Policies

See also

For a hands-on example on how to specify contact policies, look at the tutorial about contact policies.

In sid we can implement nearly any type of policy as a modification of the Contact Models. However, to keep things separable and modular, policies can also specified outside the contact models in a separate, specialized contact_policies dictionary.

contact_policies

The contact policies are a nested dictionary, mapping the policy’s name to its specification. You can choose any name you wish.

The specification must contain an affected_contact_model entry, a policy entry and provide when the policy is active. The affected_contact_model gives the name of the contact model whose output, the contacts (a pandas.Series with the same index as the states DataFrame), will be modified while the policy is active. The policy entry is either a float or a function. If it is a float, the contacts are simply multiplied with the this number. For non-recurrent contact models we will round the results for you to have the wanted reduction on average. If it is a function, it should take the states, contacts and seed as inputs and return a modified contacts Series.

To specify when the policy is active, you have three options:

• You provide a start and an end date. For example, you could specify school closures during the first lockdown which started on the 22nd of March and ended on the 20th of April as following

  {
      "1st_lockdown_school": {
          "affected_contact_model": "school",
          "policy": 0,
          "start": "2020-03-22",
          "end": "2020-04-20",
      },
  }