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Modelling Excess Mortality in Covid-19-Like Epidemics

We develop an agent-based model to assess the cumulative number of deaths during hypothetical Covid-19-like epidemics for various non-pharmaceutical intervention strategies. The model simulates three interrelated stochastic processes: epidemic spreading, availability of respiratory ventilators and c...

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Autor principal: Burda, Zdzislaw
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712842/
https://www.ncbi.nlm.nih.gov/pubmed/33287004
http://dx.doi.org/10.3390/e22111236
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author Burda, Zdzislaw
author_facet Burda, Zdzislaw
author_sort Burda, Zdzislaw
collection PubMed
description We develop an agent-based model to assess the cumulative number of deaths during hypothetical Covid-19-like epidemics for various non-pharmaceutical intervention strategies. The model simulates three interrelated stochastic processes: epidemic spreading, availability of respiratory ventilators and changes in death statistics. We consider local and non-local modes of disease transmission. The first simulates transmission through social contacts in the vicinity of the place of residence while the second through social contacts in public places: schools, hospitals, airports, etc., where many people meet, who live in remote geographic locations. Epidemic spreading is modelled as a discrete-time stochastic process on random geometric networks. We use the Monte–Carlo method in the simulations. The following assumptions are made. The basic reproduction number is [Formula: see text] and the infectious period lasts approximately ten days. Infections lead to severe acute respiratory syndrome in about one percent of cases, which are likely to lead to respiratory default and death, unless the patient receives an appropriate medical treatment. The healthcare system capacity is simulated by the availability of respiratory ventilators or intensive care beds. Some parameters of the model, like mortality rates or the number of respiratory ventilators per [Formula: see text] inhabitants, are chosen to simulate the real values for the USA and Poland. In the simulations we compare ‘do-nothing’ strategy with mitigation strategies based on social distancing and reducing social mixing. We study epidemics in the pre-vacine era, where immunity is obtained only by infection. The model applies only to epidemics for which reinfections are rare and can be neglected. The results of the simulations show that strategies that slow the development of an epidemic too much in the early stages do not significantly reduce the overall number of deaths in the long term, but increase the duration of the epidemic. In particular, a hybrid strategy where lockdown is held for some time and is then completely released, is inefficient.
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spelling pubmed-77128422021-02-24 Modelling Excess Mortality in Covid-19-Like Epidemics Burda, Zdzislaw Entropy (Basel) Article We develop an agent-based model to assess the cumulative number of deaths during hypothetical Covid-19-like epidemics for various non-pharmaceutical intervention strategies. The model simulates three interrelated stochastic processes: epidemic spreading, availability of respiratory ventilators and changes in death statistics. We consider local and non-local modes of disease transmission. The first simulates transmission through social contacts in the vicinity of the place of residence while the second through social contacts in public places: schools, hospitals, airports, etc., where many people meet, who live in remote geographic locations. Epidemic spreading is modelled as a discrete-time stochastic process on random geometric networks. We use the Monte–Carlo method in the simulations. The following assumptions are made. The basic reproduction number is [Formula: see text] and the infectious period lasts approximately ten days. Infections lead to severe acute respiratory syndrome in about one percent of cases, which are likely to lead to respiratory default and death, unless the patient receives an appropriate medical treatment. The healthcare system capacity is simulated by the availability of respiratory ventilators or intensive care beds. Some parameters of the model, like mortality rates or the number of respiratory ventilators per [Formula: see text] inhabitants, are chosen to simulate the real values for the USA and Poland. In the simulations we compare ‘do-nothing’ strategy with mitigation strategies based on social distancing and reducing social mixing. We study epidemics in the pre-vacine era, where immunity is obtained only by infection. The model applies only to epidemics for which reinfections are rare and can be neglected. The results of the simulations show that strategies that slow the development of an epidemic too much in the early stages do not significantly reduce the overall number of deaths in the long term, but increase the duration of the epidemic. In particular, a hybrid strategy where lockdown is held for some time and is then completely released, is inefficient. MDPI 2020-10-30 /pmc/articles/PMC7712842/ /pubmed/33287004 http://dx.doi.org/10.3390/e22111236 Text en © 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Burda, Zdzislaw
Modelling Excess Mortality in Covid-19-Like Epidemics
title Modelling Excess Mortality in Covid-19-Like Epidemics
title_full Modelling Excess Mortality in Covid-19-Like Epidemics
title_fullStr Modelling Excess Mortality in Covid-19-Like Epidemics
title_full_unstemmed Modelling Excess Mortality in Covid-19-Like Epidemics
title_short Modelling Excess Mortality in Covid-19-Like Epidemics
title_sort modelling excess mortality in covid-19-like epidemics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712842/
https://www.ncbi.nlm.nih.gov/pubmed/33287004
http://dx.doi.org/10.3390/e22111236
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