospitalized cases by 96% in Wuhan. Our modeling also indicates that the earliest start date of COVID-19 in Wuhan may be Nov 2, 2019.

scholarly journals Estimating the Prevalence of Asymptomatic COVID-19 Cases and Their Contribution in Transmission - Using Henan Province, China, as an Example

2021 ◽  
Vol 8 ◽  
Author(s):  
Chunyu Li ◽  
Yuchen Zhu ◽  
Chang Qi ◽  
Lili Liu ◽  
Dandan Zhang ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Early Stage ◽  
Henan Province ◽  
Substantial Proportion ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The World ◽  
Asymptomatic Infections ◽  
Novel Coronavirus

Background: Novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), is now sweeping across the world. A substantial proportion of infections only lead to mild symptoms or are asymptomatic, but the proportion and infectivity of asymptomatic infections remains unknown. In this paper, we proposed a model to estimate the proportion and infectivity of asymptomatic cases, using COVID-19 in Henan Province, China, as an example.Methods: We extended the conventional susceptible-exposed-infectious-recovered model by including asymptomatic, unconfirmed symptomatic, and quarantined cases. Based on this model, we used daily reported COVID-19 cases from January 21 to February 26, 2020, in Henan Province to estimate the proportion and infectivity of asymptomatic cases, as well as the change of effective reproductive number, Rt.Results: The proportion of asymptomatic cases among COVID-19 infected individuals was 42% and the infectivity was 10% that of symptomatic ones. The basic reproductive number R0 = 2.73, and Rt dropped below 1 on January 31 under a series of measures.Conclusion: The spread of the COVID-19 epidemic was rapid in the early stage, with a large number of asymptomatic infected individuals having relatively low infectivity. However, it was quickly brought under control with national measures.

scholarly journals Transmission dynamics of SARS-COV-2 in China: impact of public health interventions

2020 ◽  
Author(s):  
Wenbao Wang ◽  
Yiqin Chen ◽  
Qi Wang ◽  
Ping Cai ◽  
Ye He ◽  
...  
Keyword(s):  
Public Health ◽  
Health Interventions ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Public Health Interventions ◽  
The Public ◽  
Global Pandemic ◽  
Actual Growth ◽  
Global Threat ◽  
The Impact

AbstractCOVID-19 has become a global pandemic. However, the impact of the public health interventions in China needs to be evaluated. We established a SEIRD model to simulate the transmission trend of China. In addition, the reduction of the reproductive number was estimated under the current forty public health interventions policies. Furthermore, the infection curve, daily transmission replication curve, and the trend of cumulative confirmed cases were used to evaluate the effects of the public health interventions. Our results showed that the SEIRD curve model we established had a good fit and the basic reproductive number is 3.38 (95% CI, 3.25–3.48). The SEIRD curve show a small difference between the simulated number of cases and the actual number; the correlation index (H2) is 0.934, and the reproductive number (R) has been reduced from 3.38 to 0.5 under the current forty public health interventions policies of China. The actual growth curve of new cases, the virus infection curve, and the daily transmission replication curve were significantly going down under the current public health interventions. Our results suggest that the current public health interventions of China are effective and should be maintained until COVID-19 is no longer considered a global threat.

scholarly journals A mathematical model of COVID-19 transmission between frontliners and the general public

2020 ◽  
Author(s):  
Christian Alvin H. Buhat ◽  
Monica C. Torres ◽  
Yancee H. Olave ◽  
Maica Krizna A. Gavina ◽  
Edd Francis O. Felix ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Customer Service ◽  
General Public ◽  
Food Service ◽  
The Philippines ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Primary Case ◽  
Epidemic Curve ◽  
Community Effort

ABSTRACTThe number of COVID-19 cases is continuously increasing in different countries (as of March 2020) including the Philippines. It is estimated that the basic reproductive number of COVID-19 is around 1.5 to 4. The basic reproductive number characterizes the average number of persons that a primary case can directly infect in a population full of susceptible individuals. However, there can be superspreaders that can infect more than this estimated basic reproductive number. In this study, we formulate a conceptual mathematical model on the transmission dynamics of COVID-19 between the frontliners and the general public. We assume that the general public has a reproductive number between 1.5 to 4, and frontliners (e.g. healthcare workers, customer service and retail personnel, food service crews, and transport or delivery workers) have a higher reproduction number. Our simulations show that both the frontliners and the general public should be protected or resilient against the disease. Protecting only the frontliners will not result in flattening the epidemic curve. Protecting only the general public may flatten the epidemic curve but the infection risk faced by the frontliners is still high, which may eventually affect their work. Our simple model does not consider all factors involved in COVID-19 transmission in a community, but the insights from our model results remind us of the importance of community effort in controlling the transmission of the disease. All in all, the take-home message is that everyone in the community, whether a frontliner or not, should be protected or should implement preventive measures to avoid being infected.

scholarly journals Sensitivity and mathematical model analysis on secondhand smoking tobacco

2020 ◽  
Vol 28 (1) ◽  
Author(s):  
Birliew Fekede ◽  
Benyam Mebrate
Keyword(s):  
Mathematical Model ◽  
Equilibrium Point ◽  
Equilibrium Points ◽  
Reproductive Number ◽  
Primary Case ◽  
Susceptible Population ◽  
Proposed Model ◽  
Relative Change ◽  
Well Posed ◽  
Mathematical Model Analysis

AbstractIn this paper, we are concerned with a mathematical model of secondhand smoker. The model is biologically meaningful and mathematically well posed. The reproductive number $$R_{0}$$ R 0 is determined from the model, and it measures the average number of secondary cases generated by a single primary case in a fully susceptible population. If $$R_{0}<1,$$ R 0 < 1 , the smoking-free equilibrium point is stable, and if $$R_{0}>1,$$ R 0 > 1 , endemic equilibrium point is unstable. We also provide numerical simulation to show stability of equilibrium points. In addition, sensitivity analysis of parameters involving in the dynamic system of the proposed model has been included. The parameters involving in reproductive number measure the relative change in $$R_{0}$$ R 0 when the value of the parameter changes.

scholarly journals A fractional complex network model for novel corona virus in China

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
H. A. A. El-Saka ◽  
I. Obaya ◽  
H. N. Agiza
Keyword(s):  
Sensitivity Analysis ◽  
Complex Network ◽  
Epidemic Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Zoonotic Virus ◽  
Numerical Examples ◽  
Novel Coronavirus ◽  
Varying Population

AbstractAs is well known the novel coronavirus (COVID-19) is a zoonotic virus and our model is concerned with the effect of the zoonotic source of the coronavirus during the outbreak in China. We present a SEIS complex network epidemic model for the novel coronavirus. Our model is presented in fractional form and with varying population. The steady states and the basic reproductive number are calculated. We also present some numerical examples and the sensitivity analysis of the basic reproductive number for the parameters.

scholarly journals The Novel Coronavirus, 2019-nCoV, is Highly Contagious and More Infectious Than Initially Estimated

2020 ◽  
Author(s):  
Steven Sanche ◽  
Yen Ting Lin ◽  
Chonggang Xu ◽  
Ethan Romero-Severson ◽  
Nick Hengartner ◽  
...  
Keyword(s):  
Case Reports ◽  
Individual Case ◽  
Control Measures ◽  
Basic Reproductive Number ◽  
Contact Tracing ◽  
Reproductive Number ◽  
The Novel ◽  
Transmission Potential ◽  
Novel Coronavirus ◽  
Strong Control

AbstractThe novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R0, was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus.One-sentence summaryBy collecting and analyzing spatiotemporal data, we estimated the transmission potential for 2019-nCoV.

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