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 anend
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", }, }