Evidence map›Paper›PMID 34729027›Full record

ArticleRisk management and healthcare policy2021

Exploring the Pattern of Early COVID-19 Transmission Caused by Population Migration Based on 14 Cities in Hubei Province, China.

Lin Luo, Wen Wen, Chun-Yi Wang, Mengyun Zhou, Jie Ni, Jingjie Jiang, Juan Chen, Ming-Wei Wang, Zhanhui Feng, Yong-Ran Cheng

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lin LuoHangzhou Ruolin Hospital Management Co. Ltd, Hangzhou, 310007, People's Republic of China.
Wen WenHangzhou Institute of Cardiovascular Diseases, Hangzhou Medical Key Discipline, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, People's Republic of China.
Chun-Yi WangHangzhou Institute of Cardiovascular Diseases, Hangzhou Medical Key Discipline, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, People's Republic of China.
Mengyun ZhouDepartment of Molecular & Cellular Physiology, Shinshu University School of Medicine, Nagano, 3900803, Japan.
Jie NiInternal Medicine-Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, People's Republic of China.
Jingjie JiangHangzhou Institute of Cardiovascular Diseases, Hangzhou Medical Key Discipline, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, People's Republic of China.
Juan ChenHangzhou Institute of Cardiovascular Diseases, Hangzhou Medical Key Discipline, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, People's Republic of China.
Ming-Wei WangHangzhou Institute of Cardiovascular Diseases, Hangzhou Medical Key Discipline, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, People's Republic of China.ORCID 0000-0001-9060-5107
Zhanhui FengInternal Medicine-Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, People's Republic of China.
Yong-Ran ChengSchool of Public Health, Hangzhou Medical College, Hangzhou, 311300, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimRelevant studies show that population migration has a great impact on the early spread of infectious diseases. Therefore, it is important to explore whether there is an explicit relationship between population migration and the number of confirmed cases for the control of the COVID-19 epidemic. This paper mainly explores the impact of population migration on early COVID-19 transmission, and establishes a predictive nonlinear mathematical model to predict the number of early cases.

methodsData of confirmed cases were sourced from the official website of the Municipal Health Committee, and the proportions of migration from Wuhan to other cities were sourced from the Baidu data platform. The data of confirmed cases and the migration proportions of 14 cities in Hubei Province were collected, the COVID-19 cases study period was determined as 10 days based on the third quartile of the interval of the incubation period, and a non-linear mathematical model was constructed to clarify the relationship between the migration proportion and the number of confirmed COVID-19 cases. Finally, eight typical regions were selected to verify the accuracy of the model.

resultsThe daily population migration rates and the growth curves of the number of confirmed cases in the 14 cities were basically consistent, and Pearson's correlation coefficient was 0.91. The specific mathematical expression of 14 regions is . In each of the fourteen cities, The nonlinear exponential model structure is as follows:. It was found that the

conclusionThe study found that population migration has a positive and significant impact on the spread of COVID-19. Modeling COVID-19 risk may be a useful strategy for directing public health surveillance and interventions. Restricting the migration of the population is of great significance to the joint prevention and control of the pandemic worldwide.

Indexed as

COVID-19non-linear exponentialSARS-CoV-2spreadstravel

Identifiers

PMID34729027
PMCPMC8555669

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.