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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: May 20, 2022
Date Accepted: Feb 23, 2023
Date Submitted to PubMed: Feb 27, 2023

The final, peer-reviewed published version of this preprint can be found here:

Impact of Human Mobility on COVID-19 Transmission According to Mobility Distance, Location, and Demographic Factors in the Greater Bay Area of China: Population-Based Study

Xia J, Yin K, Yue Y, Li Q, Wang X, Hu D, Wang X, Du Z, Cowling BJ, Chen E, Zhou Y

Impact of Human Mobility on COVID-19 Transmission According to Mobility Distance, Location, and Demographic Factors in the Greater Bay Area of China: Population-Based Study

JMIR Public Health Surveill 2023;9:e39588

DOI: 10.2196/39588

PMID: 36848228

PMCID: 10138924

Impact of human mobility on COVID-19 transmission according to mobility distance, locations and demographic factors in the Greater Bay area of China:a population-based study

  • Jizhe Xia; 
  • Kun Yin; 
  • Yang Yue; 
  • Qingquan Li; 
  • Xiling Wang; 
  • Dongsheng Hu; 
  • Xiong Wang; 
  • Zhanwei Du; 
  • Ben J Cowling; 
  • Erzhen Chen; 
  • Ying Zhou

ABSTRACT

Background:

Mobility restriction is one of the primary measures used to restrain the spread of COVID-19 in the pandemic all over the world. Governments implemented and relaxed various mobility restriction measures in the absence of evidence for almost three years, which caused severe adverse outcomes in health, society and economy.

Objective:

This study aims to quantify the impact of mobility reduction on COVID-19 transmission according to mobility distance, locations and demographic factors to provide evidences to optimize mobility restriction policies.

Methods:

Millions of the anonymized, aggregated mobile phone position data between Jan 1 and Feb 24, 2020 was collected for the nine mega cities Greater Bay Area (GBA), China. A generalized linear model (GLM) was established to test the association between mobility volume (number of trips) and COVID-19 transmission. Subgroups analysis was also performed for sex, age, travel locations and travel distance. The statistical interaction terms were included in a variety of models that express different relations between the involved variables.

Results:

The GLM analysis demonstrated a significant association between the COVID-19 growth rate ratio (GR) and mobility volume. A stratification analysis revealed a higher effect of mobility volume on the COVID-19 growth rate ratio (GR) among people aged 50-59 years (a decrease of 13.17% for GR per 10% reduction of mobility volume for persons 50-59 years, P <.001) than for other age groups (a decrease of 7.80%, 10.43%, 7.48%, 8.01%, 10.43% for age groups of ≤18, 19-29, 30-39, 40-49, ≥ 60 years, respectively, Pinteraction=.024). The impact of mobility reduction on COVID-19 transmission was higher in transit stations and shopping areas: a decrease of 0.67, 0.53, 0.30, 0.37, 0.44, 0.32 for instantaneous reproduction number R(t) per 10% reduction in mobility volume to transit stations, shopping, work, school, recreation, and other locations, separately (Pinteraction=.016). The association between reduction in mobility volume and COVID-19 transmission was lower with decreasing mobility distance as there was significant interaction between mobility volume and mobility distance on R(t) (Pinteraction<.001). Specifically, the R(t) reduced by 11.97% per 10% reduction of mobility volume when the mobility distance increased to 110% (Spring Festival), by 6.74% when distance remained unchanged and by 1.52% when the distance decreased to 90%.

Conclusions:

The association between mobility reduction and COVID-19 transmission significantly varied by mobility distance, locations and age. The substantially higher impact of mobility volume on COVID-19 transmission in longer travel distance, certain age groups, and for specific travel destinations highlights the potential to optimize the effectiveness of mobility restriction strategies. Our study would help governments make informed decisions to balance the benefits of mobility restriction on reducing infectious diseases transmission and negative impact on health, society, and economy in this COVID-19 pandemic and provide evidences for next pandemics. Clinical Trial: Not applicable.


 Citation

Please cite as:

Xia J, Yin K, Yue Y, Li Q, Wang X, Hu D, Wang X, Du Z, Cowling BJ, Chen E, Zhou Y

Impact of Human Mobility on COVID-19 Transmission According to Mobility Distance, Location, and Demographic Factors in the Greater Bay Area of China: Population-Based Study

JMIR Public Health Surveill 2023;9:e39588

DOI: 10.2196/39588

PMID: 36848228

PMCID: 10138924

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