What’s new

All notable changes to the codebase are documented in this file. Changes that may result in differences in model output, or are required in order to run an old parameter set with the current version, are flagged with the term “Regression information”.

Latest versions (1.6.x)

Version 1.6.0 (2020-09-08)

  • There is a new cv.vaccine() intervention, which can be used to implement vaccination for subgroups of people. Vaccination can affect susceptibility, symptomaticity, or both. Multiple doses (optionally with diminishing efficacy) can be delivered.

  • cv.Layer objects have a new highly optimized find_contacts() method, which reduces time required for the contact tracing by a factor of roughly 2. This method can also be used directly to find the matching contacts for a set of indices, e.g. sim.people.contacts['h'].find_contacts([12, 144, 2048]) will find all contacts of the three people listed.

  • The method sim.compute_summary() has been removed; sim.summarize() now serves both purposes. This function previously always took the last time point in the results arrays, but now can take any time point.

  • A new reset keyword has been added to sim.initialize(), which will overwrite sim.people even if it already exists. Similarly, both interventions and analyzers are preserved after a sim run, unless sim.initialize() is called again (previously, analyzers were preserved but interventions were reset). This is to support storing data in interventions, as used by cv.vaccine().

  • sim.date() can now handle strings or date objects (previously, it could only handle integers).

  • Data files in formats .json and .xls can now be loaded, in addition to the .csv and .xlsx formats supported previously.

  • Additional flexibility has been added to plotting, including user-specified colors for data; custom sim labels; and reusing existing axes for plots.

  • Metadata now saves correctly to PDF and SVG images via cv.savefig(). An issue with cv.check_save_version() using the wrong calling frame was also fixed.

  • The field date_exposed has been added to transmission trees.

  • The result “Effective reproductive number” has been renamed “Effective reproduction number”.

  • Analyzers now have additional validation to avoid out-of-bounds dates, as well as additional test coverage.

  • Regression information: No major backwards incompatibilities are introduced by this version. Instances of sim.compute_summary() should be replaced by sim.summarize(), and results dependent on the original state of an intervention post-simulation should use sim._orig_pars['interventions'] (or perform sim.initialize() prior to using them) instead of sim['interventions'].

  • GitHub info: PR 664, previous head 017a3b7

Versions 1.5.x (1.5.0 – 1.5.3)

Version 1.5.3 (2020-09-01)

  • An AlreadyRunError is now raised if sim.run() is called in such a way that no timesteps will be taken. This error is a distinct type so that it can be safely caught and ignored if required, but it is anticipated that most of the time, calling run() and not taking any timesteps, would be an inadvertent error.

  • If the simulation has reached the end, sim.run() (and sim.step()) will now raise an AlreadyRunError.

  • sim.run() now only validates parameters as part of initialization. Parameters will always be validated in the normal workflow where sim.initialize() is called via sim.run(). However, the use case for modifying parameters during a split run or otherwise modifying parameters after initialization suggests that the user should have maximum control over the parameters at this point, so in this specialist workflow, the user is responsible for setting the parameter values correctly and in return, sim.run() is guaranteed not to change them.

  • Added a sim.complete attribute, which is True if all timesteps have been executed. This is independent of finalizing results, since if sim.step() is being called externally, then finalizing the results may happen separately.

  • GitHub info: : PR 654, previous head 9041157

Version 1.5.2 (2020-08-18)

  • Modify cv.People.quarantine() to allow it schedule future quarantines, and allow quarantines of varying duration.

  • Update the quarantine pipeline so that date_known_contact is not removed when someone goes into quarantine.

  • Fixed bug where people identified as known contacts while on quarantine would be re-quarantined at the end of their quarantine for the entire quarantine duration. Now if a quarantine is requested while someone is already on quarantine, their existing quarantine will be correctly extended where required. For example, if someone is quarantined for 14 days on day 0 so they are scheduled to leave quarantine on day 14, and they are then subsequently identified as a known contact of a separate person on day 6 requiring 14 days quarantine, in previous versions of Covasim they would be released from quarantine on day 15, and then immediately quarantined on day 16 until day 30. With this update, their original quarantine would now be extended, so they would be released from quarantine on day 20.

  • Quarantine duration via cv.People.trace() is now based on time since tracing, not time since notification, as people are typically instructed to isolate for a period after their last contact with the confirmed case, whenever that was. This results in an overall decrease in time spent in quarantine when the trace_time is greater than 0.

  • Regression information:
    • Scripts that called cv.People.quarantine() directly would have also had to manually update sim.results['new_quarantined']. This is no longer required, and those commands should now be removed as they will otherwise be double counted

    • Results are expected to differ slightly because the handling of quarantines being extended has been improved, and because quarantine duration is now reduced when by the trace_time.

  • GitHub info: PR 624, previous head aaa4d7c

Version 1.5.1 (2020-08-17)

  • Modify cv.BasePeople.__getitem__() to retrieve a person if the item is an integer, so that sim.people[5] will return a cv.Person instance

  • Modify cv.BasePeople.__iter__ so that iterating over people e.g. for person in sim.people: iterates over cv.Person instances

  • Regression information: To restore previous behavior of for idx in sim.people: use for idx in range(len(sim.people)): instead

  • GitHub info: PR 623, previous head 775cf35

Version 1.5.0 (2020-07-01)

  • Based on calibrations to Seattle-King County data, default parameter values have been updated to have higher dispersion and smaller differences between layers.

  • Keywords for computing goodness-of-fit (e.g. use_frac) can now be passed to the Fit() object.

  • The overview plot (to_plot='overview') has been updated with more plots.

  • Subtargeting of testing interventions is now more flexible: values can now be specified per person.

  • Issues with specifying DPI and for saving calling function information via cv.savefig() have been addressed.

  • Several minor plotting bugs were fixed.

  • A new function, cv.undefined(), can be used to find indices for which a quantity is not defined (e.g., cv.undefined(sim.people.date_diagnosed) returns the indices of everyone who has never been diagnosed).

  • Regression information: To restore previous behavior, use the following parameter changes:

    pars['beta_dist'] = {'dist':'lognormal','par1':0.84, 'par2':0.3}
    pars['beta_layer'] = dict(h=7.0, s=0.7, w=0.7, c=0.14)
    pars['iso_factor']  = dict(h=0.3, s=0.0, w=0.0, c=0.1)
    pars['quar_factor'] = dict(h=0.8, s=0.0, w=0.0, c=0.3)
  • GitHub info: PR 596, previous head 39b1e52

Versions 1.4.x (1.4.0 – 1.4.7)

Version 1.4.7 (2020-06-02)

  • Added quar_policy argument to cv.test_num() and cv.test_prob(); by default, people are only tested upon entering quarantine ('start'); other options are to test people as they leave quarantine, both as they enter and leave, and every day they are in quarantine (which was the previous default behavior).

  • Requirements have been tidied up; python setup.py develop nowebapp now only installs minimal packages. In a future version, this may become the default.

  • Fixed intervention export and import from JSON.

  • Regression information: To restore previous behavior (not recommended) with using contact tracing, add quar_policy='daily' to cv.test_num() and cv.test_prob() interventions.

  • GitHub info: PR 593, previous head 89c58e1

Version 1.4.6 (2020-06-01)

  • Implemented continuous rescaling: dynamic rescaling can now be used with an arbitrarily small rescale_factor. The amount of rescaling on a given timestep is now either rescale_factor or the factor that would be required to bring the population below the threshold, whichever is larger.

  • Regression information: Results should not be affected unless a simulation was run with too small of a rescaling factor. This change corrects this issue.

  • GitHub info: PR 588, previous head 4cabddc

Version 1.4.5 (2020-05-31)

  • Added cv.date_range().

  • Changed cv.day() and cv.date() to assume a start day of 2020-01-01 if not supplied.

  • Added the option to add custom data to a Fit object, e.g. age histogram data.

Version 1.4.4 (2020-05-31)

  • Improved transmission tree histogram plotting, including allowing start and end days, and renamed plot_histograms().

  • Added functions for negative binomial distributions, allowing easier exploration of overdispersion effects: see cv.make_random_contacts(), and, most importantly, pars['beta_dist'].

  • Renamed cv.multinomial() to cv.n_multinomial().

  • Added a build_docs script.

Version 1.4.3 (2020-05-30)

  • Added swab_delay to cv.test_prob(), which behaves the same way as for cv.test_num() (to set the delay between experiencing symptoms and receiving a test).

  • Allowed weights for a Fit to be specified as a time series.

Version 1.4.2 (2020-05-30)

  • Renamed cv.check_save_info() to cv.check_save_version(), and allowed the die argument to be passed.

  • Allowed verbose to be a float instead of an int; if between 0 and 1, during a model run, it will print out once every 1/verbose days, e.g. verbose = 0.2 will print an update once every 5 days.

  • Updated the default number of household contacts from 2.7 to 2.0 for hybrid, and changed cv.poisson() to no longer cast to an integer. These two changes cancel out, so default behavior has not changed.

  • Updated the calculation of contacts from household sizes (now uses household size - 1, to remove self-connections).

  • Added cv.MultiSim.load().

  • Added Numba caching to compute_viral_load(), reducing overall Covasim load time by roughly 50%.

  • Added an option for parallel execution of Numba functions (see utils.py); although this significantly improves performance (20-30%), it results in non-deterministic results, so is disabled by default.

  • Changed People to use its own contact layer keys rather than those taken from the parameters.

  • Improved plotting and corrected minor bugs in age histogram and model fit analyzers.

  • Regression information:

    • Replace cv.check_save_info() with cv.check_save_version().

    • If you used a non-integer number of contacts, round down to the nearest integer (e.g., change 2.7 to 2.0).

    • If you loaded a household size distribution (e.g. cv.Sim(location='nigeria')), add one to the number of household contacts (but then round down).

  • GitHub info: PR 577, previous head a828d29

Version 1.4.1 (2020-05-29)

  • Added sim.people.plot(), which shows the age distribution, and distribution of contacts by age and layer.

  • Added sim.make_age_histogram(), as well as the ability to call cv.age_histogram(sim), as an alternative to adding these as analyzers to a sim.

  • Updated cv.make_synthpop() to pass a random seed to SynthPops (note: requires SynthPops version 0.7.1 or later).

  • cv.set_seed() now also resets random.seed(), to ensure reproducibility among functions that use this (e.g., NetworkX).

  • Corrected sim.run() so sim.t is left at the last timestep (instead of one more).

Version 1.4.0 (2020-05-28)

This version contains a large number of changes, including two new classes, Analyzer and Fit, for performing simulation analyses and fitting the model to data, respectively. These changes are described below.


  • Added a new class, Analyzer, to perform analyses on a simulation.

  • Added a new parameter, sim['analyzers'], that operates like interventions: it accepts a list of functions or Analyzer objects.

  • Added two analyzers: cv.age_hist records age histograms of infections, diagnoses, and deaths; cv.snapshot makes copies of the People object at specified points in time.


  • Added a new class, cv.Fit(), that stores information about the fit between the model and the data. “Likelihood” is no longer automatically calculated, but instead “mismatch” can be calculated via fit = sim.compute_fit().

  • The Poisson test that was previously used for the “likelihood” calculation has been deprecated; the new default mismatch is based on normalized absolute error.

  • For a plot of how the mismatch is being calculated, use fit.plot().


  • Added multisim.init_sims(), which is not usually necessary, but can be helpful if you want to create the Sim objects without running them straight away.

  • Added multisim.split(), easily allowing a merged multisim to be split back into its constituent parts (non-merged multisims can also be split). This can be used for example to create several multisims, merge them together, run them all at the same time in parallel, and then split the back for analysis.

Display functions

  • Added sim.summarize(), which shows a short review of key sim results (cumulative counts).

  • Added sim.brief(), which shows a one-line summary of the sim.

  • Added multisim.summarize(), which prints a brief summary of all the constituent sims.

Parameter changes

  • Removed the parameter interv_func; instead, intervention functions can now be appended to sim['interventions'].

  • Changed the default for the rescale parameter from False to True. To return to previous behavior, define sim['rescale'] = False explicitly.

Other changes

  • Added cv.day() convenience function to convert a date to an integer number of days (similar to cv.daydiff()); also modified cv.date() to be able to handle input more flexibly. While sim.day() and sim.date() are still the recommended functions, the same functionality is now also available without a Sim object available.

  • Allowed cv.load_data()` to accept non-time-series inputs.

  • Added cumulative diagnoses to default plots.

  • Moved sweeps (Weights & Biases) to examples/wandb.

  • Refactored cruise ship example to work again.

  • Various bugfixes (e.g. to plotting arguments, data scrapers, etc.).

  • Regression information: To migrate an old parameter set pars to this version and to restore previous behavior, use:

    pars['analyzers'] = None # Add the new parameter key
    interv_func = pars.pop('interv_func', None) # Remove the deprecated key
    if interv_func:
        pars['interventions'] = interv_func # If no interventions
        pars['interventions'].append(interv_func) # If other interventions are present
    pars['rescale'] = pars.pop('rescale', False) # Change default to False
  • GitHub info: PR 569, previous head 8b157a2

Versions 1.3.x (1.3.0 – 1.3.5)

Version 1.3.5 (2020-05-28)

  • Added swab_delay argument to cv.test_num(), allowing a distribution of times between when a person develops symptoms and when they go to be tested (i.e., receive a swab) to be specified.

Version 1.3.4 (2020-05-26)

  • Allowed data to be loaded from a dataframe instead of from file.

  • Fixed data scrapers to use correct column labels.

Version 1.3.3 (2020-05-26)

  • Fixed issue with a loaded population being reloaded when a simulation is re-initialized.

  • Fixed issue with the argument dateformat not being passed to the right plotting routine.

  • Fixed issue with MultiSim plotting appearing in separate panels when run in a Jupyter notebook.

  • Fixed issue with cv.git_info() failing to write to file when the calling function could not be found.

Version 1.3.2 (2020-05-25)

  • People and popdict objects can now be supplied directly to the sim instead of a file name.

  • git_info() and check_save_info() now include information from the calling script (not just Covasim). They also now include a comments field to optionally store additional information.

Version 1.3.1 (2020-05-25)

  • Modified calculation of R_eff to include a longer integration period at the beginning, and restored previous method of creating seed infections.

  • Updated default plots to include number of active infections, and removed recoveries.

Version 1.3.0 (2020-05-24)

  • Changed the default number of work contacts in hybrid from 8 to 16, and halved beta from 1.4 to 0.7, to better capture superspreading events. Regression information: To restore previous behavior, set sim['beta_layer']['w'] = 0.14 and sim['contacts']['w'] = 8.

  • Initial infections now occur at a distribution of dates instead of all at once; this fixes the artificial spike in R_eff that occurred at the very beginning of a simulation. Regression information: This change affects results, but was reverted in the next version (1.3.1).

  • Changed the definition of age bins in prognoses to be lower limits rather than upper limits. Added an extra set of age bins for 90+.

  • Changed population loading and saving to be based on People objects, not popdicts (syntax is exactly the same, although it is recommended to use .ppl instead of .pop for these files).

  • Added additional random seed resets to population initialization and just before the run so that populations loaded from disk produce identical results to newly created ones. Regression information: This affects results by changing the random number stream. In most cases, previous behavior can typically be restored by setting sim.run(reset_seed=False).

  • Added a new convenience method, cv.check_save_info(), which can be put at the top of a script to check the Covasim version and automatically save the Git info to file.

  • Added additional methods to People to retrieve different types of keys: e.g., sim.people.state_keys() returns all the different states a person can be in (e.g., symptomatic).

  • GitHub info: PR 557, previous head aac9f1d

Versions 1.2.x (1.2.0 – 1.2.3)

Version 1.2.3 (2020-05-23)

  • Added cv.savefig(), which is an alias to Matplotlib’s savefig() function, but which saves additional metadata in the figure file. This metadata can be loaded with the new cv.get_png_metdata() function.

  • Major changes to MultiSim plotting, incorporating all the flexibility of both simulation and scenario plotting. By default, with a small number of runs (<= 5), it defaults to scenario-style plotting; else, it defaults to simulation-style plotting.

  • Default scenario plotting options were updated (e.g., showing deaths instead of hospitalizations).

  • You may merge multiple multisims more merrily now, with e.g. msim = cv.MultiSim.merge(msim1, msim2).

  • Test scripts (e.g. tests/run_tests) have been updated to use pytest-parallel, reducing wall-clock time by a factor of 5.

  • GitHub info: PR 552, previous head 28bf02b

Version 1.2.2 (2020-05-22)

  • Changed the syntax of cv.clip_edges() to match cv.change_beta(). The old format of intervention cv.clip_edges(start_day=d1, end_day=d2, change=c) should now be written as cv.clip_edges(days=[d1, d2], changes=[c, 1.0]).

  • Changed the syntax for the transmission tree: it now takes the Sim object rather than the People object, and typical usage is now tt = sim.make_transtree().

  • Plots now default to a maximum of 4 rows; this can be overridden using the n_cols argument, e.g. sim.plot(to_plot='overview', n_cols=2).

  • Various bugs with MultiSim plotting were fixed.

  • GitHub info: PR 551, previous head 07009eb

Version 1.2.1 (2020-05-21)

  • Added influenza-like illness (ILI) symptoms to testing interventions. If nonzero, this reduces the effectiveness of symptomatic testing, because you cannot distinguish between people who are symptomatic with COVID and people with other ILI symptoms.

  • Removed an unneeded copy() in single_run() because multiprocessing always produces copies of objects via the pickling process.

  • GitHub info: PR 541, previous head 9b2dbfb

Version 1.2.0 (2020-05-20)

  • Since parameters can be modified during the run, previously, the sim could not be rerun with the guarantee that the results would be the same. sim.run() now has a restore_pars argument (default true), which makes a copy of the parameters just prior to the run to ensure reproducibility.

  • In plotting, by default, data points are now slightly transparent and behind the lines to improve visibility of the model curve.

  • Interventions now have a label attribute, which can be helpful for finding them if many are used, e.g. [interv if interv.label=='Close schools' for interv in sim['interventions']. There is also a new method, intervention.disp(), which prints out detailed information about an intervention object.

  • Subtargeting of particular people in testing interventions can now be done via a function that gets called dynamically, avoiding the need to initialize the sim prior to creating the intervention.

  • Layer keys are now stored inside the popdict, for greater consistency handling loaded populations. Layer key handling has been simplified and made more robust.

  • Loading and saving a population is now controlled by the Sim object, not by the sim.initialize() method. Instead of sim = cv.Sim(); sim.initialize(save_pop=True), you can now simply do sim = cv.Sim(save_pop=True, and it will save when the sim is initialized.

  • Added prevalence and incidence as results.

  • Added sim.scaled_pop_size, which is the population size (the number of agents) times the population scale factor. This corresponds to the “actual” population size being modeled.

  • Removed the numerical artifact at the beginning and end of the R_eff calculation due to the smoothing kernel, and confirmed that the spike in R_eff often seen at the beginning is due to the way the seed infectious progress from exposed to infectious, and not from a bug.

  • Added more flexibility to plotting, including a new show_args keyword, allowing particular aspects of plotting (e.g., the data or interventions) to be turned on or off.

  • Moved the cruise ship code from the core folder into the examples folder.

  • GitHub info: PR 538, previous head 451f410

Versions 1.1.x (1.1.0 – 1.1.7)

Version 1.1.7 (2020-05-19)

  • Diagnoses are now reported on the day the test was conducted, not the day the person gets their diagnosis. This is to better align with data (which is reported this way), and to avoid a bug in which test yield could be >100%. A new attribute, date_pos_test, was added to the sim.people object in order to track the date on which a person is given the test which will (after test_delay days) come back positive.

  • An “overview” plotting feature has been added for sims and scenarios: simply use sim.plot(to_plot='overview') to use. This plots almost all of the simulation outputs on one screen.

  • It is now possible to set pop_type = None if you are supplying a custom population.

  • Population creation functions (including the People class) have been tidied up with additional docstrings added.

  • Duplication between pre- and post-step state checking has been removed.

  • GitHub info: PR 537, previous head 2d55c38

Version 1.1.6 (2020-05-19)

  • Created an analysis.py file to support different types of analysis.

  • Moved transtree from sim.people into its own class: thus instead of sim.people.make_detailed_transtree(), the new syntax is tt = cv.TransTree(sim.people).

  • GitHub info: PR 531, previous head 998116c

Version 1.1.5 (2020-05-18)

  • Added extra flexibility for targeting interventions by index of a person, for example, by age.

Version 1.1.4 (2020-05-18)

  • Added a new hospital bed capacity constraint and renamed health system capacity parameters. To migrate an older set of parameters to this version, set:

    pars['no_icu_factor']  = pars.pop('OR_no_treat')
    pars['n_beds_icu']     = pars.pop('n_beds')
    pars['no_hosp_factor'] = 1.0
    pars['n_beds_hosp']    = None
  • Removed the bed_capacity result.

  • GitHub info: PR 510, previous head 0f6d48c

Version 1.1.3 (2020-05-18)

  • Improved the how “layer parameters” (e.g., beta_layer) are initialized.

  • Allowed arbitrary arguments to be passed to SynthPops via cv.make_synthpop.

Version 1.1.2 (2020-05-18)

  • Added a new result, test_yield, which is the number of diagnoses divided by the number of cases each day.

  • Minor improvements to date handling and plotting.

Version 1.1.1 (2020-05-13)

  • Refactored the contact tracing and quarantining functions, to fixed a bug (introduced in v1.1.0) in which some people who went into quarantine never came out of quarantine.

  • Changed initialization so seed infections are now sampled randomly from the population, rather than the first pop_infected agents. Since hybrid also uses consecutive indices for constructing households, this was causing some households to be fully infected on initialization, while all other households had no infections.

  • Updated the default rescale_factor from 2.0 to 1.2, since large amounts of rescaling cause noticeable “blips” in inhomogeneous networks (e.g., a population where some households are 100% infected and most are 0% infected).

  • Added ability to pass plotting arguments to intervention.plot().

  • Removed default noise in scenarios (restore previous behavior by setting metapars = dict(noise=0.1)).

  • Refactored and renamed computed results (e.g., summary stats) in the Sim class.

  • GitHub info: PR 513, previous head 973801a

Version 1.1.0 (2020-05-12)

  • Renamed the parameter diag_factor to iso_factor, and converted it to a dictionary by layer.

  • Renamed the parameter quar_eff to quar_factor (but otherwise left it unchanged).

  • Added the option for presumptive isolation and quarantine in testing interventions.

  • Fixed a bug whereby people who had been in quarantine and were then diagnosed had both diagnosis and quarantine factors applied.

  • GitHub info: PR 502, previous head 0230383

Versions 1.0.x (1.0.0 – 1.0.3)

Version 1.0.3 (2020-05-11)

  • Added an extra output of make_microstructured_contacts() to store each person’s cluster identifier. Currently, this is only supported for the hybrid population type, but in future versions, synthpops will also be supported.

  • Removed the directed argument from population creation functions since it is no longer supported in the model.

Version 1.0.2 (2020-05-10)

  • Added uncertainty to the plot_result() method of MultiSims.

  • Added documentation and webapp links to the paper.

Version 1.0.1 (2020-05-09)

  • Added argument as_date for sim.date() to return a datetime object instead of a string.

  • Fixed plotting of interventions in the webapp.

  • Removed default 1-hour time limit for simulations.

  • GitHub info: PR 490, previous head 9a6c23b

Version 1.0.0 (2020-05-08)

  • Official release of Covasim.

  • Made scenario and simulation plotting more flexible: to_plot can now simply be a list of results keys, e.g. cum_deaths.

  • Added additional tests, increasing test coverage from 67% to 92%.

  • Fixed bug in cv.save().

  • Added reset() to MultiSim that undoes a reduce() or combine() call.

  • General code cleaning: made exceptions raised more consistent, removed unused functions, etc.

  • GitHub info: PR 487, previous head c8ca32d

Prerelease versions (0.27.0 – 0.32.1)

Version 0.32.1 (2020-05-06)

  • Allow until to be a date, e.g. sim.run(until='2020-05-06').

  • Added ipywidgets dependency since otherwise the webapp breaks due to a bug with the latest Plotly version (4.7).

Version 0.32.0 (2020-05-05)

  • Changed the edges of the contact network from being directed to undirected, halving the amount of memory required and making contact tracing and edge clipping more realistic.

  • Added comorbidities to the prognoses parameters.

  • GitHub info: PR 482, previous head 029585f

Version 0.31.0 (2020-05-05)

  • Added age-susceptible odds ratios, and modified severe and critical progression probabilities. To compensate, default beta has been increased from 0.015 to 0.016. To restore previous behavior (which was based on the Imperial paper), set beta=0.015 and set the following values in sim.pars['prognoses']:

    sus_ORs[:]   = 1.0
    severe_probs = np.array([0.00100, 0.00100, 0.01100, 0.03400, 0.04300, 0.08200, 0.11800, 0.16600, 0.18400])
    crit_probs   = np.array([0.00004, 0.00011, 0.00050, 0.00123, 0.00214, 0.00800, 0.02750, 0.06000, 0.10333])
  • Relative susceptibility and transmissibility (i.e., sim.people.rel_sus) are now set when the population is initialized (before, they were modified dynamically when a person became infected or recovered). This means that modifying them before a simulation starts, or during a simulation, should be more robust.

  • Reordered results dictionary to start with cumulative counts.

  • sim.export_pars() now accepts a filename to save to.

  • Added a tests/regression folder with previous versions of default parameter values.

  • Changed pars['n_beds'] to interpret 0 or None as no bed constraint.

  • GitHub info: PR 480, previous head c7171f8

Version 0.30.4 (2020-05-04)

  • Changed the detailed transmission tree (sim.people.transtree.detailed) to include much more information.

  • Added animation method to transmission tree: sim.people.transtree.animate().

  • Added support to generate populations on the fly in SynthPops.

  • Adjusted the default arguments for test_prob and fixed a bug with test_num not accepting date input.

  • Added tests/devtests/intervention_showcase.py, using and comparing all available interventions.

Version 0.30.3 (2020-05-03)

  • Fixed bugs in dynamic scaling; see tests/devtests/dev_test_rescaling.py. When using pop_scale>1, the recommendation is now to use rescale=True.

  • In cv.test_num(), renamed argument from sympt_test to symp_test for consistency.

  • Added plot_compare() method to MultiSim.

  • Added labels arguments to plotting methods, to allow custom labels to be used.

Version 0.30.2 (2020-05-02)

  • Updated r_eff to use a new method based on daily new infections. The previous version, where infections were counted from when someone recovered or died, is available as sim.compute_r_eff(method='outcome'), while the traditional method, where infections are counted from the day someone becomes infectious, is available via sim.compute_r_eff(method='infectious').

Version 0.30.1 (2020-05-02)

  • Added end_day as a parameter, allowing an end date to be specified instead of a number of days.

  • Sim.run() now displays the date being simulated.

  • Added a par_args argument to multi_run(), allowing arguments (e.g. ncpus) to be passed to sc.parallelize().

  • Added a compare() method to multisims and stopped people from being saved by default.

  • Fixed bug whereby intervention were not getting initialized if they were added to a sim after it was initialized.

Version 0.30.0 (2020-05-02)

  • Added new MultiSim class for plotting a single simulation with uncertainty.

  • Added low and high attributes to the Result object.

  • Refactored plotting to increase consistency between sim.plot(), sim.plot_result(), scens.plot(), and multisim.plot().

  • Doubling time calculation defaults have been updated to use a window of 3 days and a maximum of 30 days.

  • Added an until argument to sim.run(), to make it easier to run a partially completed sim and then resume. See tests/devtests/test_run_until.py.

  • Fixed a bug whereby cv.clip_edges() with no end day specified resulted in large sim files when saved.

Version 0.29.9 (2020-04-28)

  • Fixed bug in which people who had been tested and since recovered were not being diagnosed.

  • Updated definition of “Time to die” parameter in the webapp.

Version 0.29.8 (2020-04-28)

  • Updated webapp UI with more detail on and control over interventions.

Version 0.29.7 (2020-04-27)

  • New functions cv.date() and cv.daydiff() have been added, to ease handling of dates of different formats.

  • Defaults are now functions rather than dictionaries, specifically: cv.default_sim_plots is now cv.get_sim_plots(); cv.default_scen_plots is now cv.get_scen_plots(); and cv.default_colors is now cv.get_colors().

  • Interventions now have a do_plot kwarg, which if False will disable their plotting.

  • The example scenario (examples/run_scenario.py) has been rewritten to include a test-trace-quarantine example.

Version 0.29.6 (2020-04-27)

  • Updated to use Sciris v0.17.0, to fix JSON export issues and improve KeyError messages.

Version 0.29.5 (2020-04-26)

  • Fixed bug whereby layer betas were applied twice, and updated default values.

  • Includes individual-level viral load (to use previous results, set pars['beta_dist'] = {'dist':'lognormal','par1':1.0, 'par2':0.0} and pars['viral_dist']  = {'frac_time':0.0, 'load_ratio':1, 'high_cap':0}).

  • Updated parameter values (mostly durations) based on revised literature review.

  • Added sim.export_pars() and sim.export_results() methods.

  • Interventions can now be converted to/from JSON – automatically when loading a parameters dictionary into a sim, or manually using cv.InterventionDict().

  • Improvements to transmission trees: can now make a detailed tree with sim.people.make_detailed_transtree() (replacing sim.people.transtree.make_detailed(sim.people)), and can plot via sim.people.transtree.plot().

  • Improved date handling, so most functions are now agnostic as to whether a date string, datetime object, or number of days is provided; new functions: sim.day() converts dates to days, sim.date() (formerly sim.inds2dates()) converts days to dates, and sim.daydiff() computes the number of days between two dates.

Version 0.28.8 (2020-04-24)

  • Includes data on household sizes from various countries.

  • Includes age data on US states.

  • Changes to interventions to include end as well as start days, and plotting as a default option.

  • Adds version checks to loading and introduces a new function cv.load() to replace e.g. cv.Sim.load().

  • Major layout and functionality changes to the webapp, including country selection (disabled by default).

  • Provided access to Plotly graphs via the backend.

  • Moved relative probabilities (e.g. rel_death_prob) from population creation to loop so can be modified dynamically.

  • Introduced cv.clip_edges() intervention, similar to cv.change_beta() but removes contacts entirely.

Version 0.28.1 (2020-04-19)

  • Major refactor of transmission trees, including additional detail via sim.people.transtree.make_detailed().

  • Counting of diagnoses before and after interventions on each timestep (allowing people to go into quarantine on the same day).

  • Improved saving of people in scenarios, and updated keyword for sims (sim.save(keep_people=True)).

Version 0.28.0 (2020-04-19)

  • Includes dynamic per-person viral load.

  • Refactored data types.

  • Changed how populations are handled, including adding a dynam_layer parameter to specify which layers are dynamic.

  • Disease progression duration parameters were updated to be longer.

  • Fixed bugs with quarantine.

  • Fixed bug with hybrid school and work contacts.

  • Changed contact tracing to be only for contacts with nonzero transmission.

Version 0.27.12 (2020-04-17)

  • Caches Numba functions, reducing load time from 2.5 to 0.5 seconds.

  • Pins Numba to 0.48, which is 10x faster than 0.49.

  • Fixed issue with saving populations in scenarios.

  • Refactored how populations are handled, removing use_layers parameter (use pop_type instead).

  • Removed layer key from layer object, reducing total sim memory footprint by 3x.

  • Improved handling of mismatches between loaded population layers and simulation parameters.

  • Added custom key errors to handle multiline error messages.

  • Fix several issues with probability-based testing.

  • Changed how layer betas are applied (inside the sim rather than statically).

  • Added more detail to the transmission tree.

  • Refactored random population calculation, speeding up large populations (>100k) by a factor of 10.

  • Added documentation.

Version 0.27.0 (2020-04-16)

  • Refactor calculations to be vector-based rather than object based.

  • Include factors for per-person viral load (transmissibility) and susceptibility.

  • Started a changelog (needless to say).