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 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.

scholarly journals Estimating the reproductive number and the outbreak size of COVID-19 in Korea

2020 ◽  
Vol 42 ◽  
pp. e2020011 ◽  
Author(s):  
Sunhwa Choi ◽  
Moran Ki
Keyword(s):  
Transmission Rate ◽  
Transmission Model ◽  
Reproductive Number ◽  
Onset Date ◽  
The Public ◽  
Start Date ◽  
Patient Symptom ◽  
Number Of Patients ◽  
Transmission Period ◽  
Novel Coronavirus

OBJECTIVES: Since the first novel coronavirus disease 2019 (COVID-19) patient in Korea was diagnosed on January 20, 2020, 30 patients were diagnosed until February 17, 2020. However, 5,298 additional patients were confirmed until March 4, 2020. Therefore, our objective was to estimate the reproduction number (<i>R</i>) and evaluate the effectiveness of preventive measures.METHODS: A COVID-19 transmission model (SEIHR) was established to suit the Korean outbreak. The number of daily confirmed cases in Daegu and North Gyeongsang Province (NGP), the main area of outbreak, was used. The first patient’ symptom onset date in the Daegu/NGP outbreak was assumed as January 22, 2020. The <i>R</i> according to the start date of the effect of preventive measures was estimated.RESULTS: The estimated <i>R</i> in Hubei Province, China, was 4.0281, whereas the estimated initial <i>R</i> in Korea was 0.555, but later in Daegu/NGP, the value was between 3.472 and 3.543. When the transmission period decreases from 4-day to 2-day, the outbreak ends early, but the peak of the epidemic increases, and the total number of patients does not change greatly. It was found that, if transmission rate decreases, the outbreak ends early, and the size of the peak and the total number of patients also decreases.CONCLUSIONS: To end the COVID-19 epidemic, efforts to reduce the spread of the virus, such as social distancing and wearing masks, are absolutely crucial with the participation of the public, along with the policy of reducing the transmission period by finding and isolating patients as quickly as possible through the efforts of the quarantine authorities.

scholarly journals Estimation of Unreported Novel Coronavirus (SARS-CoV-2) Infections from Reported Deaths: A Susceptible–Exposed–Infectious–Recovered–Dead Model

2020 ◽  
Vol 9 (5) ◽  
pp. 1350 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi
Keyword(s):  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Novel Coronavirus ◽  
Testing Policies ◽  
Case Data

In the midst of the novel coronavirus (SARS-CoV-2) epidemic, examining reported case data could lead to biased speculations and conclusions. Indeed, estimation of unreported infections is crucial for a better understanding of the current emergency in China and in other countries. In this study, we aimed to estimate the unreported number of infections in China prior to the 23 January 2020 restrictions. To do this, we developed a Susceptible–Exposed–Infectious–Recovered–Dead (SEIRD) model that estimated unreported infections from the reported number of deaths. Our approach relied on the fact that observed deaths were less likely to be affected by ascertainment biases than reported infections. Interestingly, we estimated that the basic reproductive number (R0) was 2.43 (95%CI = 2.42–2.44) at the beginning of the epidemic and that 92.9% (95%CI = 92.5%–93.1%) of total cases were not reported. Similarly, the proportion of unreported new infections by day ranged from 52.1% to 100%, with a total of 91.8% (95%CI = 91.6%–92.1%) of infections going unreported. Agreement between our estimates and those from previous studies proves that our approach is reliable for estimating the prevalence and incidence of undocumented SARS-CoV-2 infections. Once it has been tested on Chinese data, our model could be applied to other countries with different surveillance and testing policies.

scholarly journals Evaluating new evidence in the early dynamics of the novel coronavirus COVID-19 outbreak in Wuhan, China with real time domestic traffic and potential asymptomatic transmissions

2020 ◽  
Author(s):  
Can Zhou
Keyword(s):  
Real Time ◽  
Early Stage ◽  
Empirical Support ◽  
Credible Interval ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Sources Of Information ◽  
Alternative Sources ◽  
Novel Coronavirus

AbstractThe novel coronavirus (COVID-19), first detected in Wuhan, China in December 2019, has spread to 28 countries/regions with over 43,000 confirmed cases. Much about this outbreak is still unknown. At this early stage of the epidemic, it is important to investigate alternative sources of information to understand its dynamics and spread. With updated real time domestic traffic, this study aims to integrate recent evidence of international evacuees extracted from Wuhan between Jan. 29 and Feb. 2, 2020 to infer the dynamics of the COVD-19 outbreak in Wuhan. In addition, a modified SEIR model was used to evaluate the empirical support for the presence of asymptomatic transmissions. Based on the data examined, this study found little evidence for the presence of asymptomatic transmissions. However, it is still too early to rule out its presence conclusively due to sample size and other limitations. The updated basic reproductive number was found to be 2.12 on average with a 95% credible interval of [2.04, 2.18]. It is smaller than previous estimates probably because the new estimate factors in the social and non-pharmaceutical mitigation implemented in Wuhan through the evacuee dataset. Detailed predictions of infected individuals exported both domestically and internationally were produced. The estimated case confirmation rate has been low but has increased steadily to 23.37% on average. The findings of this study depend on the validity of the underlying assumptions, and continuing work is needed, especially in monitoring the current infection status of Wuhan residents.

scholarly journals Characterizing the transmission and identifying the control strategy for COVID-19 through epidemiological modeling

2020 ◽  
Author(s):  
Huijuan Zhou ◽  
Chengbin Xue ◽  
Guannan Gao ◽  
Lauren Lawless ◽  
Linglin Xie ◽  
...  
Keyword(s):  
Predictive Modeling ◽  
Control Strategies ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Epidemiological Analysis ◽  
Government Action ◽  
Epidemiological Modeling ◽  
Novel Coronavirus ◽  
Fast Transmission

ABSTRACTThe outbreak of the novel coronavirus disease, COVID-19, originating from Wuhan, China in early December, has infected more than 70,000 people in China and other countries and has caused more than 2,000 deaths. As the disease continues to spread, the biomedical society urgently began identifying effective approaches to prevent further outbreaks. Through rigorous epidemiological analysis, we characterized the fast transmission of COVID-19 with a basic reproductive number 5.6 and proved a sole zoonotic source to originate in Wuhan. No changes in transmission have been noted across generations. By evaluating different control strategies through predictive modeling and Monte carlo simulations, a comprehensive quarantine in hospitals and quarantine stations has been found to be the most effective approach. Government action to immediately enforce this quarantine is highly recommended.

scholarly journals Early epidemiological assessment of the transmission potential and virulence of coronavirus disease 2019 (COVID-19) in Wuhan City: China, January-February, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Katsushi Kagaya ◽  
Gerardo Chowell
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Public Health Intervention ◽  
Ecological Modelling ◽  
The Novel ◽  
Wuhan City ◽  
Transmission Potential ◽  
The World ◽  
Novel Coronavirus ◽  
Epidemiological Parameters

AbstractBackgroundSince the first cluster of cases was identified in Wuhan City, China, in December, 2019, coronavirus disease 2019 (COVID-19) rapidly spread around the world. Despite the scarcity of publicly available data, scientists around the world have made strides in estimating the magnitude of the epidemic, the basic reproduction number, and transmission patterns. Accumulating evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which highlights the need to reassess the transmission potential of this emerging disease. In this study, we derive estimates of the transmissibility and virulence of COVID-19 in Wuhan City, China, by reconstructing the underlying transmission dynamics using multiple data sources.MethodsWe employ statistical methods and publicly available epidemiological datasets to jointly derive estimates of transmissibility and severity associated with the novel coronavirus. For this purpose, the daily series of laboratory–confirmed COVID-19 cases and deaths in Wuhan City together with epidemiological data of Japanese repatriated from Wuhan City on board government–chartered flights were integrated into our analysis.ResultsOur posterior estimates of basic reproduction number (R) in Wuhan City, China in 2019–2020 reached values at 3.49 (95%CrI: 3.39–3.62) with a mean serial interval of 6.0 days, and the enhanced public health intervention after January 23rd in 2020 was associated with a significantly reduced R at 0.84 (95%CrI: 0.81–0.88), with the total number of infections (i.e. cumulative infections) estimated at 1906634 (95%CrI: 1373500–2651124) in Wuhan City, elevating the overall proportion of infected individuals to 19.1% (95%CrI: 13.5–26.6%). We also estimated the most recent crude infection fatality ratio (IFR) and time–delay adjusted IFR at 0.04% (95% CrI: 0.03%–0.06%) and 0.12% (95%CrI: 0.08–0.17%), respectively, estimates that are several orders of magnitude smaller than the crude CFR estimated at 4.06%ConclusionsWe have estimated key epidemiological parameters of the transmissibility and virulence of COVID-19 in Wuhan, China during January-February, 2020 using an ecological modelling approach. The power of this approach lies in the ability to infer epidemiological parameters with quantified uncertainty from partial observations collected by surveillance systems.

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 Consideration of the Management of Pediatric Fever Clinics During the Novel Coronavirus Pneumonia Outbreak

2020 ◽  
pp. 1-7
Author(s):  
Hui Ding ◽  
Zhaoling Shi ◽  
Zhen Ruan ◽  
Xiaoning Cheng ◽  
Ruying Li ◽  
...  
Keyword(s):  
Medical Staff ◽  
Prevention And Control ◽  
Cross Infection ◽  
The Novel ◽  
Wuhan City ◽  
Control Programs ◽  
Treatment And Prevention ◽  
Epidemic Period ◽  
Novel Coronavirus ◽  
And Control

ABSTRACT Since the outbreak of 2019 novel coronavirus (2019-nCoV) infection in Wuhan City, China, pediatric cases have gradually increased. It is very important to prevent cross-infection in pediatric fever clinics, to identify children with fever in pediatric fever clinics, and to strengthen the management of pediatric fever clinics. According to prevention and control programs, we propose the guidance on the management of pediatric fever clinics during the nCoV pneumonia epidemic period, which outlines in detail how to optimize processes, prevent cross-infection, provide health protection, and prevent disinfection of medical staff. The present consideration statement summarizes current strategies on the pre-diagnosis, triage, diagnosis, treatment, and prevention of 2019-nCoV infection, which provides practical suggestions on strengthening the management of pediatric fever clinics during the nCoV pneumonia epidemic period.

Evaluation of stability and inactivation methods of SARS-CoV-2 in context of laboratory settings

2020 ◽  
Author(s):  
Sandra Westhaus ◽  
Marek Widera ◽  
Holger F. Rabenau ◽  
Sebastian Hoehl ◽  
Denisa Bojkova ◽  
...  
Keyword(s):  
Culture Media ◽  
Heat Inactivation ◽  
The Novel ◽  
Safety Issues ◽  
Rapid Spread ◽  
Level 3 ◽  
Global Concern ◽  
The Stability ◽  
Novel Coronavirus ◽  
Uv C

SummaryThe novel coronavirus SARS-CoV-2 is the causative agent of the acute respiratory disease COVID-19, which has become a global concern due to its rapid spread. Laboratory work with SARS-CoV-2 in a laboratory setting was rated to biosafety level 3 (BSL-3) biocontainment level. However, certain research applications in particular in molecular biology require incomplete denaturation of the proteins, which might cause safety issues handling contaminated samples. In particular, it is critical to provide proof of inactivation before samples can be removed from the BSL-3.In this study, the stability of the virus in cell culture media at 4°C and on touch panel surfaces used in laboratory environment was analyzed. In addition, we evaluated common lysis buffers that are used in molecular biological laboratories for their ability to inactivate SARS-CoV-2. We have found that guanidine thiocyanate and most of the tested detergent containing lysis buffers were effective in inactivation of SARS-CoV-2, however, the M-PER lysis buffer containing a proprietary detergent failed to inactivate SARS-CoV-2. Furthermore, we compared chemical and non-chemical inactivation methods including ethanol, acetone-methanol mixture, PFA, UV-C light, and heat inactivation.In conclusion, careful evaluation of the used inactivation methods are required and additional inactivation steps are necessary before removal of lysed viral samples from BSL-3.

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