scholarly journals Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions

2020 ◽  
Author(s):  
Jonathan M. Read ◽  
Jessica R.E. Bridgen ◽  
Derek A.T. Cummings ◽  
Antonia Ho ◽  
Chris P. Jewell
Keyword(s):  
Large Scale ◽  
Likelihood Function ◽  
Restriction Analysis ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Reproductive Number ◽  
List Type ◽  
Novel Coronavirus ◽  
Scale Control

AbstractSince first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. using a transmission model, we estimate a basic reproductive number of 3.11 (95%CI, 2.39–4.13); 58–76% of transmissions must be prevented to stop increasing; Wuhan case ascertainment of 5.0% (3.6–7.4); 21022 (11090–33490) total infections in Wuhan 1 to 22 January.Changes to previous versioncase data updated to include 22 Jan 2020; we did not use cases reported after this period as cases were reported at the province level hereafter, and large-scale control interventions were initiated on 23 Jan 2020;improved likelihood function, better accounting for first 41 confirmed cases, and now using all infections (rather than just cases detected) in Wuhan for prediction of infection in international travellers;improved characterization of uncertainty in parameters, and calculation of epidemic trajectory confidence intervals using a more statistically rigorous method;extended range of latent period in sensitivity analysis to reflect reports of up to 6 day incubation period in household clusters;removed travel restriction analysis, as different modelling approaches (e.g. stochastic transmission, rather than deterministic transmission) are more appropriate to such analyses.

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 Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates

2021 ◽  
Vol 376 (1829) ◽  
pp. 20200265
Author(s):  
Jonathan M. Read ◽  
Jessica R. E. Bridgen ◽  
Derek A. T. Cummings ◽  
Antonia Ho ◽  
Chris P. Jewell
Keyword(s):  
Prediction Interval ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Reproductive Number ◽  
Theme Issue ◽  
Epidemic Size ◽  
Pandemic Response ◽  
Novel Coronavirus ◽  
The Uk ◽  
Size Estimates

Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39–4.13), indicating that 58–76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6–7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090–33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

scholarly journals Differential effects of intervention timing on COVID-19 spread in the United States

2020 ◽  
Vol 6 (49) ◽  
pp. eabd6370 ◽  
Author(s):  
Sen Pei ◽  
Sasikiran Kandula ◽  
Jeffrey Shaman
Keyword(s):  
United States ◽  
Disease Transmission ◽  
Human Mobility ◽  
The United States ◽  
Control Measures ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Reproductive Number ◽  
Mobility Data ◽  
Nonpharmaceutical Interventions

Assessing the effects of early nonpharmaceutical interventions on coronavirus disease 2019 (COVID-19) spread is crucial for understanding and planning future control measures to combat the pandemic. We use observations of reported infections and deaths, human mobility data, and a metapopulation transmission model to quantify changes in disease transmission rates in U.S. counties from 15 March to 3 May 2020. We find that marked, asynchronous reductions of the basic reproductive number occurred throughout the United States in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same measures been implemented 1 to 2 weeks earlier, substantial cases and deaths could have been averted and that delayed responses to future increased incidence will facilitate a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive control in combatting the COVID-19 pandemic.

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 Evaluation of Different Types of Face Masks to Limit the Spread of SARS-CoV-2 – A Modeling Study

2021 ◽  
Author(s):  
Brian M. Gurbaxani ◽  
Andrew N. Hill ◽  
Prabasaj Paul ◽  
Pragati V. Prasad ◽  
Rachel B. Slayton
Keyword(s):  
The United States ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Source Control ◽  
Reproductive Number ◽  
Medical Procedure ◽  
Different Types ◽  
Protection Efficacy ◽  
N95 Respirators ◽  
Related Mortality

AbstractWe updated a published mathematical model of SARS-CoV-2 transmission with laboratory-derived source and wearer protection efficacy estimates for a variety of face masks to estimate their impact on COVID-19 incidence and related mortality in the United States. When used at already-observed population rates of 80% for those ≥65 years and 60% for those <65 years, face masks are associated with 69% (cloth) to 78% (medical procedure mask) reductions in cumulative COVID-19 infections and 82% (cloth) to 87% (medical procedure mask) reductions in related deaths over a 6-month timeline in the model. If cloth or medical procedure masks’ source control and wearer protection efficacies are boosted about 30% each to 84% and 60% by cloth over medical procedure masking, fitters, or braces, the COVID-19 basic reproductive number of 2.5 could decrease to an effective reproductive number ≤ 1.0, and from 4.0 to ≈ 1.6 for the B.1.1.7 variant.Article Summary LineAdapting a published SARS-CoV-2 transmission model together with updated, laboratory-derived source control and wearer protection efficacy estimates for a variety of face coverings as well as N95 respirators, we demonstrate that community masking as currently practiced has likely reduced cases and deaths and that this benefit can be increased with wider adoption of better performing masks.

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 Expected impact of lockdown in Île-de-France and possible exit strategies

2020 ◽  
Author(s):  
Laura Di Domenico ◽  
Giulia Pullano ◽  
Chiara E. Sabbatini ◽  
Pierre-Yves Boëlle ◽  
Vittoria Colizza
Keyword(s):  
Substantial Reduction ◽  
Case Finding ◽  
System Capacity ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Reproductive Number ◽  
Health Crisis ◽  
Social Distancing ◽  
Response Planning ◽  
Exit Strategies

More than half of the global population is currently under strict forms of social distancing, with more than 90 countries in lockdown, including France. Estimating the expected impact of the lockdown, and the potential effectiveness of different exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis. We use a stochastic age-structured transmission model integrating data on age profile and social contacts in the Île-de-France region to (i) assess the current epidemic situation, (ii) evaluate the expected impact of the lockdown implemented in France on March 17, 2020, and (iii) estimate the effectiveness of possible exit strategies. The model is calibrated on hospital admission data of the region before lockdown and validated on syndromic and virological surveillance data. Different types and durations of social distancing interventions are simulated, including a progressive lifting of the lockdown targeted on specific classes of individuals (e.g. allowing a larger proportion of the population to go to work, while protecting the elderly), and large-scale testing. We estimate the basic reproductive number at 3.0 [2.8, 3.2] (95% confidence interval) prior to lockdown and the population infected by COVID-19 as of April 5 to be in the range 1% to 6%. The average number of contacts is predicted to be reduced by 80% during lockdown, leading to a substantial reduction of the reproductive number (RLD =0.68 [0.62-0.73]). Under these conditions, the epidemic curve reaches ICU system capacity and slowly decreases during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave largely overwhelming the healthcare system. Extensive case-finding, testing and isolation are required to envision social distancing strategies that gradually relax current constraints (larger fraction of individuals going back to work, progressive reopening of activities), while keeping schools closed and seniors isolated. As France faces the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case-finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.

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.

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