Intervention types#

This section describes the intervention types and their parameters.

Interventions are defined in the proper simulation intervention file

Mobility intervention#

Mobility intervention can be used to simulate region lockdowns. When some region is locked down, agents cannot travel in and out of the region. This intervention can take effect only if mobility feature is enabled and defined with proper mobility input data (for details see here).

Example of valid keys for parameters

location_code use label intervention_type start_day num_days end_day
CZ01 true mob_change mobility_change 2020-03-01 2020-05-19
CZ02 false mob_change mobility_change "[10,25]"

Change in beta (overall transmission) intervention#

This intervention can be used to specify transmission by a certain amount for given day/days. Can be used for school closures/restrictions, home office, wearing masks etc. These changes affect the overall transmission parameter in the selected layers.

Example of valid keys for parameters

location_code use label intervention_type start_day num_days end_day beta_change layers
global false mah beta_change 2020-01-01 2020-03-19 [0.5] [w,s]
global true meh beta_change 2020-01-10 15 [0.5,0.7]

Contact isolation intervention#

Isolate contacts from simulation by, for example, removing contacts for school or for every contact layer. When intervention ends contacts will be restored. Can affect putting people to quarantine, if there is testing and tracking, because of contact removal. Can be used for example for school closures, home offices etc. Compared to the change in beta, contact isolation intervention removes contacts while preserving the transmission value.

Example of valid keys for parameters

location_code use label intervention_type start_day num_days end_day beta_change layers
CZ01 true contact isolation interv isolate_contacts 25 83 [0.7,1] [s,w]
Global true contact isolation interv global isolate_contacts 25 0.7 [s,w]

Daily testing intervention#

Intervention for daily testing specifies the number of agents tested per day. Its value can be also dependent on other values such as the probability of testing people who are quarantined etc. More info can be found in parameters.

Example of valid keys for parameters

location_code use label intervention_type start_day num_days end_day daily_tests symp_test sensitivity test_delay
CZ01 false Per day testing intervention CZ01 per_day_testing 10 2020-01-30 1.5 1.0 5
Global false Per day testing intervention global per_day_testing 2020-01-01 2020-01-30 1000 1.0 1.0 1

Testing probability intervention#

This intervention assigns to each person a probability of being tested based on the person's symptom state etc. The total number of tests is not specified as in Daily testing intervention, but it influences the probability of being tested. Can be used as a substitute to the daily testing intervention.

Example of valid keys for parameters

location_code use label intervention_type start_day num_days end_day symp_prob symp_quar_prob asymp_prob
global false Testing probability CZ01 testing_probability 20 2020-03-30 0.1 0.3 0.01
CZ01 false Tetsing probability CZ01 testing_probability 2020-01-01 30 0.1 0.3 0.01

Contact tracing intervention#

Contact tracing of agents who are already diagnosed positive by a testing intervention. Contacts are contacted and put in the quarantine (depends on simulation key:quar_factor parameter) for a certain period of time. If there is a probability of testing intervention, there can be significant increase of testing of contact-traced agents.

Example of valid keys for parameters. Note that there must be testing intervention (such as Daily testing or Probability testing) before/on day D of starting the contact tracing intervention, otherwise this intervention will not work.

location_code use label intervention_type num_days capacity trace_probs quar_period
Cz01 false contact tracing contact_tracing 0.5 6 6
global false contact tracing contact_tracing [10,30] 0.5 6 6

Simple vaccination#

Can be used to apply a simple vaccine to a subset of the population. This intervention can be added to changing the relative susceptibility and the probability of developing symptoms if still infected. More info about vaccination can be found in T5.3 Simulation - Immunity and variants.

Example of valid keys for parameters

location_code use label intervention_type prob rel_sus rel_symp
global true simple_vac_interv simple_vaccination 0.9 1.0 1.0

Intervention stacking#

You can define multiple interventions and it is not necessary to use all the keys. In the intervention csv/xlsx file you can define multiple intervention with its corresponding keys and those while leaving empty those interventions that are not used. Do not define user custom keys which are not corresponding to the allowed keys for each intervention.

Example of intervention stacking:

location_code use label intervention_type start_day num_days end_day beta_change layers vaccine sequence num_doses symp_prob symp_quar_prob asymp_prob capacity trace_probs quar_period daily_tests symp_test sensitivity test_delay
CZ01 true TestLabel mobility_change 2020-03-01 2020-05-19
global true TestLabel beta_change 2020-01-10 15 [0.5,0.7]
global false TestLabel testing_probability 2020-01-01 2020-03-30 0.1 0.3 0.01
global false TestLabel contact_tracing 10 0.5 6 6
CZ01 false TestLabel per_day_testing 10 2020-01-30 900 1.0 1 1
global false TestLabel testing_probability 20 2020-03-30 0.1 0.3 0.01
global false TestLabel contact_tracing [10,30] 0.5 6 6

Requirements#

Valid keys with values must be provided for each intervention, along with the necessary keys.