Evidence map›Paper›PMID 36059792›Full record

ArticleChina CDC weekly2022

Modeling Cross-Regional Transmission and Assessing the Effectiveness of Restricting Inter-Regional Population Movements in Controlling COVID-19 - Xi'an City, Shaanxi Province, China, 2021.

Tianlong Yang, Yao Wang, Nankun Liu, Guzainuer Abudurusuli, Shiting Yang, Shanshan Yu, Weikang Liu, Xuecheng Yin, Tianmu Chen

Abstract read
In one paragraph

Article in China CDC weekly, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

9 authors.

Tianlong YangSchool of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Yao WangState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Xiamen University, Xiamen City, Fujian Province, China.
Nankun LiuChinese Center for Disease Control and Prevention, Beijing, China.
Guzainuer AbudurusuliSchool of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Shiting YangSchool of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Shanshan YuSchool of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Weikang LiuSchool of Public Health, Xiamen University, Xiamen City, Fujian Province, China.
Xuecheng YinSchool of Public Health, Yale University, New Haven, Connecticut, US.
Tianmu ChenSchool of Public Health, Xiamen University, Xiamen City, Fujian Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The aim of this study was to construct an assessment method for cross-regional transmission of coronavirus disease 2019 (COVID-19) and to provide recommendations for optimizing measures such as interregional population movements. Methods: Taking Xi'an City as the example subject of this study's analysis, a Cross-Regional-Gravitational-Dynamic model was constructed to simulate the epidemic in each district of Xi'an under three scenarios of controlled population movement (Scenario 1: no intensive intervention; Scenario 2: blocking Yanta District on December 18 and blocking the whole region on December 23; and Scenario 3: blocking the whole region on December 23). This study then evaluated the effects of such simulated population control measures. Results: The cumulative number of cases for the three scenarios was 8,901,425, 178, and 474, respectively, and the duration of the epidemic was 175, 18, and 22 days, respectively. The real world prevention and control measures in Xi'an reduced the cumulative number of cases for its outbreak by 99.98% in comparison to the simulated response in Scenario 1; in contrast, the simulated prevention and control strategies set in Scenarios 2 (91.26%) and 3 (76.73%) reduced cases even further than the real world measures used in Xi'an. Discussion: The constructed model can effectively simulate an outbreak across regions. Timely implementation of two-way containment and control measures in areas where spillover is likely to occur is key to stopping cross-regional transmission.

Indexed as

containment and control measuresCOVID-19cross-regional transmissiontransmission dynamics model

Identifiers

PMID36059792
PMCPMC9433766

What OpenQuestion holds

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Registered trials

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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.