Evidence map›Paper›PMID 35805223›Full record

ArticleInternational journal of environmental research and public health2022

Social Network Analysis on the Mobility of Three Vulnerable Population Subgroups: Domestic Workers, Flight Crews, and Sailors during the COVID-19 Pandemic in Hong Kong.

Weijun Yu, Cheryll Alipio, Jia'an Wan, Heran Mane, Quynh C Nguyen

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 46% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 3 institutions in 1 country.

Weijun YuDepartment of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0002-0771-5581
Cheryll AlipioWalter H. Shorenstein Asia-Pacific Research Center, Freeman Spogli Institute for International Studies, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-2437-7681
Jia'an WanSamuel Curtis Johnson Graduate School of Management, Cornell University, Ithaca, NY 14850, USA.
Heran ManeDepartment of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA.
Quynh C NguyenDepartment of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0003-4745-6681
University of Maryland, College Park · USCornell University · USPacific Research Institute · US

Funding

Rosie the Chatbot: Leveraging Automated and Personalized Health Information Communication to Reduce Disparities in Maternal and Child HealthR01MD016037 · NIMHD · UNIV OF MARYLAND, COLLEGE PARK · PI NGUYEN, THU, NORELL, ELIZABETH MARIE · 2021 to 2025
$3.3M
Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects ResearchR01LM012849 · NLM · UNIV OF MARYLAND, COLLEGE PARK · PI NGUYEN, QUYNH · 2018 to 2021
$1.3M
NIMHD NIH HHS R01 MD016037NLM NIH HHS R01 LM012849
6 · The paper itself

Abstract

backgroundDomestic workers, flight crews, and sailors are three vulnerable population subgroups who were required to travel due to occupational demand in Hong Kong during the COVID-19 pandemic.

objectiveThe aim of this study was to explore the social networks among three vulnerable population subgroups and capture temporal changes in their probability of being exposed to SARS-CoV-2 via mobility.

methodsWe included 652 COVID-19 cases and utilized Exponential Random Graph Models to build six social networks: one for the cross-sectional cohort, and five for the temporal wave cohorts, respectively. Vertices were the three vulnerable population subgroups. Edges were shared scenarios where vertices were exposed to SARS-CoV-2.

resultsThe probability of being exposed to a COVID-19 case in Hong Kong among the three vulnerable population subgroups increased from 3.38% in early 2020 to 5.78% in early 2022. While domestic workers were less mobile intercontinentally compared to flight crews and sailors, domestic workers were 1.81-times in general more likely to be exposed to SARS-CoV-2.

conclusionsVulnerable populations with similar ages and occupations, especially younger domestic workers and flight crew members, were more likely to be exposed to SARS-CoV-2. Social network analysis can be used to provide critical information on the health risks of infectious diseases to vulnerable populations.

Indexed as

COVID-19Military PersonnelCross-Sectional StudiesHong KongHumansPandemicsSARS-CoV-2Social Network AnalysisVulnerable PopulationsCOVID-19domestic workerexponential random graph modelflight crewmobilitysailorSARS-CoV-2social network analysisvulnerable population

Identifiers

PMID35805223
PMCPMC9265614
OpenAlexW4283265319

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.