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

Int J Environ Res Public Health. 2022 Jun 21;19(13):7565. doi: 10.3390/ijerph19137565.

Abstract

Background: Domestic 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.

Objective: The 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.

Methods: We 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.

Results: The 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.

Conclusions: Vulnerable 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.

Keywords: COVID-19; SARS-CoV-2; domestic worker; exponential random graph model; flight crew; mobility; sailor; social network analysis; vulnerable population.

MeSH terms

  • COVID-19* / epidemiology
  • Cross-Sectional Studies
  • Hong Kong / epidemiology
  • Humans
  • Military Personnel*
  • Pandemics
  • SARS-CoV-2
  • Social Network Analysis
  • Vulnerable Populations