Evidence map›Paper›PMID 34899033›Full record

ArticleTransactions in GIS : TG2022

Urban spatial epidemic simulation model: A case study of the second COVID-19 outbreak in Beijing, China.

Qiang Huang, Qiyong Liu, Ci Song, Xiaobo Liu, Hua Shu, Xi Wang, Yaxi Liu, Xiao Chen, Jie Chen, Tao Pei

Abstract read
In one paragraph

Article in Transactions in GIS : TG, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment.International journal of environmental research and public health · 2022
    Article
  4. 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

10 authors.

Qiang HuangState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.ORCID https://orcid.org/0000-0002-3180-041X
Qiyong LiuState Key Laboratory of Infectious Disease Prevention and Control Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases WHO Collaborating Centre for Vector Surveillance and Management National Institute for Communicable Disease Control and Prevention Chinese Center for Disease Control and Prevention Beijing China.
Ci SongState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.
Xiaobo LiuState Key Laboratory of Infectious Disease Prevention and Control Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases WHO Collaborating Centre for Vector Surveillance and Management National Institute for Communicable Disease Control and Prevention Chinese Center for Disease Control and Prevention Beijing China.
Hua ShuState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.
Xi WangState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.
Yaxi LiuState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.ORCID https://orcid.org/0000-0002-3261-829X
Xiao ChenState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.
Jie ChenState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.
Tao PeiState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.ORCID https://orcid.org/0000-0002-5311-8761

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The second COVID-19 outbreak in Beijing was controlled by non-pharmaceutical interventions, which avoided a second pandemic. Until mass vaccination achieves herd immunity, cities are at risk of similar outbreaks. It is vital to quantify and simulate Beijing's non-pharmaceutical interventions to find effective intervention policies for the second outbreak. Few models have achieved accurate intra-city spatio-temporal epidemic spread simulation, and most modeling studies focused on the initial pandemic. We built a dynamic module of infected case movement within the city, and established an urban spatially epidemic simulation model (USESM), using mobile phone signaling data to create scenarios to assess the impact of interventions. We found that: (1) USESM simulated the transmission process of the epidemic within Beijing; (2) USESM showed the epidemic curve and presented the spatial distribution of epidemic spread on a map; and (3) to balance resources, interventions, and economic development, nucleic acid testing intensity could be increased and restrictions on human mobility in non-epidemic areas eased.

Identifiers

PMID34899033
PMCPMC8646780

What OpenQuestion holds

Textmetadata
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.