Merge remote-tracking branch 'origin/feature/mc' into feature/mc

# Conflicts:
#	cara/mc-output.py

cara/mc-output-publication.py

@@ -0,0 +1,44 @@
+""" Title: COVID Airborne Risk Assessment
+Author: <author(s) names>
+Date: <date>
+Code version: <code version>
+Availability: <where it's located> """
+
+from cara.montecarlo import *
+from cara.model_scenarios_publication import *
+
+# qR table:
+generate_qr_csv('qR_unmasked')
+generate_qr_csv('qr_masked', masked=True)
+
+# qR values for Breathing, light activity:
+print('\n<<<<<<<<<<< qR for Breathing, light activity >>>>>>>>>>>')
+present_qR_values(qR_models[0].concentration_model)
+# qR values for Speaking, light activity:
+print('\n<<<<<<<<<<< qR for Speaking, light activity >>>>>>>>>>>')
+present_qR_values(qR_models[1].concentration_model)
+# qR values for Shouting, light activity:
+print('\n<<<<<<<<<<< qR for Shouting / Singing, light activity >>>>>>>>>>>')
+present_qR_values(qR_models[2].concentration_model)
+
+# qR values for shouting and light activity - qID=100, 500 and 1000
+print('\n<<<<<<<<<<< Shouting and light activity - qID=100 >>>>>>>>>>>')
+present_qR_values(qR_models_shout_light[0].concentration_model)
+print('\n<<<<<<<<<<< Shouting and light activity - qID=500 >>>>>>>>>>>')
+present_qR_values(qR_models_shout_light[1].concentration_model)
+print('\n<<<<<<<<<<< Shouting and light activity - qID=1000 >>>>>>>>>>>')
+present_qR_values(qR_models_shout_light[2].concentration_model)
+print('\n<<<<<<<<<<<<<<<<<>>>>>>>>>>>>>>>>>>>>')
+
+present_model(qR_models[2].concentration_model, title='')
+
+# qR for the S V Chorale superspreading event
+print('\n<<<<<<<<<<< S V Chorale: Shouting and light activity - qID=100 >>>>>>>>>>>')
+present_qR_quantiles(qR_models_shout_light[0].concentration_model, quantile=0.8)
+
+# CDF plots of qR
+generate_cdf_curves_vs_qr(masked=False,qid=100)
+generate_cdf_curves_vs_qr(masked=False,qid=500)
+generate_cdf_curves_vs_qr(masked=False,qid=1000)
+
+

cara/mc-output.py

@@ -0,0 +1,123 @@
+from cara.montecarlo import *
+from cara.model_scenarios import *
+
+#compare_concentration_curves([classroom_model_with_hepa[0],classroom_model_full_open_multi[0]],['xxx', 'yyy'])
+
+#plot_concentration_curve(classroom_model[1])
+#compare_concentration_curves([classroom_model, classroom_model_with_hepa], ['Just window', 'Window and HEPA'])
+
+#print(np.mean(classroom_model[0].infection_probability()))
+#print(np.mean(classroom_model[1].infection_probability()))
+#print(np.mean(chorale_model.infection_probability())+np.std(chorale_model.infection_probability()))
+#print(np.quantile(chorale_model[0].infection_probability(),0.8))
+#print(np.quantile(chorale_model.infection_probability(),0.90))
+#print(np.quantile(chorale_model.infection_probability(),0.1))
+
+#plot_pi_vs_exposure_time(chorale_model, ['model1', 'model2'])
+#print(np.mean(ski_cabin_model_baseline_20[1].infection_probability()))
+#plot_pi_vs_exposure_time(ski_cabin_model_baseline_exposure_time+ski_cabin_model_baseline_exposure_time_FFP2, ['Ski cabin - surgical masks', 'Ski cabin - no masks','Ski cabin - FFP2 masks',''],
+#                         colors=['#1f77b4','tomato', 'seagreen', 'seagreen'],
+#                         linestyles=['solid', 'dashed', '-.', '-.'],
+#                         points=20,
+#                         time_in_minutes=True,
+#                         normalize_y_axis=True)
+
+#compare_viruses_qr(violins=True)
+present_qR_values(classroom_model[1].concentration_model)
+#print_qd_info(waiting_room_model_full_winter[1])
+
+#print(np.mean(shared_office_model[1].infection_probability()))
+#composite_plot_pi_vs_viral_load([shared_office_worst_model[1], shared_office_model[1], shared_office_better_model[1]],
+#                                 labels=['No mask &\nwindows closed', 'Baseline:Windows\nopen (10min/2h)', 'Windows open\n(10min/2h) +\nHEPA filter'],
+#                                 colors=['tomato', '#1f77b4', 'limegreen'],
+#                                 title='',
+#  plot_pi_vs_viral_load                               vl_points=200)
+#composite_plot_pi_vs_viral_load([classroom_model_no_vent[1], classroom_model[1], classroom_model_with_hepa[1], classroom_model_full_open_multi[1], classroom_model_full_open_multi_masks[1]],
+#                                 labels=['Windows closed', 'Baseline:Windows\nopen (10min/2h)', 'Windows open\n(10min/2h) + HEPA', 'Multiple windows open', 'Multiple windows open\n+masks'],
+#                                 colors=['tomato','#1f77b4', 'dodgerblue', 'seagreen', 'limegreen'],
+#                                 title='',
+#                                 vl_points=200)
+
+#composite_plot_pi_vs_viral_load([ski_cabin_model_60[1], ski_cabin_model_30[1], ski_cabin_model_baseline_20[1], ski_cabin_model_10[1]],
+#                                 labels=['60 min', '30 min', 'Baseline: 20 min', '10 min'],
+#                                 colors=['tomato', 'lightsalmon', '#1f77b4', 'limegreen'],
+#                                 title='',
+#                                 vl_points=200)
+#
+#composite_plot_pi_vs_viral_load([ski_cabin_model_baseline_20_no_mask[1], ski_cabin_model_baseline_20[1], ski_cabin_model_baseline_20_FFP2[1]],
+#                                 labels=['20min\nno masks', 'Baseline: 20 min\nsurgical mask', '20 min\nFFP2 mask'],
+#                                 colors=['tomato', '#1f77b4','seagreen'],
+#                                 title='',
+#                                 vl_points=200)
+
+#compare_concentration_curves([classroom_model_no_vent[1], classroom_model[1], classroom_model_with_hepa[1], classroom_model_full_open_multi[1]],
+#                             labels=['Windows closed', 'Baseline: Windows open (10min/2h)', 'Windows open (10min/2h) + HEPA', 'Multiple windows open'],
+#                             colors=['tomato','#1f77b4', 'seagreen', 'limegreen'],
+#                             title=''
+#                             )
+
+#compare_concentration_curves_virus_IGH_paper([classroom_model_no_vent[1], classroom_model[1], classroom_model_with_hepa[1], classroom_model_full_open_multi[1]],
+#                             labels=['Windows closed', 'Baseline: Windows open (10min/2h)', 'Windows open (10min/2h) + HEPA', 'Multiple windows open'],
+#                             colors=['tomato','#1f77b4', 'seagreen', 'limegreen'],
+#                             title=''
+#                             )
+#
+#compare_concentration_curves([waiting_room_model[1], waiting_room_model_full_summer[1],
+#                              waiting_room_model_full_winter[1], waiting_room_model_periodic_winter[1]],
+#                             labels=['Baseline: Windows closed', 'Windows open (summer)', 'Windows open (winter)', 'Windows open 5min/20min (winter)'],
+#                             colors=['#1f77b4', 'darkorange', 'deepskyblue', 'lightskyblue'],
+#                             title=''
+#                             )
+
+#compare_concentration_curves_virus_IGH_paper([waiting_room_model[1], waiting_room_model_full_summer[1],
+#                              waiting_room_model_full_winter[1], waiting_room_model_periodic_winter[1]],
+#                             labels=['Baseline: Windows closed', 'Windows open (summer)', 'Windows open (winter)', 'Windows open 5min/20min (winter)'],
+#                             colors=['#1f77b4', 'darkorange', 'deepskyblue', 'lightskyblue'],
+#                             title=''
+#                             )
+
+#plot_pi_vs_viral_load([classroom_model_no_vent[1]], labels=['Windows closed'],title='')
+#plot_pi_vs_viral_load([classroom_model_no_vent[1],classroom_model_full_open_multi_masks[1]], labels=['Windows closed','Multiple windows open + Masks'],title='')
+
+#generate_cdf_curves_vs_qr(masked=False,qid=1000)
+
+# rs = [model.expected_new_cases() for model in large_population_baselines]
+# print(f"R0 - original variant:\t{np.mean(rs[0])}")
+# print(f"R0 - english variant:\t{np.mean(rs[1])}")
+# print(f"Ratio between R0's:\t\t{np.mean(rs[1]) / np.mean(rs[0])}")
+#
+# compare_infection_probabilities_vs_viral_loads(*exposure_models)
+#
+#
+#present_model(exposure_models[0].concentration_model, title='')
+# plot_pi_vs_qid(fixed_vl_exposure_models, labels=['Viral load = $10^{' + str(i) + '}$' for i in range(6, 11)],
+#                qid_min=5, qid_max=2000, qid_samples=200)
+#
+# plot_pi_vs_qid(fixed_vl_exposure_models, labels=['Viral load = $10^{' + str(i) + '}$' for i in range(6, 11)],
+#                qid_min=100, qid_max=400, qid_samples=100)
+#
+#
+# plot_pi_vs_viral_load(exposure_models, labels=['Without masks', 'With masks'])
+#
+# for model in exposure_models:
+#     present_model(model.concentration_model, title=f'Model summary - {"English" if model.concentration_model.infected.qid == 60 else "Original"} variant')
+#     plt.hist(model.infection_probability(), bins=200)
+#     plt.xlabel('Percentage probability of infection')
+#     plt.title(f'Probability of infection in baseline case - {"English" if model.concentration_model.infected.qid == 60 else "Original"} variant')
+#     plt.yticks([], [])
+#     plt.show()
+
+#composite_plot_pi_vs_viral_load([classroom_model_no_vent[1],classroom_model_full_open_multi_masks[1]],
+#                                 labels=['Windows closed','Multiple windows open + Masks'],
+#                                 colors=['#1f77b4','#ff7f0e'],
+#                                 title='',
+#                                 vl_points=500)
+#
+#compare_concentration_curves_virus_IGH_paper([classroom_model_no_vent[1], classroom_model[1], classroom_model_with_hepa[1], classroom_model_full_open_multi[1]],
+#                             labels=['Windows closed', 'Windows open (for 10min every 2h)', 'Windows open (for 10min every 2h) + HEPA', 'Multiple windows open (at all times)'],
+#                             colors=['tomato','#1f77b4', 'seagreen', 'limegreen'],
+#                             title='Mean concentration of infectious quantum and\ncumulative dose over exposure time'
+#                             )
+
+#generate_qr_csv('qR_unmasked')
+#generate_qr_csv('qr_masked', masked=True)

cara/mc-output_IGH_paper.py

@@ -0,0 +1,232 @@
+from cara.montecarlo import *
+from cara.model_scenarios_IGH_paper import *
+
+# #Fig 1c
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_no_mask_windows_open_breaks[0],
+#                              classroom_model_IGH_no_mask_windows_open_alltimes[0]],
+#                             labels=['Windows closed', 'Window open during breaks', 'Window open at all times'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1c ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_open_breaks[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_open_alltimes[0])
+#
+# #Fig 1d
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_no_mask_windows_open_breaks_winter[0],
+#                              classroom_model_IGH_no_mask_windows_open_alltimes_winter[0], classroom_model_IGH_no_mask_windows_fully_open_alltimes_winter[0]],
+#                             labels=['Windows closed', 'Window fully open during breaks', 'Window slightly open at all times', 'Window fully open at all times'],
+#                             colors=['tomato', 'lightskyblue', '#1f77b4', 'limegreen', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1d ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_open_breaks_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_open_alltimes_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_fully_open_alltimes_winter[0])
+#
+# #Fig 1e
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_no_mask_2windows_open_breaks[0],
+#                              classroom_model_IGH_no_mask_2windows_open_alltimes[0]],
+#                             labels=['Windows closed', '2 windows open during breaks', '2 windows open at all times'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1e ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_breaks[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_alltimes[0])
+#
+# #Fig 1f
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_no_mask_2windows_open_breaks_winter[0],
+#                              classroom_model_IGH_no_mask_2windows_open_alltimes_winter[0], classroom_model_IGH_no_mask_2windows_fully_open_alltimes_winter[0]],
+#                             labels=['Windows closed', '2 windows fully open during breaks', '2 windows slighty open at all times', '2 windows fully open at all times'],
+#                             colors=['tomato', 'lightskyblue', '#1f77b4', 'limegreen', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1f ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_breaks_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_alltimes_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_fully_open_alltimes_winter[0])
+#
+# #Fig 1g
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_no_mask_6windows_open_breaks[0],
+#                              classroom_model_IGH_no_mask_6windows_open_alltimes[0]],
+#                             labels=['Windows closed', '6 windows open during breaks', '6 windows open at all times'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1g ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_alltimes[0])
+#
+# #Fig 1h
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_no_mask_6windows_open_breaks_winter[0],
+#                              classroom_model_IGH_no_mask_6windows_open_alltimes_winter[0], classroom_model_IGH_no_mask_6windows_fully_open_alltimes_winter[0]],
+#                             labels=['Windows closed', '6 windows fully open during breaks', '6 windows slighty open at all times', '6 windows fully open at all times'],
+#                             colors=['tomato', 'lightskyblue', '#1f77b4', 'limegreen', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1h ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_alltimes_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_fully_open_alltimes_winter[0])
+#
+# #Fig 1i
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],
+#                             classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass[0]],
+#                             labels=['Windows closed',
+#                                     '6 windows open during breaks + end of classes'],
+#                             colors=['tomato', '#1f77b4'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1i ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass[0])
+#
+# #Fig 1j
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],
+#                             classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass_winter[0]],
+#                             labels=['Windows closed',
+#                                     '6 windows open during breaks + end of classes'],
+#                             colors=['tomato', '#1f77b4'],
+#                             title=''
+#                             )
+# print("\n############ Fig 1j ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass_winter[0])
+#
+#
+#
+# #Fig 2a
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_no_mask_windows_closed_1HEPA[0],
+#                              classroom_model_IGH_no_mask_windows_closed_2HEPA[0]],
+#                             labels=['Windows closed', 'Windows closed + 1 HEPA filter (2.5 ACH)', 'Windows closed + 2 HEPA filter (5 ACH)'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 2a ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_1HEPA[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_2HEPA[0])
+#
+# #Fig 2b
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_no_mask_windows_closed_1HEPA_winter[0],
+#                              classroom_model_IGH_no_mask_windows_closed_2HEPA_winter[0]],
+#                             labels=['Windows closed', 'Windows closed + 1 HEPA filter (2.5 ACH)', 'Windows closed + 2 HEPA filter (5 ACH)'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 2b ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_1HEPA_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_2HEPA_winter[0])
+#
+# #Fig 2c
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_with_mask_windows_closed[0]],
+#                             labels=['Windows closed', 'Windows closed + surgical type masks'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 2c ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_with_mask_windows_closed[0])
+#
+# #Fig 2d
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_with_mask_windows_closed_winter[0]],
+#                             labels=['Windows closed', 'Windows closed + surgical type masks'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 2d ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_with_mask_windows_closed_winter[0])
+#
+#
+# #Fig 3b
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_no_mask_2windows_open_alltimes_winter_bis[0],
+#                              classroom_model_IGH_with_mask_2windows_open_alltimes_winter[0]],
+#                             labels=['Windows closed', '2 windows open at all times', '2 windows open at all times + surgical masks'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 3b ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_alltimes_winter_bis[0])
+# print_qd_info(classroom_model_IGH_with_mask_2windows_open_alltimes_winter[0])
+#
+# #Fig 3c
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_with_mask_windows_closed_1HEPA[0],
+#                               classroom_model_IGH_with_mask_windows_closed_2HEPA[0]],
+#                              labels=['No masks', '1 HEPA filter (2.5 ACH) + surgical masks', '2 HEPA filter (5 ACH) + surgical masks'],
+#                              colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                              title=''
+#                              )
+# print("\n############ Fig 3c ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+# print_qd_info(classroom_model_IGH_with_mask_windows_closed_1HEPA[0])
+# print_qd_info(classroom_model_IGH_with_mask_windows_closed_2HEPA[0])
+#
+# #Fig 3d
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed_winter[0],classroom_model_IGH_with_mask_2windows_open_alltimes_winter_1HEPA[0],
+#                              classroom_model_IGH_with_mask_2windows_open_alltimes_winter_2HEPA[0]],
+#                             labels=['Windows closed', '2 windows open at all times + 1 HEPA filter (2.5 ACH) + surgical masks', '2 windows open at all times + 2 HEPA filter (5 ACH) + surgical masks'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title=''
+#                             )
+# print("\n############ Fig 3d ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_closed_winter[0])
+# print_qd_info(classroom_model_IGH_with_mask_2windows_open_alltimes_winter_1HEPA[0])
+# print_qd_info(classroom_model_IGH_with_mask_2windows_open_alltimes_winter_2HEPA[0])
+#
+#
+# #Hourly breaks
+# print("\n############ Hourly breaks - summer ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_open_breaks_endOfClass[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_breaks_endOfClass[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass[0])
+#
+# print("\n############ Hourly breaks - winter ###########\n")
+# print_qd_info(classroom_model_IGH_no_mask_windows_open_breaks_endOfClass_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_2windows_open_breaks_endOfClass_winter[0])
+# print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass_winter[0])
+
+
+
+#>>>>>>>>>>> Aux >>>>>>>>
+
+
+#print_qd_info(classroom_model_IGH_no_mask_windows_closed[0])
+#print_qd_info(classroom_model_IGH_no_mask_6windows_open_breaks_endOfClass[0])
+#print_qd_info(classroom_model_IGH_no_mask_2windows_open_breaks_endOfClass_winter[0])
+#print_qd_info(classroom_model_IGH_no_mask_windows_open_breaks_endOfClass_winter[0])
+
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_no_mask_2windows_open_breaks_winter_bis[0],
+#                              classroom_model_IGH_with_mask_2windows_open_breaks_winter[0]],
+#                             labels=['Windows closed', '2 windows open during breaks', '2 windows open during breaks + surgical masks'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title='Combination of measures (winter period) '
+#                             )
+
+# compare_concentration_curves_virus_IGH_paper([classroom_model_IGH_no_mask_windows_closed[0],classroom_model_IGH_with_mask_2windows_open_breaks_winter_1HEPA[0],
+#                              classroom_model_IGH_with_mask_2windows_open_breaks_winter_2HEPA[0]],
+#                             labels=['Windows closed', '2 windows open during breaks + 1 HEPA filter (2.5 ACH) + surgical masks', '2 windows open during breaks + 2 HEPA filter (5 ACH) + surgical masks'],
+#                             colors=['tomato', 'lightskyblue', 'limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title='Combination of measures (winter period) '
+#                             )
+
+#compare_concentration_curves([classroom_model_IGH_no_mask_windows_closed[1],classroom_model_IGH_no_mask_2windows_open_breaks[1],classroom_model_IGH_no_mask_2windows_open_breaks_endOfClass[1],
+#                              classroom_model_IGH_no_mask_2windows_open_alltimes[1], classroom_model_IGH_no_mask_windows_closed_1HEPA[1],
+#                              classroom_model_IGH_no_mask_windows_closed_2HEPA[1]],
+#                             labels=['Windows closed', '2 Windows open during breaks', '2 Windows open during breaks + end of classes',
+#                                     '2 Windows open at all times', 'Windows closed + HEPA filter (2.5 ACH)', 'Windows closed + HEPA filter (5 ACH)'],
+#                             colors=['tomato','limegreen', '#1f77b4', 'seagreen', 'lightskyblue', 'deepskyblue'],
+#                             title='No mask - Spring/Summer period'
+#                             )
+
+#present_model(classroom_model_IGH_no_mask_windows_closed[0].concentration_model, title='')
+

cara/model_scenarios.py

@@ -0,0 +1,947 @@
+from cara import models
+from cara.montecarlo import *
+
+
+fixed_vl_exposure_models = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=45),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=10),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 4), (5, 9))),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=100),
+            expiratory_activity=1,
+            samples=2000000,
+            breathing_category=1,
+            viral_load=float(vl)
+        )
+    ),
+    exposed=models.Population(
+        number=2,
+        presence=models.SpecificInterval(((0, 4), (5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['Type I']
+    )
+) for vl in range(6, 11)]
+
+
+large_population_baselines = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=800),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=2000.
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 4), (5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=1,
+            samples=200000,
+            breathing_category=2,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+
+    ),
+    exposed=models.Population(
+        number=60,
+        presence=models.SpecificInterval(((0, 4), (5, 9))),
+        activity=models.Activity.types['Standing'],
+        mask=models.Mask.types['No mask']
+    )
+) for qid in (100, 60)]
+
+######### Standard exposure models ###########
+exposure_models = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=45),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.2,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 4), (5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=3,
+            samples=2000000,
+            breathing_category=3,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=2,
+        presence=models.SpecificInterval(((0, 4), (5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['Type I']
+    )
+) for qid in (100, 60)]
+
+exposure_models_2 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=33),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 4), (5, 9))),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=4,
+            samples=2000000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.1, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=2,
+        presence=models.SpecificInterval(((0, 4), (5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['Type I']
+    )
+) for qid in (100, 60)]
+
+######## Classroom exposure models ###########
+classroom_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=10),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_full_open = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_summer = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=10),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (291,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_full_open_summer = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (291,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_no_vent = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.AirChange(
+            active=models.PeriodicInterval(period=120, duration=120),
+            air_exch=0.25,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_teacher_mask_full_open = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (291,)),
+            window_height=1.6, opening_length=4*0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=True,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_with_hepa = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.MultipleVentilation(
+            ventilations=(
+                models.SlidingWindow(
+                            active=models.PeriodicInterval(period=120, duration=10),
+                            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+                            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+                            window_height=1.6, opening_length=0.6,
+                        ),
+                models.HEPAFilter(active=models.PeriodicInterval(period=120, duration=120),
+                                 q_air_mech=800)
+            )
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_full_open_multi = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.MultipleVentilation(
+            ventilations=(
+                models.SlidingWindow(
+                            active=models.PeriodicInterval(period=120, duration=120),
+                            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+                            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+                            window_height=1.6, opening_length=4*0.6,
+                        ),
+                models.HEPAFilter(active=models.PeriodicInterval(period=120, duration=120),
+                                 q_air_mech=0)
+            )
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+classroom_model_full_open_multi_masks = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=160),
+        ventilation=models.MultipleVentilation(
+            ventilations=(
+                models.SlidingWindow(
+                            active=models.PeriodicInterval(period=120, duration=120),
+                            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+                            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+                            window_height=1.6, opening_length=4*0.6,
+                        ),
+                models.HEPAFilter(active=models.PeriodicInterval(period=120, duration=120),
+                                 q_air_mech=0)
+            )
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+            masked=True,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=3,
+        )
+    ),
+    exposed=models.Population(
+        number=19,
+        presence=models.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['Type I']
+    )
+)for qid in (100, 60)]
+
+######### Shared office exposure models ###########
+shared_office_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=50),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=10),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+            masked=True,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['Type I']
+    )
+) for qid in (100, 60)]
+
+shared_office_model_no_mask = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=50),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=10),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+) for qid in (100, 60)]
+
+shared_office_worst_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=50),
+        ventilation=models.AirChange(
+            active=models.PeriodicInterval(period=120, duration=120),
+            air_exch=0.25,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+) for qid in (100, 60)]
+
+shared_office_better_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=50),
+        ventilation=models.MultipleVentilation(
+            ventilations=(
+                models.SlidingWindow(
+                    active=models.PeriodicInterval(period=120, duration=10),
+                    inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+                    outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+                    window_height=1.6, opening_length=0.6,
+                ),
+                models.AirChange(active=models.PeriodicInterval(period=120, duration=120),
+                                 air_exch=5.)
+            )
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+            masked=True,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['Type I']
+    )
+) for qid in (100, 60)]
+
+######### Ski cabine exposure models ###########
+ski_cabin_model_10 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 10/60),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 10/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['Type I']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_baseline_20 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 20/60),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 20/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['Type I']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_baseline_20_FFP2 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 20/60),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 20/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['FFP2']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_baseline_20_no_mask = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 20/60),)),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 20/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_25 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 25/60),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 25/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['Type I']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_30 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 30/60),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 30/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['Type I']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_60 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 1),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 1),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['Type I']
+    )
+)for qid in (100, 60)]
+
+ski_cabin_model_baseline_exposure_time = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 60/60),)),
+            masked=mi,
+            virus=MCVirus(halflife=1.1, qID=60),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 60/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types[me]
+    )
+)for mi, me in zip((True, False), ('Type I', 'No mask', 'FFP2'))]
+
+ski_cabin_model_baseline_exposure_time_FFP2 = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=10),
+        ventilation=models.HVACMechanical(
+            active=models.PeriodicInterval(period=120, duration=120),
+            q_air_mech=0.,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 60/60),)),
+            masked=True,
+            virus=MCVirus(halflife=1.1, qID=60),
+            expiratory_activity=2,
+            samples=200000,
+            breathing_category=4,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=3,
+        presence=models.SpecificInterval(((0, 60/60),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['FFP2']
+    )
+)for mi in (True, False)]
+
+######### Gym exposure models ###########
+gym_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=300),
+        ventilation=models.AirChange(
+            active=models.PeriodicInterval(period=120, duration=120),
+            air_exch=6.,
+        ),
+        infected=MCInfectedPopulation(
+            number=2,
+            presence=models.SpecificInterval(((0, 1),)),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=1,
+            samples=200000,
+            breathing_category=5,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=28,
+        presence=models.SpecificInterval(((0, 1),)),
+        activity=models.Activity.types['Heavy exercise'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+gym_model_exposure_time = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=300),
+        ventilation=models.AirChange(
+            active=models.PeriodicInterval(period=120, duration=120),
+            air_exch=6.,
+        ),
+        infected=MCInfectedPopulation(
+            number=2,
+            presence=models.SpecificInterval(((0, 1),)),
+            masked=mi,
+            virus=MCVirus(halflife=1.1, qID=60),
+            expiratory_activity=1,
+            samples=200000,
+            breathing_category=5,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=28,
+        presence=models.SpecificInterval(((0, 1),)),
+        activity=models.Activity.types['Heavy exercise'],
+        mask=models.Mask.types[me]
+    )
+)for mi, me in zip((True, False), ('Type I', 'No mask'))]
+
+######### Waiting room exposure models ###########
+waiting_room_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=100),
+        ventilation=models.AirChange(
+            active=models.PeriodicInterval(period=120, duration=120),
+            air_exch=0.25,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2),)),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=14,
+        presence=models.SpecificInterval(((0, 2),)),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+waiting_room_model_full_winter = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=100),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2),)),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=14,
+        presence=models.SpecificInterval(((0, 2),)),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+waiting_room_model_full_summer = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=100),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (291,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2),)),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=14,
+        presence=models.SpecificInterval(((0, 2),)),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+waiting_room_model_periodic_winter = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=100),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=20, duration=5),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2),)),
+            masked=False,
+            virus=MCVirus(halflife=3.8, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=14,
+        presence=models.SpecificInterval(((0, 2),)),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+waiting_room_model_periodic_summer = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=100),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=60, duration=10),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (291,)),
+            window_height=1.6, opening_length=0.6,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2),)),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=4,
+            samples=200000,
+            breathing_category=1,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=14,
+        presence=models.SpecificInterval(((0, 2),)),
+        activity=models.Activity.types['Seated'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]
+
+######### S V Chorale exposure models ###########
+chorale_model = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=810),
+        ventilation=models.AirChange(
+            active=models.PeriodicInterval(period=120, duration=120),
+            air_exch=0.7,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 2.5),)),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=3,
+            samples=20000,
+            breathing_category=3,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=60,
+        presence=models.SpecificInterval(((0, 2.5),)),
+        activity=models.Activity.types['Moderate activity'],
+        mask=models.Mask.types['No mask']
+    )
+)for qid in (100, 60)]

cara/model_scenarios_publication.py

@@ -0,0 +1,59 @@
+from cara import models
+from cara.montecarlo import *
+
+######### Standard exposure models ###########
+qR_models = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=45),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.2,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 4), (5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=100),
+            expiratory_activity=a,
+            samples=2000000,
+            breathing_category=3,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=2,
+        presence=models.SpecificInterval(((0, 4), (5, 9))),
+        activity=models.Activity.types['Light activity'],
+        mask=models.Mask.types['No mask']
+    )
+) for a in (1, 2, 3)]
+
+qR_models_shout_light = [MCExposureModel(
+    concentration_model=MCConcentrationModel(
+        room=models.Room(volume=45),
+        ventilation=models.SlidingWindow(
+            active=models.PeriodicInterval(period=120, duration=120),
+            inside_temp=models.PiecewiseConstant((0, 24), (293,)),
+            outside_temp=models.PiecewiseConstant((0, 24), (283,)),
+            window_height=1.6, opening_length=0.2,
+        ),
+        infected=MCInfectedPopulation(
+            number=1,
+            presence=models.SpecificInterval(((0, 4), (5, 9))),
+            masked=False,
+            virus=MCVirus(halflife=1.1, qID=qid),
+            expiratory_activity=3,
+            samples=2000000,
+            breathing_category=3,
+            expiratory_activity_weights=(0.7, 0.3, 0)
+        )
+    ),
+    exposed=models.Population(
+        number=2,
+        presence=models.SpecificInterval(((0, 4), (5, 9))),
+        activity=models.Activity.types['Light activity'],
+        mask=models.Mask.types['No mask']
+    )
+) for qid in (100, 500, 1000)]

cara/models.py

@@ -236,7 +236,7 @@ class WindowOpening(Ventilation):
     def air_exchange(self, room: Room, time: float) -> float:
         # If the window is shut, no air is being exchanged.
         if not self.active.triggered(time):
-            return 0.
+            return 0.25
 
         # Reminder, no dependence on time in the resulting calculation.
         inside_temp = self.inside_temp.value(time)
@@ -384,7 +384,7 @@ class Virus:
 Virus.types = {
     'SARS_CoV_2': Virus(
         halflife=1.1,
-        viral_load_in_sputum=10e8,
+        viral_load_in_sputum=1e9,
         # No data on coefficient for SARS-CoV-2 yet.
         # It is somewhere between 0.001 and 0.01 to have a 50% chance
         # to cause infection. i.e. 1000 or 100 SARS-CoV viruses to cause infection.

cara/output-files/qR_unmasked.csv

@@ -0,0 +1,9 @@
+,,Breathing,,,Speaking,,,Shouting,
+Percentiles,Seated,Light,Heavy,Seated,Light,Heavy,Seated,Light,Heavy
+1st,4.37e-06,1.08e-05,2.75e-05,3.32e-04,8.11e-04,2.08e-03,1.66e-03,4.08e-03,1.05e-02
+5th,1.86e-05,4.61e-05,1.18e-04,1.41e-03,3.47e-03,8.83e-03,7.06e-03,1.73e-02,4.44e-02
+20th,6.62e-04,1.65e-03,4.23e-03,5.04e-02,1.24e-01,3.23e-01,2.53e-01,6.21e-01,1.62e+00
+50th,4.59e-02,1.13e-01,2.96e-01,3.48e+00,8.62e+00,2.25e+01,1.75e+01,4.29e+01,1.13e+02
+80th,1.16e+00,2.84e+00,7.34e+00,8.77e+01,2.16e+02,5.59e+02,4.37e+02,1.08e+03,2.80e+03
+95th,7.90e+00,1.94e+01,5.10e+01,6.00e+02,1.48e+03,3.88e+03,3.00e+03,7.34e+03,1.94e+04
+99th,2.42e+01,5.91e+01,1.57e+02,1.83e+03,4.50e+03,1.19e+04,9.20e+03,2.24e+04,5.95e+04

cara/output-files/qr_masked.csv

@@ -0,0 +1,9 @@
+,,Breathing,,,Speaking,,,Shouting,
+Percentiles,Seated,Light,Heavy,Seated,Light,Heavy,Seated,Light,Heavy
+1st,8.32e-07,2.05e-06,5.25e-06,6.06e-05,1.51e-04,3.84e-04,3.06e-04,7.50e-04,1.91e-03
+5th,3.54e-06,8.77e-06,2.24e-05,2.58e-04,6.37e-04,1.62e-03,1.30e-03,3.20e-03,8.14e-03
+20th,1.26e-04,3.15e-04,8.04e-04,9.36e-03,2.30e-02,5.91e-02,4.66e-02,1.15e-01,2.95e-01
+50th,8.80e-03,2.17e-02,5.64e-02,6.40e-01,1.58e+00,4.11e+00,3.23e+00,7.92e+00,2.07e+01
+80th,2.21e-01,5.42e-01,1.40e+00,1.61e+01,3.95e+01,1.03e+02,8.08e+01,1.99e+02,5.12e+02
+95th,1.51e+00,3.71e+00,9.77e+00,1.10e+02,2.71e+02,7.11e+02,5.52e+02,1.35e+03,3.57e+03
+99th,4.62e+00,1.13e+01,3.02e+01,3.35e+02,8.30e+02,2.20e+03,1.68e+03,4.13e+03,1.10e+04

setup.cfg

@@ -16,3 +16,12 @@ ignore_missing_imports = True
 
 [mypy-mistune.*]
 ignore_missing_imports = True
+
+[mypy-tqdm.*]
+ignore_missing_imports = True
+
+[mypy-scipy.*]
+ignore_missing_imports = True
+
+[mypy-sklearn.*]
+ignore_missing_imports = True