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PreprintCC BY 4.0HAL

Optimal transport for primary care planning

  • Souleymane Kane Diallo
  • Joseph Touzet
  • Xavier Bacon
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Abstract

This paper proposes a new model based on optimal transport theory that provides both a local and global measure of access to primary care. We extend a previously introduced OT-based spatial heterogeneity index designed to analyse spatial disparities in electoral results. The method allows us to identify shortage areas and determine geographically where additional general practitioners (GPs) should be located in order to maximize access to physicians. The model has significant policy implications given that it enables policymakers to target areas in need to implement incentives to attract new physicians. Thus, it helps avoid a concentration of physicians in some areas and help also to design a better distribution of physician across areas. To illustrate our method, we apply our model to Occitanie, the second-largest region in metropolitan France, which displays sufficient spatial heterogeneity for our purposes.

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Cite

BibTeXRIS
BibTeX
@misc{diallo2026optimal,
  title = {{Optimal transport for primary care planning}},
  author = {Souleymane Kane Diallo and Joseph Touzet and Xavier Bacon},
  howpublished = {HAL},
  year = {2026},
  month = sep,
  url = {https://hal.science/hal-05744938v1},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Optimal transport for primary care planning
AU  - Souleymane Kane Diallo
AU  - Joseph Touzet
AU  - Xavier Bacon
PY  - 2026
DA  - 2026/09/10
PB  - HAL
UR  - https://hal.science/hal-05744938v1
AB  - This paper proposes a new model based on optimal transport theory that provides both a local and global measure of access to primary care. We extend a previously introduced OT-based spatial heterogeneity index designed to analyse spatial disparities in electoral results. The method allows us to identify shortage areas and determine geographically where additional general practitioners (GPs) should be located in order to maximize access to physicians. The model has significant policy implications given that it enables policymakers to target areas in need to implement incentives to attract new physicians. Thus, it helps avoid a concentration of physicians in some areas and help also to design a better distribution of physician across areas. To illustrate our method, we apply our model to Occitanie, the second-largest region in metropolitan France, which displays sufficient spatial heterogeneity for our purposes.
ER  -