- {% block report_scenarios_summary_table %} -
| Scenario | -P(I) | -Expected new cases | -
|---|---|---|
| {{ scenario_name }} | -{{ scenario_stats.probability_of_infection | non_zero_percentage }} | -{{ scenario_stats.expected_new_cases | float_format }} | -
+ {% block report_scenarios_summary_table %} +
| Scenario | +P(I) | +Expected new cases | +
|---|---|---|
| {{ scenario_name }} | +{{ scenario_stats.probability_of_infection | non_zero_percentage }} | +{{ scenario_stats.expected_new_cases | float_format }} | +
+
Notes for alternative scenarios:
+
-
+
- This graph shows the concentration of infectious quanta in the air. The filtration of Type I and FFP2 masks, if worn, applies not only to the emission rate but also to the individual exposure (i.e. inhalation). + For this reason, scenarios with different types of mask will show the same concentration on the graph but have different absorbed doses and infection probabilities. +
- If you have selected more sophisticated options, such as HEPA filtration or FFP2 masks, this will be indicated in the plot as the "base scenario", representing the inputs inserted in the form.
+ The other alternative scenarios shown for comparison will not include either HEPA filtration or FFP2 masks.
+
+
-
Notes for alternative scenarios:
-
-
-
- This graph shows the concentration of infectious quanta in the air. The filtration of Type I and FFP2 masks, if worn, applies not only to the emission rate but also to the individual exposure (i.e. inhalation). - For this reason, scenarios with different types of mask will show the same concentration on the graph but have different absorbed doses and infection probabilities. -
- If you have selected more sophisticated options, such as HEPA filtration or FFP2 masks, this will be indicated in the plot as the "base scenario", representing the inputs inserted in the form.
- The other alternative scenarios shown for comparison will not include either HEPA filtration or FFP2 masks.
-
-
+ Short-range interactions: {{ form.short_range_interactions|length }} +
-
+ {% for interaction in form.short_range_interactions %}
+
- Expiratory activity {{ loop.index if form.short_range_interactions|length > 1 }}: {{ interaction.expiration }} +
- Start time {{ loop.index if form.short_range_interactions|length > 1 }}: {{ interaction.start_time }} +
- Duration {{ loop.index if form.short_range_interactions|length > 1 }}: {{ interaction.duration }} {{ "minutes" if interaction.duration|float > 1 else "minute" }} + {% endfor %} +
Exposed occupant(s) activity time:
Start time: {{ form.exposed_start | minutes_to_time }}
@@ -408,42 +440,8 @@
Disclaimer:
- CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions. -
-- CARA models the concentration profile of potential infectious viruses in enclosed spaces with clear and intuitive graphs. - The user can set a number of parameters, including room volume, exposure time, activity type, mask-wearing and ventilation. - The report generated indicates how to avoid exceeding critical concentrations and chains of airborne transmission in spaces such as individual offices, meeting rooms and labs. -
-- The risk assessment tool simulates the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 airborne transmission therein. - The results DO NOT include short-range airborne exposure (where the physical distance is a significant factor) nor the other known modes of SARS-CoV-2 transmission. - Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures. -
-- The model used is based on scientific publications relating to airborne transmission of infectious diseases, dose-response exposures and aerosol science, as of February 2021. - It can be used to compare the effectiveness of different airborne-related risk mitigation measures. -
-- Note that this model applies a deterministic approach, i.e., it is assumed at least one person is infected and shedding viruses into the simulated volume. - Nonetheless, it is also important to understand that the absolute risk of infection is uncertain, as it will depend on the probability that someone infected attends the event. - The model is most useful for comparing the impact and effectiveness of different mitigation measures such as ventilation, filtration, exposure time, physical activity and - the size of the room, only considering long-range airborne transmission of COVID-19 in indoor settings. -
-- This tool is designed to be informative, allowing the user to adapt different settings and model the relative impact on the estimated infection probabilities. - The objective is to facilitate targeted decision-making and investment through comparisons, rather than a singular determination of absolute risk. - While the SARS-CoV-2 virus is in circulation among the population, the notion of 'zero risk' or 'completely safe scenario' does not exist. - Each event modelled is unique, and the results generated therein are only as accurate as the inputs and assumptions. -
-- CARA has not undergone review, approval or certification by competent authorities, and as a result, it cannot be considered - as a fully endorsed and reliable tool, namely in the assessment of potential viral emissions from infected hosts to be modelled. -
- + Disclaimer:
- CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions. -
-- CARA models the concentration profile of potential virions in enclosed spaces with clear and intuitive graphs. - The user can set a number of parameters, including room volume, exposure time, activity type, mask-wearing and ventilation. - The report generated indicates how to avoid exceeding critical concentrations and chains of airborne transmission in spaces such as individual offices, meeting rooms and labs. -
-- The risk assessment tool simulates the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 airborne transmission therein. - The results DO NOT include short-range airborne exposure (where the physical distance is a significant factor) nor the other known modes of SARS-CoV-2 transmission. - Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures. -
-- The model used is based on scientific publications relating to airborne transmission of infectious diseases, dose-response exposures and aerosol science, as of February 2021. - It can be used to compare the effectiveness of different airborne-related risk mitigation measures. -
-- Note that this model applies a deterministic approach, i.e., it is assumed at least one person is infected and shedding viruses into the simulated volume. - Nonetheless, it is also important to understand that the absolute risk of infection is uncertain, as it will depend on the probability that someone infected attends the event. - The model is most useful for comparing the impact and effectiveness of different mitigation measures such as ventilation, filtration, exposure time, physical activity and - the size of the room, only considering long-range airborne transmission of COVID-19 in indoor settings. -
-- This tool is designed to be informative, allowing the user to adapt different settings and model the relative impact on the estimated infection probabilities. - The objective is to facilitate targeted decision-making and investment through comparisons, rather than a singular determination of absolute risk. - While the SARS-CoV-2 virus is in circulation among the population, the notion of 'zero risk' or 'completely safe scenario' does not exist. - Each event modelled is unique, and the results generated therein are only as accurate as the inputs and assumptions. -
-- CARA has not undergone review, approval or certification by competent authorities, and as a result, it cannot be considered - as a fully endorsed and reliable tool, namely in the assessment of potential viral emissions from infected hosts to be modelled. -
-There are a few predefined activities in the tool at present.
- Office = All persons seated, talking occasionally (1/3rd of the time, with normal breathing the other 2/3rds of the time). Everyone (exposed and infected occupants) is treated the same in this model. -
- Meeting = All persons seated, having a conversation (approximately each occupant is 1/N % of the time talking, where N is the number of occupants). Everyone (exposed and infected occupants) is treated the same in this model. +
- Small meeting = Less than 10 participants. All persons seated, having a conversation (approximately each occupant is 1/N % of the time talking, where N is the number of occupants). Everyone (exposed and infected occupants) is treated the same in this model. +
- Large Meeting = 10 or more participants. Similar to a seminar with 'speakers and audience'. Infected occupant(s) is standing and speaking 1/3rd of the time, while the other occupants are seated.
- Library = All persons seated, breathing only (not talking), all the time.
- Call Centre = All persons seated, all talking simultaneously, all the time. This is a conservative profile, i.e. will show an increased
P(i)compared to office/meeting activity. Everyone (exposed and infected occupants) is treated the same in this model. - Control Room (day shift) = All persons seated, all talking 50% of the time. This is a conservative profile, i.e. will show an increased
P(i)compared to office/meeting activity. Everyone (exposed and infected occupants) is treated the same in this model.
diff --git a/cara/apps/templates/cern/calculator.report.html.j2 b/cara/apps/templates/cern/calculator.report.html.j2
index 36e65cd2..11c6f5c2 100644
--- a/cara/apps/templates/cern/calculator.report.html.j2
+++ b/cara/apps/templates/cern/calculator.report.html.j2
@@ -1,8 +1,9 @@
{% extends "base/calculator.report.html.j2" %}
-{% if ((prob_inf > 10) or (expected_new_cases >= 1)) %} {% set cern_level = 'red' %}
-{% elif (2 <= prob_inf <= 10) %} {% set cern_level = 'orange' %}
-{% else %} {% set cern_level = 'green' %}
+{% set cern_level = 'green-1' %}
+{% if ((prob_inf > 10) or (expected_new_cases >= 1)) %} {% set scale_warning = 'red' %}
+{% elif (2 <= prob_inf <= 10) %} {% set scale_warning = 'orange' %}
+{% else %} {% set scale_warning = 'green' %}
{% endif %}
{% block report_preamble_navtab %}
@@ -12,9 +13,9 @@
{% endblock report_preamble_navtab %}
{% block warning_animation %}
- {% if cern_level == 'red' %} {% set warning_color= 'bg-danger' %}
- {% elif cern_level == 'orange' %} {% set warning_color = 'bg-warning' %}
- {% elif cern_level == 'green' %} {% set warning_color = 'bg-success' %}
+ {% if scale_warning == 'red' %} {% set warning_color= 'bg-danger' %}
+ {% elif scale_warning == 'orange' %} {% set warning_color = 'bg-warning' %}
+ {% elif scale_warning == 'green' %} {% set warning_color = 'bg-success' %}
{% endif %}
- {% if scale_warning.level == "green-1" %} + {% if cern_level == "green-1" %}
Note: The CERN COVID Level is not specified.
@@ -72,13 +73,13 @@ {% endblock report_summary %} {% block report_summary_footnote %} - {% if cern_level == 'red' %} + {% if scale_warning == 'red' %} This exceeds the authorised risk threshold or number of expected new cases. The risk level must be reduced before this activity can be undertaken. - {% elif cern_level == 'orange' %} + {% elif scale_warning == 'orange' %} This activity has an elevated level of risk, ALARA principles must be applied to minimise the level of risk before undertaking the activity. See the footnotes for more details on the ALARA principles. - {% elif cern_level == 'green' %} + {% elif scale_warning == 'green' %} This level of risk is within acceptable parameters, no further actions are required. {% endif %} {% endblock report_summary_footnote %} @@ -133,7 +134,7 @@
diff --git a/cara/apps/templates/common_text.md.j2 b/cara/apps/templates/common_text.md.j2 index 5eebb32d..795c07b5 100644 --- a/cara/apps/templates/common_text.md.j2 +++ b/cara/apps/templates/common_text.md.j2 @@ -22,6 +22,41 @@ We wish to thank CERN’s HSE Unit, Beams Department, Experimental Physics Department, Information Technology Department, Industry, Procurement and Knowledge Transfer Department and International Relations Sector for their support to the study. Thanks to Doris Forkel-Wirth, Benoit Delille, Walid Fadel, Olga Beltramello, Letizia Di Giulio, Evelyne Dho, Wayne Salter, Benoit Salvant and colleagues from the COVID working group for providing expert advice and extensively testing the model. Finally, we wish to thank Fabienne Landua and the design service for preparing the illustrations and Alessandro Raimondo and Manuela Cirilli from the Knowledge Transfer Group for their continuous support. Our compliments towards the work and research performed by world leading scientists in this domain: Dr. Julian Tang, Prof. Manuel Gameiro, Dr. Linsey Marr, Prof. Lidia Morawska, Prof. Yuguo Li, and others – their scientific contribution was indispensable for this project. +## Disclaimer +
+ CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions. +
++ CARA models the concentration profile of virions in enclosed spaces with clear and intuitive graphs. + The user can set a number of parameters, including room volume, exposure time, activity type, mask-wearing and ventilation. + The report generated indicates how to avoid exceeding critical concentrations and chains of airborne transmission in spaces such as individual offices, meeting rooms and labs. +
++ The risk assessment tool simulates the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 airborne transmission therein. + The results DO NOT include short-range airborne exposure (where the physical distance is a significant factor) nor the other known modes of SARS-CoV-2 transmission. + Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures. +
++ The model used is based on scientific publications relating to airborne transmission of infectious diseases, dose-response exposures and aerosol science, as of February 2021. + It can be used to compare the effectiveness of different airborne-related risk mitigation measures. +
++ Note that this model applies a deterministic approach, i.e., it is assumed at least one person is infected and shedding viruses into the simulated volume. + Nonetheless, it is also important to understand that the absolute risk of infection is uncertain, as it will depend on the probability that someone infected attends the event. + The model is most useful for comparing the impact and effectiveness of different mitigation measures such as ventilation, filtration, exposure time, physical activity and + the size of the room, only considering long-range airborne transmission of COVID-19 in indoor settings. +
++ This tool is designed to be informative, allowing the user to adapt different settings and model the relative impact on the estimated infection probabilities. + The objective is to facilitate targeted decision-making and investment through comparisons, rather than a singular determination of absolute risk. + While the SARS-CoV-2 virus is in circulation among the population, the notion of 'zero risk' or 'completely safe scenario' does not exist. + Each event modelled is unique, and the results generated therein are only as accurate as the inputs and assumptions. +
++ CARA has not undergone review, approval or certification by competent authorities, and as a result, it cannot be considered + as a fully endorsed and reliable tool, namely in the assessment of potential viral emissions from infected hosts to be modelled. +
+ ## References Reference list can be found in the CARA paper: CERN-OPEN-2021-004