A simple SIR model with a large set of asymptomatic infectives

@article{Gaeta2020ASS,
  title={A simple SIR model with a large set of asymptomatic infectives},
  author={Giuseppe Lucio Gaeta},
  journal={Mathematics in Engineering},
  year={2020},
  url={https://api.semanticscholar.org/CorpusID:213003944}
}
A SIR-type model taking into account the presence of asymptomatic, or however undetected, infective, and the substantially long time these spend being infective and not isolated is developed and applied to the COVID-19 epidemics in Italy.
[PDF] Semantic Reader
81 Citations
Highly Influential Citations
12
Background Citations
33
Methods Citations
12
Results Citations
8

Figures and Tables from this paper

81 Citations

Understanding COVID-19 nonlinear multi-scale dynamic spreading in Italy

A logistic regression is employed to capture the evolution of the total positive cases in each region and throughout Italy, and an enhanced version of a SIR-type model is tuned to fit the different territorial epidemic dynamics via a differential evolution algorithm.

How long does a lockdown need to be

It is argued that a strategy based uniquely on social distancing requires to maintain the relative measures for a very long time, while a more articulate strategy, which also uses early detection and prompt isolation, can be both more efficient on reducing the epidemic peak and allow to relax the social Distancing measures after a much shorter time.

How to reduce epidemic peaks keeping under control the time-span of the epidemic

Measuring the impact of social-distancing, testing, and undetected asymptomatic cases on the diffusion of COVID-19

This study proposes a new compartmental model—the SICUR model—which can address undetected asymptomatic cases and considers the three main drivers of the diffusion of COVID-19: the degree of social distancing, the speed of testing, and the detection rate of infected cases.

Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model with Varying Mitigation Measures and Transmission Rate

An Epidemiology-Informed Neural Network algorithm is introduced to learn the time-varying transmission rate for the COVID-19 pandemic in the presence of various mitigation scenarios.

Data-driven deep learning algorithms for time-varying infection rates of COVID-19 and mitigation measures

EINN algorithms are introduced to discover time-varying infection rates for the COVID-19 pandemic and the effectiveness of vaccination, a pharmaceutical mitigation measure, together with non-pharmaceutical mitigation measures on the daily reported infectives is demonstrated.

A data-driven epidemic model with social structure for understanding the COVID-19 infection on a heavily affected Italian province

The proposed research combines a new mathematical description of the spread of an infectious diseases which takes into account both age and average daily social contacts with a detailed analysis of the dataset of all traced infected individuals in the Province of Pavia to develop a data-driven model.

Predicting the evolution of the COVID-19 epidemic with the A-SIR model: Lombardy, Italy and São Paulo state, Brazil

Size and timescale of epidemics in the SIR framework

Simulation of Covid-19 epidemic evolution: are compartmental models really predictive?

A machine learning approach based on particle swarm optimization (PSO) is proposed to automatically identify the model parameters based on a training set of data of progressive increasing size, considering Lombardy in Italy as a case study to address the fundamental question whether a SIR epidemiological model could be able to provide reliable predictions on the epidemic evolution.
...

60 References

Social distancing versus early detection and contacts tracing in epidemic management

Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)

It is estimated that 86% of all infections were undocumented before the 23 January 2020 travel restrictions, which explains the rapid geographic spread of SARS-CoV-2 and indicates that containment of this virus will be particularly challenging.

Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

The results presented here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries.

Viral dynamics in asymptomatic patients with COVID-19

The disease-induced herd immunity level for Covid-19 is substantially lower than the classical herd immunity level

It is shown here that the disease-induced herd immunity level hD, after an outbreak has taken place in a country/region with a set of preventive measures put in place, is actually substantially smaller than hC.

Evidence Supporting Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 While Presymptomatic or Asymptomatic

SARS-CoV-2 transmission in the absence of symptoms reinforces the value of measures that prevent the spread of SARS- covirus 2 by infected persons who may not exhibit illness despite being infectious.

COVID-19: PCR screening of asymptomatic health-care workers at London hospital

Heterogeneous contact networks in COVID-19 spreading: the role of social deprivation

The predictions of hotspots are found to be in good agreement with those currently being identfied empirically as containment zones and provide a useful guide for identifying potential areas of concern.

Size and timescale of epidemics in the SIR framework

...