ArticleChaos, solitons, and fractals2020
A quantitative framework for exploring exit strategies from the COVID-19 lockdown.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- An algebraic formula, deep learning and a novel SEIR-type model for the COVID-19 pandemic.Royal Society open science · 2023Article
- An epidemiology-based model for the operational allocation of COVID-19 vaccines: A case study of Thailand.Computers & industrial engineering · 2022Article
- Determining an effective short term COVID-19 prediction model in ASEAN countries.Scientific reports · 2022Article
- Influence of state reopening policies in COVID-19 mortality.Scientific reports · 2022Article
- Analyzing the Impact of Demographic Variables on Spreading and Forecasting COVID-19.Journal of healthcare informatics research · 2022Article
- A model for the spread of infectious diseases compatible with case data.Proceedings. Mathematical, physical, and engineering sciences · 2021Article
- Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review.Sustainable cities and society · 2021Article
- Lockdown measures and their impact on single- and two-age-structured epidemic model for the COVID-19 outbreak in Mexico.Mathematical biosciences · 2021Article
- SARS-CoV-2: The Second Wave in Europe.Journal of medical Internet research · 2021Article
- Covid-19: predictive mathematical formulae for the number of deaths during lockdown and possible scenarios for the post-lockdown period.Proceedings. Mathematical, physical, and engineering sciences · 2021Article
- Easing COVID-19 lockdown measures while protecting the older restricts the deaths to the level of the full lockdown.Scientific reports · 2021Article
- Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021Article
- Social distancing versus early detection and contacts tracing in epidemic management.Chaos, solitons, and fractals · 2020Article
- Size and timescale of epidemics in the SIR framework.Physica D. Nonlinear phenomena · 2020Article
- Mathematical models and deep learning for predicting the number of individuals reported to be infected with SARS-CoV-2.Journal of the Royal Society, Interface · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Following the highly restrictive measures adopted by many countries for combating the current pandemic, the number of individuals infected by SARS-CoV-2 and the associated number of deaths steadily decreased. This fact, together with the impossibility of maintaining the lockdown indefinitely, raises the crucial question of whether it is possible to design an exit strategy based on quantitative analysis. Guided by rigorous mathematical results, we show that this is indeed possible: we present a robust numerical algorithm which can compute the cumulative number of deaths that will occur as a result of increasing the number of contacts by a given multiple, using as input only the most reliable of all data available during the lockdown, namely the cumulative number of deaths.
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