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Coronavir.org

Site de veille et d'information sur le nouveau coronavirus SARS-COV-2 et la maladie associée COVID-19

Actualités et recherches en cours

With interest, we read the recommendation on the management of pregnant women with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by Guillaume Favre and colleagues.1 Some of the recommendations made in the flowsheet of their Correspondence have long-term consequences (eg, termination of pregnancy, no breastfeeding) of an unforeseeable extent, are harmful when applied to the general population (eg, early cord clamping in ex...

We are grateful for the concerns of Manuel Schmidt and colleagues about our previous guidelines1 for pregnant women with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. At the time we developed the algorithm (February, 2020), there were no data regarding potential vertical transmission from infected mothers and outcomes in newborns. To date, there has been no evidence of vertical transmission of coronavirus disea...

The new coronavirus known as COVID-19 is rapidly spreading since December 2019. Without any vaccination or medicine, the means of controlling it are limited to quarantine and social distancing. Here we study the spatio-temporal propagation of the COVID-19 virus in China and compare it to other global locations. Our results suggest that the disease propagation is highly related to population migration from Hubei resembling a L\'{e}vy flight whic...

Motivated with various responses of world governments to COVID-19, here we develop a toy model of the dependence epidemics spreading on the availability of tests for disease. Our model, that we call SUDR+K, is based on usual SIR model, but it splits the total fraction of infected individuals into two components: those that are undetected and those that are detected through tests. Moreover, we assume that available tests increase at a constant r...

The sudden spread of Covid-19 outside China has pushed on March 11 the World Health Organization to acknowledge the ongoing outbreak as a pandemic. It is crucial in this phase to understand what should countries which presently lag behind in the spread of the infection learn from countries where the infection spread earlier. The choice of this work is to prefer timeliness to comprehensiveness. By adopting a purely empirical approach, we will li...

A model of reactive social distancing in epidemics is proposed, in which the infection rate changes with the number infected. The final-size equation for the total number that the epidemic will infect can be derived analytically, as can the peak infection proportion. This model could assist planners during for example the COVID-19 pandemic. ...

Motivated with various responses of world governments to COVID-19, here we develop a toy model of the dependence epidemics spreading on the availability of tests for disease. Our model, that we call SUDR+K, is based on usual SIR model, but it splits the total fraction of infected individuals into two components: those that are undetected and those that are detected through tests. Moreover, we assume that available tests increase at a constant r...

The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. Recent outbreak of novel coronavirus infected and killed thousands of people in the world. Rapid methods in finding peptides or antibody sequences that can inhibit the viral epitopes of COVID-19 will save the life of thousands. In this paper, we devised a machine learning (ML) model to predict the possible inh...

In a move described as unprecedented in public health history, starting 24 January 2020, China imposed quarantine and isolation restrictions in Wuhan, a city of more than 10 million people. This raised the question: is mass quarantine and isolation effective as a social tool in addition to its scientific use as a medical tool? In an effort to address this question, using a epidemiological model driven approach augmented by machine learning, we ...

We present a data-driven machine learning analysis of COVID-19 from its \emph{early} infection dynamics, with the goal of extracting actionable public health insights. We focus on the transmission dynamics in the USA starting from the first confirmed infection on January 21 2020. We find that COVID-19 has a strong infectious force if left unchecked, with a doubling time of under 3 days. However it is not particularly virulent. Our methods may b...

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