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Updated: Nov 26, 2025

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy
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Quantifying the dynamics of migration after Hurricane Maria in Puerto Rico.

Rolando J Acosta1, Nishant Kishore2, Rafael A Irizarry1,3

  • 1Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115.

Proceedings of the National Academy of Sciences of the United States of America
|December 9, 2020
PubMed
Summary

Natural disasters like Hurricane Maria cause significant population displacement. Mobile phone and social media data offer valuable insights into migration patterns and population loss in affected regions.

Keywords:
Hurricane MariaPuerto Ricopassively collected datapopulation displacement

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Area of Science:

  • Disaster epidemiology
  • Demography
  • Geospatial analysis

Background:

  • Natural disasters can lead to significant population displacement, impacting regional demographics and public health metrics.
  • Accurate population estimates are crucial for post-disaster resource allocation and mortality calculations.

Purpose of the Study:

  • To estimate population displacement in Puerto Rico following Hurricane Maria using mobile phone and social media data.
  • To compare these novel data sources with traditional methods like air travel records and census data.
  • To analyze the heterogeneity of migration within the island and identify factors influencing population loss.

Main Methods:

  • Analysis of anonymized mobile phone and social media data to track population movements.
  • Comparison of passively collected data with air travel records and census population estimates.
  • Geospatial analysis to assess within-island migration patterns and population density changes.

Main Results:

  • All data sources indicated population loss post-Hurricane Maria, with varying magnitudes.
  • Mobile phone data estimated an 8% population decrease, while social media data suggested a 17% loss.
  • Smaller municipalities experienced a proportionally larger population decrease, potentially indicating greater infrastructure damage.

Conclusions:

  • Passively collected data (mobile phone, social media) show promise in supplementing traditional methods for estimating population displacement after disasters.
  • Each data source possesses unique biases and limitations that must be considered.
  • Population shifts from rural to urban areas were observed, highlighting internal migration dynamics.