Epidemic Growth and Reproduction Number for the Novel Coronavirus Disease (COVID-19) Outbreak on the Diamond Princess Cruise Ship from January 20 to February 19, 2020: A preliminary Data-Driven Analysis

2020 ◽  
Author(s):  
Shi Zhao ◽  
Peihua Cao ◽  
Daozhou Gao ◽  
Zian Zhuang ◽  
Marc KC Chong ◽  
...  
Keyword(s):  
Preliminary Data ◽  
Reproduction Number ◽  
Data Driven ◽  
The Novel ◽  
Cruise Ship ◽  
Novel Coronavirus ◽  
Growth And Reproduction

scholarly journals Purely data-driven exploration of COVID-19 pandemic after three months of the outbreak

2020 ◽  
Author(s):  
Shirali Kadyrov ◽  
Hayot Berk Saydaliev
Keyword(s):  
Reproduction Number ◽  
Statistical Tests ◽  
Disease Outbreak ◽  
Data Driven ◽  
The Novel ◽  
Epidemic Modeling ◽  
Death Rates ◽  
Sir Epidemic ◽  
Novel Coronavirus ◽  
Epidemiological Characteristics

AbstractIt has been three months since the novel coronavirus (COVID-19) pandemic outbreak. Many research studies were carried to understand its epidemiological characteristics in the early phase of the disease outbreak. The current study is yet another contribution to better understand the disease properties by parameter estimation of mathematical SIR epidemic modeling. The authors use Johns Hopkins University’s dataset to estimate the basic reproduction number of COVID-19 for representative countries (Japan, Germany, Italy, France, and Netherlands) selected using cluster analysis. As a by-product, the authors estimate transmission, recovery, and death rates for each selected country and carry statistical tests to see if there are any significant differences.

scholarly journals Age-dependence of mortality from novel coronavirus disease (COVID-19) in highly exposed populations: New York transit workers and residents and Diamond Princess passengers.

2020 ◽  
Author(s):  
Christopher T Leffler ◽  
Matthew C Hogan
Keyword(s):  
New York ◽  
New York City ◽  
New York State ◽  
Age Groups ◽  
The Novel ◽  
Cruise Ship ◽  
Age Dependence ◽  
York State ◽  
Novel Coronavirus ◽  
Available Information

Background. Populations heavily exposed to the novel coronavirus provide an opportunity to estimate the mortality from COVID-19 in different age groups. Methods. The mortality reported by May 13 from COVID-19 among Diamond Princess cruise ship passengers, and New York residents and Metropolitan Transit Authority (MTA) workers was estimated based on publicly available information. Results. The mortality among children (age 0 to 17 yrs) in New York City was 1 in 172,692. The mortality in New York state was 1 in 322,217 for ages 10-19 yrs., and 1 in 36,725 for ages 20-29 yrs. The mortality among New York transit workers was estimated to be 1 in 7,329 for ages 30-39 years; 1 in 1,075 for ages 40-49 yrs.; 1 in 343 for ages 50-59 yrs.; and 1 in 178 for ages 60-69 yrs. Among Diamond Princess passengers, the mortality was estimated to be 1 in 145 for ages 70-79, and 1 in 54 for ages 80-89. Conclusions: Mortality among populations exposed to the novel coronavirus increases with age, ranging from about 1 in 170,000 below the age of 18 years, to 1 in 54 above the age of 80 years.

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.

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 SARS2020: an integrated platform for identification of novel coronavirus by a consensus sequence-function model

2020 ◽  
Author(s):  
Dachuan Zhang ◽  
Tong Zhang ◽  
Sheng Liu ◽  
Dandan Sun ◽  
Shaozhen Ding ◽  
...  
Keyword(s):  
Biological Function ◽  
Consensus Sequence ◽  
Rapid Identification ◽  
Data Driven ◽  
Supplementary Information ◽  
Respiratory Syndrome Virus ◽  
The Novel ◽  
Function Model ◽  
Catalytic Function ◽  
Novel Coronavirus

Abstract Motivation The 2019 novel coronavirus outbreak has significantly affected global health and society. Thus, predicting biological function from pathogen sequence is crucial and urgently needed. However, little work has been conducted to identify viruses by the enzymes that they encode, and which are key to pathogen propagation. Results We built a comprehensive scientific resource, SARS2020, which integrates coronavirus-related research, genomic sequences and results of anti-viral drug trials. In addition, we built a consensus sequence-catalytic function model from which we identified the novel coronavirus as encoding the same proteinase as the severe acute respiratory syndrome virus. This data-driven sequence-based strategy will enable rapid identification of agents responsible for future epidemics. Availabilityand implementation SARS2020 is available at http://design.rxnfinder.org/sars2020/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Hybrid Method for Simulation of a Fractional COVID-19 Model with Real Case Application

Axioms ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 290
Author(s):  
Anwarud Din ◽  
Amir Khan ◽  
Anwar Zeb ◽  
Moulay Rchid Sidi Ammi ◽  
Mouhcine Tilioua ◽  
...  
Keyword(s):  
Hybrid Method ◽  
Reproduction Number ◽  
Real Data ◽  
The Novel ◽  
Order Analysis ◽  
The Laplace Transform ◽  
Case Application ◽  
Novel Coronavirus ◽  
Available Information ◽  
Fractional Orders

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9 April to 2 June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders.

scholarly journals Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Gerardo Chowell
Keyword(s):  
Mathematical Modeling ◽  
Time Series ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Threshold ◽  
Transmission Potential ◽  
Incidence Data ◽  
The Mean ◽  
Novel Coronavirus

AbstractAn outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ∼11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

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