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Serial interval of novel coronavirus (COVID-19) infections.

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TLDR
The serial interval of COVID-19 is close to or shorter than its median incubation period, indicating that a substantial proportion of secondary transmission may occur prior to illness onset and that calculations made using the SARS serial interval may introduce bias.
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This article is published in International Journal of Infectious Diseases.The article was published on 2020-03-04 and is currently open access. It has received 963 citations till now. The article focuses on the topics: Serial interval & Credible interval.

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Citations
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Daily-activity-dependency of effective reproduction number in COVID-19 pandemic: direct modelling from GPS data

TL;DR: In this paper , the authors developed a model that enables quantitative estimations of the infection risk for individual places and activities by using smartphone GPS data for the Tokyo metropolitan area, and calculated the effective reproduction number from the number of infectious social contacts defined by the square of the population density at each location.
Journal ArticleDOI

Epidemiologic Parameters for COVID-19: A Systematic Review and Meta-Analysis

TL;DR: In this paper , the authors aimed to estimate the epidemiologic parameters of the COVID-19 pandemic for clinical and epidemiological help, and selected 76 articles based on epidemiological parameters, including basic reproduction number, serial interval, incubation period, doubling time, growth rate, case-fatality rate and onset of symptom to hospitalization as eligibility criteria.
Posted Content

Estimation of the effective reproduction number for SARS-CoV-2 infection during the first epidemic wave in the metropolitan area of Athens, Greece

TL;DR: In this article, the authors provided estimations for the effective reproduction number (R_e) for the greater metropolitan area of Athens, Greece during the first wave of the pandemic (February 26-May 15, 2020).
Posted ContentDOI

Synchronization in Epidemic Growth and the Impossibility of Selective Containment

TL;DR: A simple model of epidemic dynamics separating the population into two groups, namely a low-risk group and a high- Risk group, finds that maintaining a slower epidemic growth behavior for the high- risk group is unstable against any finite coupling between the two groups.
Book ChapterDOI

Comparative Analysis of Machine Learning Algorithms with Ensemble Techniques and Forecasting COVID-19 Cases in India

TL;DR: In this paper , the authors used bagging, boosting, stacking and voting with four distinct machine learning algorithms linear regression, sequential minimal optimizer for regression, multilayer perceptron and Gaussian process to predict confirmed cases, recovered cases and deceased cases.
References
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Journal ArticleDOI

Transmission Dynamics and Control of Severe Acute Respiratory Syndrome

TL;DR: It is estimated that a single infectious case of SARS will infect about three secondary cases in a population that has not yet instituted control measures, and public-health efforts to reduce transmission are expected to have a substantial impact on reducing the size of the epidemic.
Journal ArticleDOI

Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: A statistical analysis of publicly available case data

TL;DR: The incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution and it is recommended that the length of quarantine should be at least 14 days.
Journal ArticleDOI

Factors that make an infectious disease outbreak controllable.

TL;DR: It is concluded that severe acute respiratory syndrome and smallpox are easier to control using these simple public health measures and should be a priority during an outbreak of a novel infectious agent.
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What is the mutation period for Covid 19?

The serial interval of COVID-19 is close to or shorter than its median incubation period.