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Research article
amin golabpour
Shahrood University of Medical Sciences
Corresponding Author
ORCiD: https://orcid.org/0000-0001-7649-4033
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background The high prevalence COVID-19 has made it a new pandemic. Predicting the prevalence and incidence of this disease throughout the world is crucial to helping health professionals make key decisions about the disease.
Methods The coronavirus dataset contains information on COVID-19 cases in 252 geographic regions since January 22 and is updated daily. Data are included in the analysis as of March 29, 2020, with 17,136 records and 4 variables: latitude, longitude, date, and records. In order to design the prevalence pattern for each geographic area, the information of the region and its neighborhoods in the past two weeks, has been used. Then, using a Boosting Classification algorithm, a method was developed to predict the prevalence rate for the next two weeks.
Results The model was presented for three groups with a prevalence of less than 200, ranging from 200 to 1000, and more than 1000 cases, and the model error rates were 9.42, 17.08, and 12.26, respectively. In addition, more than 1 million new cases are expected to become infected in the next two weeks (March 30 - April 12). The number of new cases are expected to be more than 19,000 new cases in Africa, over 100,000 in Asia, over 14,000 in Australia, over 600,000 in Europe and over 300,000 in the Americas.
Conclusion The increase in the prevalence growth rate of the disease will also be in the Southern Hemisphere, and the United States will have the highest prevalence worldwide.
Keywords
COVID-19, Predicting, Data Mining, Prevalence
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View the published article at BMC Public Health.
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Review #3 received
Received 02 Feb, 2021
Reviewer #3 agreed
On 28 Jan, 2021
Review #1 received
Received 21 Jan, 2021
Reviewer #2 agreed
On 12 Jan, 2021
Review #2 received
Received 12 Jan, 2021
Reviewers invited
Invitations sent on 11 Jan, 2021
Reviewer #1 agreed
On 11 Jan, 2021
Editor assigned
On 05 Jan, 2021
Submission checks complete
On 05 Jan, 2021
Editor invited
On 05 Jan, 2021
No comments provided
Editorial decision: Major revision
On 03 Jan, 2021
Editor assigned
On 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Version 1
Posted 22 Apr, 2020
No comments provided
Editorial decision: Major revision
On 11 Nov, 2020
Review #3 received
Received 10 Nov, 2020
Reviewer #3 agreed
On 04 Sep, 2020
Review #2 received
Received 06 Aug, 2020
Reviewer #2 agreed
On 20 Jul, 2020
Review #1 received
Received 04 Jul, 2020
Reviewer #1 agreed
On 30 Apr, 2020
Reviewers invited
Invitations sent on 30 Apr, 2020
Editor assigned
On 17 Apr, 2020
Submission checks complete
On 16 Apr, 2020
Editor invited
On 16 Apr, 2020
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BMC Public Health.
This is a preprint, 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
amin golabpour
Shahrood University of Medical Sciences
Corresponding Author
ORCiD: https://orcid.org/0000-0001-7649-4033
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
View the published article at BMC Public Health.
No community comments so far
Review #3 received
Received 02 Feb, 2021
Reviewer #3 agreed
On 28 Jan, 2021
Review #1 received
Received 21 Jan, 2021
Reviewer #2 agreed
On 12 Jan, 2021
Review #2 received
Received 12 Jan, 2021
Reviewers invited
Invitations sent on 11 Jan, 2021
Reviewer #1 agreed
On 11 Jan, 2021
Editor assigned
On 05 Jan, 2021
Submission checks complete
On 05 Jan, 2021
Editor invited
On 05 Jan, 2021
No comments provided
Editorial decision: Major revision
On 03 Jan, 2021
Editor assigned
On 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Version 1
Posted 22 Apr, 2020
No comments provided
Editorial decision: Major revision
On 11 Nov, 2020
Review #3 received
Received 10 Nov, 2020
Reviewer #3 agreed
On 04 Sep, 2020
Review #2 received
Received 06 Aug, 2020
Reviewer #2 agreed
On 20 Jul, 2020
Review #1 received
Received 04 Jul, 2020
Reviewer #1 agreed
On 30 Apr, 2020
Reviewers invited
Invitations sent on 30 Apr, 2020
Editor assigned
On 17 Apr, 2020
Submission checks complete
On 16 Apr, 2020
Editor invited
On 16 Apr, 2020
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 article at BMC Public Health.
Background The high prevalence COVID-19 has made it a new pandemic. Predicting the prevalence and incidence of this disease throughout the world is crucial to helping health professionals make key decisions about the disease.
Methods The coronavirus dataset contains information on COVID-19 cases in 252 geographic regions since January 22 and is updated daily. Data are included in the analysis as of March 29, 2020, with 17,136 records and 4 variables: latitude, longitude, date, and records. In order to design the prevalence pattern for each geographic area, the information of the region and its neighborhoods in the past two weeks, has been used. Then, using a Boosting Classification algorithm, a method was developed to predict the prevalence rate for the next two weeks.
Results The model was presented for three groups with a prevalence of less than 200, ranging from 200 to 1000, and more than 1000 cases, and the model error rates were 9.42, 17.08, and 12.26, respectively. In addition, more than 1 million new cases are expected to become infected in the next two weeks (March 30 - April 12). The number of new cases are expected to be more than 19,000 new cases in Africa, over 100,000 in Asia, over 14,000 in Australia, over 600,000 in Europe and over 300,000 in the Americas.
Conclusion The increase in the prevalence growth rate of the disease will also be in the Southern Hemisphere, and the United States will have the highest prevalence worldwide.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
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