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'Traffic light' theory for Covid-19 spatial mitigation policy design

Author

Listed:
  • Xieer Dai

    (University of Shenzhen)

  • Michael Beenstock

    (Hebrew University of Jerusalem)

  • Daniel Felsenstein

    (Hebrew University of Jerusalem)

  • David Genesove

    (Hebrew University of Jerusalem)

  • Nikita Kotsenko

    (Hebrew University of Jerusalem)

Abstract

We suggest the use of outdegrees from graph theory to rank locations in terms of their contagiousness. We show that outdegrees are equal to the column sums of spatial autoregressive matrices, which may be estimated using econometric methods for spatial panel data. In contrast to outdegree, R is invalid for 'traffic light' shading because it fails to distinguish between the export and import of contagion between sub-national locations. Simulation methods are used to illustrate the concept of outdegrees and its structural determinants in terms of centrality, indigenous contagion and spatial contagion. An empirical illustration is presented for Israel. A secondary criterion for traffic light shading involves the stochastic structure of morbidity shocks, which induce 'spiking' through their autoregressive persistence, conditional heteroscedasticity and diffusion jump parameters.

Suggested Citation

  • Xieer Dai & Michael Beenstock & Daniel Felsenstein & David Genesove & Nikita Kotsenko, 2023. "'Traffic light' theory for Covid-19 spatial mitigation policy design," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-35, December.
    • Handle: RePEc:spr:jospat:v:4:y:2023:i:1:d:10.1007_s43071-022-00033-8
    DOI: 10.1007/s43071-022-00033-8
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