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An artificially simulated outbreak of a respiratory infectious disease

BACKGROUND: Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a...

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Autores principales: Guo, Zuiyuan, Xu, Shuang, Tong, Libo, Dai, Botao, Liu, Yuandong, Xiao, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6993344/
https://www.ncbi.nlm.nih.gov/pubmed/32000737
http://dx.doi.org/10.1186/s12889-020-8243-6
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author Guo, Zuiyuan
Xu, Shuang
Tong, Libo
Dai, Botao
Liu, Yuandong
Xiao, Dan
author_facet Guo, Zuiyuan
Xu, Shuang
Tong, Libo
Dai, Botao
Liu, Yuandong
Xiao, Dan
author_sort Guo, Zuiyuan
collection PubMed
description BACKGROUND: Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a stochastic model to simulate an outbreak of a respiratory infectious disease at a military camp. This model fits the general pattern of disease transmission and further enriches theories on the transmission dynamics of infectious diseases. METHODS: We established an enclosed system of 500 people exposed to adenovirus type 7 (ADV 7) in a military camp. During the infection period, the patients transmitted the virus randomly to susceptible people. The spread of the epidemic under militarized management mode was simulated using a computer model named “the random collision model”, and the effects of factors such as the basic reproductive number (R(0)), time of isolation of the patients (TOI), interval between onset and isolation (IOI), and immunization rates (IR) on the developmental trend of the epidemic were quantitatively analysed. RESULTS: Once the R(0) exceeded 1.5, the median attack rate increased sharply; when R(0) = 3, with a delay in the TOI, the attack rate increased gradually and eventually remained stable. When the IOI exceeded 2.3 days, the median attack rate also increased dramatically. When the IR exceeded 0.5, the median attack rate approached zero. The median generation time was 8.26 days, (95% confidence interval [CI]: 7.84–8.69 days). The partial rank correlation coefficients between the attack rate of the epidemic and R(0), TOI, IOI, and IR were 0.61, 0.17, 0.45, and − 0.27, respectively. CONCLUSIONS: The random collision model not only simulates how an epidemic spreads with superior precision but also allows greater flexibility in setting the activities of the exposure population and different types of infectious diseases, which is conducive to furthering exploration of the epidemiological characteristics of epidemic outbreaks.
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spelling pubmed-69933442020-02-04 An artificially simulated outbreak of a respiratory infectious disease Guo, Zuiyuan Xu, Shuang Tong, Libo Dai, Botao Liu, Yuandong Xiao, Dan BMC Public Health Research Article BACKGROUND: Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a stochastic model to simulate an outbreak of a respiratory infectious disease at a military camp. This model fits the general pattern of disease transmission and further enriches theories on the transmission dynamics of infectious diseases. METHODS: We established an enclosed system of 500 people exposed to adenovirus type 7 (ADV 7) in a military camp. During the infection period, the patients transmitted the virus randomly to susceptible people. The spread of the epidemic under militarized management mode was simulated using a computer model named “the random collision model”, and the effects of factors such as the basic reproductive number (R(0)), time of isolation of the patients (TOI), interval between onset and isolation (IOI), and immunization rates (IR) on the developmental trend of the epidemic were quantitatively analysed. RESULTS: Once the R(0) exceeded 1.5, the median attack rate increased sharply; when R(0) = 3, with a delay in the TOI, the attack rate increased gradually and eventually remained stable. When the IOI exceeded 2.3 days, the median attack rate also increased dramatically. When the IR exceeded 0.5, the median attack rate approached zero. The median generation time was 8.26 days, (95% confidence interval [CI]: 7.84–8.69 days). The partial rank correlation coefficients between the attack rate of the epidemic and R(0), TOI, IOI, and IR were 0.61, 0.17, 0.45, and − 0.27, respectively. CONCLUSIONS: The random collision model not only simulates how an epidemic spreads with superior precision but also allows greater flexibility in setting the activities of the exposure population and different types of infectious diseases, which is conducive to furthering exploration of the epidemiological characteristics of epidemic outbreaks. BioMed Central 2020-01-30 /pmc/articles/PMC6993344/ /pubmed/32000737 http://dx.doi.org/10.1186/s12889-020-8243-6 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Guo, Zuiyuan
Xu, Shuang
Tong, Libo
Dai, Botao
Liu, Yuandong
Xiao, Dan
An artificially simulated outbreak of a respiratory infectious disease
title An artificially simulated outbreak of a respiratory infectious disease
title_full An artificially simulated outbreak of a respiratory infectious disease
title_fullStr An artificially simulated outbreak of a respiratory infectious disease
title_full_unstemmed An artificially simulated outbreak of a respiratory infectious disease
title_short An artificially simulated outbreak of a respiratory infectious disease
title_sort artificially simulated outbreak of a respiratory infectious disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6993344/
https://www.ncbi.nlm.nih.gov/pubmed/32000737
http://dx.doi.org/10.1186/s12889-020-8243-6
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