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Childbirth Mobilities: A Geo-Spatial Simulation Approach.

Rocco Paolillo1, Filippo Accordino1,2, Fabrizio Pecoraro1

  • 1Institute for Research on Population and Social Policies, National Research Council, Italy.

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|May 23, 2026
PubMed
Summary
This summary is machine-generated.

This study models how expectant mothers choose hospitals, considering distance, reputation, and social influence. Agent-based modeling reveals how these factors interact to shape childbirth location decisions.

Keywords:
agent-based simulationchildbirth mobilitieshospital choicesocial influencesocial network

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Area of Science:

  • Health Services Research
  • Computational Social Science
  • Geographic Information Systems

Background:

  • Childbirth hospital selection is influenced by factors like distance, hospital rankings, and word-of-mouth.
  • Existing research often studies these predictors in isolation, lacking insight into their interactions.

Purpose of the Study:

  • To model the complex interplay of factors influencing expectant women's childbirth hospital selection.
  • To utilize agent-based modeling (ABM) to simulate decision-making processes and social influence.

Main Methods:

  • Developed an agent-based model simulating expectant mothers' choices.
  • Integrated synthetic population data with geo-spatial data from the Tuscany region, Italy.
  • Analyzed the combined effects of hospital distance, opinion ranking, and social influence modes.

Main Results:

  • Identified specific combinations of distance, ranking, and social influence that accurately replicate observed hospital selection patterns.
  • Quantified the extent to which different combinations of factors influence choices.
  • Demonstrated the utility of ABM in understanding complex healthcare-seeking behaviors.

Conclusions:

  • The interaction between distance, perceived quality (ranking), and social networks significantly shapes childbirth hospital choices.
  • Agent-based modeling provides a powerful framework for exploring healthcare navigation and decision-making.
  • Findings can inform healthcare providers and policymakers aiming to improve access and patient satisfaction.