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The Optimal COVID-19 Quarantine and Testing Policies

General information

Authors : Facundo Piguillem, Liyan Shi
Date of publication : March 27th, 2020
Paper : Available here
Code available : no

Related Public policy

Government policies model-based scenario
  • Multiplicative term in infection rate in function of variable level of working interactions in time.
  • Symptomatically infectious, and asymptomatic tested, if tests are available, are isolated and don't spread the virus

Technical information

Type of model : Compartimental
Technical description : SEIR, optimal control
Historical data w/ quarantine : Early data in Italy (calibration only)
Optimization formulation : Maximization of a welfare function with hamiltonian formulation

Assumptions
  1. Recovered and death rate depend on number of infectious and hospital capacity
  2. Some economical hypothesis (like production=consumption)
Input parameters

Essentially :

  • contagion rate,
  • exposed to infected rate,
  • recovery rate,
  • death rate if treated,
  • death rate if untreated,
  • hospital capacity,
  • initial exposed,
  • critical mass,
  • daily discount rate

Output variables : Optimal level of activity trajectory

Comments/Issues

Remarks

Model formulated in terms of economic loss, gives the optimal trajectory of the intensity of lockdown. Demands lot of exogenously fixed or calibrated parameters.

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