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Research article
An artificially simulated outbreak of a respiratory infectious disease
Yuandong Liu
Corresponding Author
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View the published version at BMC Public Health.
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.
Keywords
respiratory infectious diseases; adenovirus type 7; outbreak; model; prevention; control
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CURRENT STATUS: Published
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Posted 20 Jan, 2020
Published
On 30 Jan, 2020
No community comments so far
Editorial decision: Accept
On 19 Jan, 2020
Editor assigned
On 17 Jan, 2020
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On 16 Jan, 2020
Editor invited
On 16 Jan, 2020
No comments provided
Submission checks complete
On 15 Jan, 2020
Editorial decision: Minor revision
On 15 Jan, 2020
No comments provided
Submission checks complete
On 10 Jan, 2020
Editorial decision: Minor revision
On 09 Jan, 2020
No comments provided
Editorial decision: Minor revision
On 07 Jan, 2020
Reviewers invited
Invitations sent on 23 Dec, 2019
Editor assigned
On 23 Dec, 2019
Submission checks complete
On 22 Dec, 2019
Editor invited
On 22 Dec, 2019
No comments provided
Reviewer #1 agreed
On 12 Nov, 2019
Review #1 received
Received 12 Nov, 2019
Editorial decision: Minor revision
On 12 Nov, 2019
Reviewers invited
Invitations sent on 06 Nov, 2019
Editor assigned
On 05 Nov, 2019
Submission checks complete
On 04 Nov, 2019
Editor invited
On 04 Nov, 2019
No comments provided
Review #2 received
Received 29 Oct, 2019
Editorial decision: Minor revision
On 29 Oct, 2019
Review #1 received
Received 20 Oct, 2019
Reviewer #2 agreed
On 17 Oct, 2019
Reviewers invited
Invitations sent on 16 Oct, 2019
Reviewer #1 agreed
On 16 Oct, 2019
Editor assigned
On 15 Oct, 2019
Submission checks complete
On 14 Oct, 2019
Editor invited
On 14 Oct, 2019
No comments provided
Review #1 received
Received 25 Sep, 2019
Editorial decision: Major revision
On 25 Sep, 2019
Review #2 received
Received 23 Sep, 2019
Reviewer #2 agreed
On 19 Sep, 2019
Reviewer #1 agreed
On 17 Sep, 2019
Reviewers invited
Invitations sent on 06 Sep, 2019
Editor assigned
On 05 Sep, 2019
Submission checks complete
On 05 Sep, 2019
Editor invited
On 05 Sep, 2019
First submitted
On 26 Aug, 2019
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This preprint is under consideration at BMC Public Health. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
An artificially simulated outbreak of a respiratory infectious disease
Yuandong Liu
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 7
Posted 20 Jan, 2020
Published
On 30 Jan, 2020
No community comments so far
Editorial decision: Accept
On 19 Jan, 2020
Editor assigned
On 17 Jan, 2020
Submission checks complete
On 16 Jan, 2020
Editor invited
On 16 Jan, 2020
No comments provided
Submission checks complete
On 15 Jan, 2020
Editorial decision: Minor revision
On 15 Jan, 2020
No comments provided
Submission checks complete
On 10 Jan, 2020
Editorial decision: Minor revision
On 09 Jan, 2020
No comments provided
Editorial decision: Minor revision
On 07 Jan, 2020
Reviewers invited
Invitations sent on 23 Dec, 2019
Editor assigned
On 23 Dec, 2019
Submission checks complete
On 22 Dec, 2019
Editor invited
On 22 Dec, 2019
No comments provided
Reviewer #1 agreed
On 12 Nov, 2019
Review #1 received
Received 12 Nov, 2019
Editorial decision: Minor revision
On 12 Nov, 2019
Reviewers invited
Invitations sent on 06 Nov, 2019
Editor assigned
On 05 Nov, 2019
Submission checks complete
On 04 Nov, 2019
Editor invited
On 04 Nov, 2019
No comments provided
Review #2 received
Received 29 Oct, 2019
Editorial decision: Minor revision
On 29 Oct, 2019
Review #1 received
Received 20 Oct, 2019
Reviewer #2 agreed
On 17 Oct, 2019
Reviewers invited
Invitations sent on 16 Oct, 2019
Reviewer #1 agreed
On 16 Oct, 2019
Editor assigned
On 15 Oct, 2019
Submission checks complete
On 14 Oct, 2019
Editor invited
On 14 Oct, 2019
No comments provided
Review #1 received
Received 25 Sep, 2019
Editorial decision: Major revision
On 25 Sep, 2019
Review #2 received
Received 23 Sep, 2019
Reviewer #2 agreed
On 19 Sep, 2019
Reviewer #1 agreed
On 17 Sep, 2019
Reviewers invited
Invitations sent on 06 Sep, 2019
Editor assigned
On 05 Sep, 2019
Submission checks complete
On 05 Sep, 2019
Editor invited
On 05 Sep, 2019
First submitted
On 26 Aug, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Public Health.
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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5