Support for prioritizing testing according to time since last test#35
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boazbk wants to merge 123 commits intoryansmcgee:masterfrom
Open
Support for prioritizing testing according to time since last test#35boazbk wants to merge 123 commits intoryansmcgee:masterfrom
boazbk wants to merge 123 commits intoryansmcgee:masterfrom
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…y in random testing to people for which more time passed before they were last tested
This reverts commit 51d3ad0
…ion if a certain condition is met, and ability to supress print statements.
…ndom_testing_degree_bias` parameter.
…ndom_testing_degree_bias` parameter.
…nd allow the priority of testing to be an arbitrary function
…d Series of the summary
…need to specify long parameters - useful to save on communication when running it in parallel
…need to specify long parameters - useful to save on communication when running it in parallel
# Conflicts: # seirsplus/sim_loops.py
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If number of tests available per time period is smaller than the total eligible population, at the moment the TTI loop selects the people chosen to test at random. However, it may make sense to do so based on the time people were last tested.
For example, if we test 1/2 of the population once a week, then if we select people at random then 1/4 would be tested twice in the same week and 1/4 won't be tested at all.
This pull request adds an array
testedTimeas an attribute toExtSEIRSNetworkModeland adds a parametertest_prioritytorun_tti_sim. The default value fortest_priorityisrandomwhich is the current strategy. However, if thetest_priorityparameter containslast_testedthen the pool to be tested is sorted according to the last time they were tested, breaking ties randomly.If the test priority contains
degree_obliviousthen we ignore degrees in choosing the degree pool. This makes sense if the people making decisions on testing policies do not have full information on the social network.Assuming you are interested, other enhancements I'd like to add (in a future pull request) is support for differentiating between node subgroups in:
External infections (for example staff and patients in nursing home have very different probability to be infected externally).
Testing policies for random testing (there could be different again for staff / patients)
I also can push code to run many simulations in parallel on a multi CPU machine.