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相关论文: Inferring the COVID-19 infection curve in Italy

200 篇论文

The spread of COVID-19 during the initial phase of the first half of 2020 was curtailed to a larger or lesser extent through measures of social distancing imposed by most countries. In this work, we link directly, through machine learning…

种群与进化 · 定量生物学 2020-08-20 G. D. Barmparis , G. P. Tsironis

In this work, using a detailed dataset furnished by National Health Authorities concerning the Province of Pavia (Lombardy, Italy), we propose to determine the essential features of the ongoing COVID-19 pandemic in term of contact dynamics.…

种群与进化 · 定量生物学 2021-07-05 M. Zanella , C. Bardelli , G. Dimarco , S. Deandrea , P. Perotti , M. Azzi , S. Figini , G. Toscani

Detecting changes in COVID-19 disease transmission over time is a key indicator of epidemic growth.Near real-time monitoring of the pandemic growth is crucial for policy makers and public health officials who need to make informed decisions…

应用统计 · 统计学 2021-11-30 Luca Scrucca

The most important features to assess the severity of an epidemic are its size and its timescale. We discuss these features in a systematic way in the context of SIR and SIR-type models. We investigate in detail how the size and timescale…

种群与进化 · 定量生物学 2020-06-29 Mariano Cadoni , Giuseppe Gaeta

The infections and fatalities due to SARS-CoV-2 virus for cases specific to India have been studied using a deterministic susceptible-exposed-infected-recovered-dead (SEIRD) compartmental model. One of the most significant epidemiological…

种群与进化 · 定量生物学 2020-06-09 Vishwajeet Jha

In this paper, we study the effectiveness of the modelling approach on the pandemic due to the spreading of the novel COVID-19 disease and develop a susceptible-infected-removed (SIR) model that provides a theoretical framework to…

种群与进化 · 定量生物学 2020-08-26 Ian Cooper , Argha Mondal , Chris G. Antonopoulos

It is widely accepted that the number of reported cases during the first stages of the COVID-19 pandemic severely underestimates the number of actual cases. We leverage delay embedding theorems of Whitney and Takens and use Gaussian Process…

定量方法 · 定量生物学 2022-02-02 G. A. Kevrekidis , Z. Rapti , Y. Drossinos , P. G. Kevrekidis , M. A. Barmann , Q. Y. Chen , J. Cuevas-Maraver

The COVID-19 disease has forced countries to make a considerable collaborative effort between scientists and governments to provide indicators to suitable follow-up the pandemic's consequences. Mathematical modeling plays a crucial role in…

种群与进化 · 定量生物学 2020-12-29 Patricio Cumsille , Oscar Rojas-Díaz , Pablo Moisset de Espanés

We develop a minimalist compartmental model to study the impact of mobility restrictions in Italy during the Covid-19 outbreak. We show that an early lockdown shifts the epidemic in time, while that beyond a critical value of the lockdown…

Coronavirus disease (COVID-19) is a severe ongoing novel pandemic that has emerged in Wuhan, China, in December 2019. As of October 13, the outbreak has spread rapidly across the world, affecting over 38 million people, and causing over 1…

应用统计 · 统计学 2021-08-31 Gaetano Perone

We present an early version of a Susceptible-Exposed-Infected-Recovered-Deceased (SEIRD) mathematical model based on partial differential equations coupled with a heterogeneous diffusion model. The model describes the spatio-temporal spread…

During the COVID-19 pandemic, the behavioral response to reported case numbers changed drastically over time. While a few dozen cases were enough to trigger government-induced and voluntary contact reduction in early 2020, less than a year…

物理与社会 · 物理学 2023-09-27 Bastian Heinlein , Manlio De Domenico

Susceptible-Invective-Recovered (SIR) mathematical models are in high demand due to the COVID-19 pandemic. They are used in their standard formulation, or through the many variants, trying to fit and hopefully predict the number of new…

种群与进化 · 定量生物学 2020-05-19 Ben-Hur Francisco Cardoso , Sebastián Gonçalves

In this paper, we consider a discrete-time stochastic SIR model, where the transmission rate and the true number of infectious individuals are random and unobservable. An advantage of this model is that it permits us to account for random…

物理与社会 · 物理学 2024-01-30 Katia Colaneri , Camilla Damian , Rüdiger Frey

The advent of the COVID-19 pandemic has instigated unprecedented changes in many countries around the globe, putting a significant burden on the health sectors, affecting the macro economic conditions, and altering social interactions…

物理与社会 · 物理学 2020-07-23 Dmitry Gordeev , Philipp Singer , Marios Michailidis , Mathias Müller , SriSatish Ambati

In this paper we explore a time-depended SEIR model, in which the dynamics of the infection in four groups from a selected target group (population), divided according to the infection, are modeled by a system of nonlinear ordinary…

种群与进化 · 定量生物学 2021-03-31 Svetozar Margenov , Nedyu Popivanov , Iva Ugrinova , Stanislav Harizanov , Tsvetan Hristov

The time varying reproduction number R is a critical variable for situational awareness during infectious disease outbreaks, but delays between infection and reporting hinder its accurate estimation in real time. We propose a nowcasting…

One major bottleneck in the ongoing COVID-19 pandemic is the limited number of critical care beds. Due to the dynamic development of infections and the time lag between when patients are infected and when a proportion of them enters an…

种群与进化 · 定量生物学 2020-07-28 Matthias Ritter , Derek V. M. Ott , Friedemann Paul , John-Dylan Haynes , Kerstin Ritter

Different countries -- and sometimes different regions within the same countries -- have adopted different strategies in trying to contain the ongoing COVID-19 epidemic; these mix in variable parts social confinement, early detection and…

种群与进化 · 定量生物学 2020-07-17 Giuseppe Gaeta

The COVID-19 pandemic has plagued the world for months. The U.S. has taken measures to counter it. On a daily basis, newly confirmed cases have been reported. In the early days, these numbers showed an increasing trend. Recently, the…

物理与社会 · 物理学 2020-05-21 Xiubin Bruce Wang , Chaolun Ma