Evidence map›Paper›PMID 32814822›Full record

ArticleScientific reports2020

A retrospective analysis of the dynamic transmission routes of the COVID-19 in mainland China.

Xiandeng Jiang, Le Chang, Yanlin Shi

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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

3 authors.

Xiandeng JiangSchool of Public Finance and Taxation, Southwestern University of Finance and Economics, Chengdu, 611130, Sichuan, People's Republic of China.
Le ChangResearch School of Finance, Actuarial Studies, and Statistics, Australian National University, Canberra, ACT, 2601, Australia.
Yanlin ShiDepartment of Actuarial Studies and Business Analytics, Macquarie University, Sydney, NSW, 2109, Australia. yanlin.shi@mq.edu.au.

Funding

The People Republic of China Ministry of Education Youth Project for Humanities and Social Science Research 20YJC790051
6 · The paper itself

Abstract

The fourth outbreak of the Coronaviruses, known as the COVID-19, has occurred in Wuhan city of Hubei province in China in December 2019. We propose a time-varying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dynamic transmission routes of this outbreak in mainland China over January 31-February 19, 2020. Our results demonstrate that the influential inter-location routes from Hubei have become unidentifiable since February 4, 2020, whereas the self-transmission in each provincial-level administrative region (location, hereafter) was accelerating over February 4-15, 2020. From February 16, 2020, all routes became less detectable, and no influential transmissions could be identified on February 18 and 19, 2020. Such evidence supports the effectiveness of government interventions, including the travel restrictions in Hubei. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in locations with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of COVID-19.

Indexed as

BetacoronavirusModels, StatisticalChinaCitiesCoronavirus InfectionsCOVID-19HumansPandemicsPersonal Protective EquipmentPneumonia, ViralPublic HealthQuarantineRetrospective StudiesSARS-CoV-2Time FactorsTransients and Migrants

Identifiers

PMID32814822
PMCPMC7438497

What OpenQuestion holds

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LicenceCC BY
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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.